Simon Eid is Senior Vice President Asia-Pacific (APAC) at MongoDB and leads the sales teams across Australia and New Zealand, India, ASEAN, and Japan. Simon's go-to-market organisation in APAC is growing rapidly and has nearly tripled in size in the past three years. They are hiring in all regions. In this article, Simon discusses MongoDB’s opportunity in APAC and how he builds a culture of growth and accountability. Simon Eid, SVP APAC, MongoDB (left) and Anoop Dhankar, RVP ANZ, MongoDB (right) MongoDB's opportunity in Asia-Pacific Out of the top 13 economies by GDP in the world, five of them are located in APAC: China, Japan, Australia, India, and South Korea. And that's to say nothing of the ASEAN countries which alone have more than 650 million inhabitants. Combine this with the worldwide database market, one of the largest markets in the software industry. IDC estimates that it will grow to $137B in 2027, and MongoDB has just reached $1B in ARR. This gives you a sense of the massive market opportunity we have globally. Regardless of industry, product, or service, almost every company is becoming a technology company, which means that every company is becoming a data company. We believe MongoDB is the Developer Data Platform that is best placed to support and accelerate that trend. We’ve already captured thousands of customers around the globe, but it’s important to keep in mind that our world is still in the early stages of shifting to the cloud and changing how applications are built and run. Compared to other software, what's special about the market we play in is that the database is not a “nice-to-have”; it’s mission-critical for organisations. As our world continues to undergo this digital transformation, we have the opportunity to transform how our customers use software and data to innovate, create, and disrupt industries. For example, look at Cathay Pacific, Hong Kong's home airline carrier operating in more than 60 destinations worldwide. The company's digital team turned to MongoDB on their journey to become one of the first airlines to create a truly paperless flight deck. Flight Folder, their application built on MongoDB, consolidates dozens of different information sources into one place. Since the Flight Folder launch, Cathay Pacific has completed more than 340,000 flights with full digital integration in the flight deck. Their innovation is enabled by MongoDB. Building a team across regions and cultures Our team in APAC is unique because of the different markets and cultures within the region. What this means is that we go to market differently in India than we do in Australia, in Singapore than we do in South Korea, and so on. Each market is completely different, but within all of them, there is a huge opportunity. Different from many of our peers, in APAC we've established business leaders who run regionalized teams in India, ASEAN, and ANZ with all functions reporting to them. These teams essentially operate as their own business and implement local best practices into their strategy. But, it doesn’t mean they’re operating in a silo. At the leadership level, there is an immense amount of collaboration and sharing of experiences to identify what’s working and what isn’t within each region. We also have a fantastic global sales organisation that rolls out extensive training and best practices to help enable our local teams to best help our customers and grow the business. Members of our APAC team at a recent offsite in Phuket Culture The most important thing is culture. We have a very high standard around everything we do and how we interact with each other. We don’t entertain politics. You can teach someone new skills and coach them on how to be successful in a new role, but if they’re not aligned with the culture, they will not be a fit. It’s a non-negotiable for me and why the most important aspect of the hiring process is the cultural aspect. If you get the culture right, everything else starts to fall into place. What I hear at MongoDB and from the teams I've built at other companies is that this is the kind of culture they can really thrive and grow. At MongoDB, our culture is defined and shaped by six core values. One of the values that’s most important to my team is “Embrace the Power of Differences”. Within APAC, there are a variety of cultural identities and nuances that can often be difficult to navigate, whether it is cultural values, beliefs, or go-to-market strategy. It’s important that everyone who joins my team is respectful of each other’s regional culture. What we’ve done within the APAC region, and with teams across the globe, is take everyone on a journey to understand and embrace these cultural differences. Our role as leaders is to develop our teams, from the bottom all the way up, which is part of MongoDB’s BDR to CRO career development initiative. We need to develop the next wave of leaders so that they’re prepared to step up when the time comes. For APAC, this means that regardless of where someone is from, each team member has been coached and developed on the cultural nuances so that they can lead people and go to market in each of the different regions. It’s also important that each team member contributes to a culture of psychological safety. Being part of a high-growth tech company requires taking risks and making mistakes. We have a high standard and we hold each other accountable, but it never comes at the cost of creating an environment where people are afraid to fail. When someone faces setbacks, I encourage them to share those experiences so that we can collectively learn. Through mutual support, we foster a stronger team capable of delivering exceptional results. The future of MongoDB in Asia-Pacific For any organisation to be successful, I believe it’s critically important for the entire ecosystem to act as one. As I mentioned earlier, at MongoDB the whole country ecosystem is aligned around one set of goals, so it's not a case of different teams running off in different directions. The teams are willing to lean in and do what's required to help each other build a great business. I can confidently say that in APAC, we are one team. This means sales, marketing, customer success, solutions consulting, and professional services all working together to focus on three things: making customers successful, building technical champions, and driving new workloads. As we continue to grow our team and MongoDB’s footprint in the region, these are the three things that will drive our success. As I mentioned earlier, there's a huge opportunity for MongoDB in APAC. Despite hiring slowing down or stopping completely at many other organisations, we're continuing to invest heavily in the region. To give you a sense of that - we've nearly tripled the size of our APAC go-to-market team in the past three years, and we've got more open roles across the different functions and regions. If you want to be part of this journey, there are three things I want to reiterate: First, we are extremely passionate about our culture, from the field level up to the leadership level. As a team, this is the brand we bring to the market. Second, the opportunity here is massive based on the total addressable market and our current share. And third, we place critical importance on development. By joining this team, I can promise that you’ll be provided with countless opportunities to develop your career and make an impact. I’m confident in my team and the leadership we have in place who are ready to take MongoDB APAC to the next level. Join us!

Tens of thousands of customers and millions of developers rely on MongoDB Atlas to run business-critical applications because of its flexible document data model and ability to work with virtually any type of data using a single, intuitive developer data platform that can run on all major cloud providers. Earlier this year, we announced that we would enable developers to apply the benefits of the document model and a unified interface to streaming data with Atlas Stream Processing. In a short amount of time, we have seen a strong response from developers eager to use this capability to simplify building event-driven applications. To accelerate the development of our streaming offering, we are thrilled to announce that the team behind Grainite — a streaming application platform, backed by Sequoia Capital and Menlo Ventures, that makes it easy to read, process, store, and query events in real-time — has now joined MongoDB. Grainite was founded by world-class technologists Ashish Kumar, who spent over ten years running structured storage products and other high-scale infrastructure projects at Google, and Abhishek Chauhan, who previously served as CTO of Cloud Networking at Citrix. Ashish and Abhishek bring with them a team of talented engineers to MongoDB who will help accelerate the development of Atlas Stream Processing and the release of new capabilities that will make it even easier for customers to process and analyze streaming data for real-time application experiences. “We’re excited to be joining a company that shares our vision for making it effortless to build event-driven applications,” said Kumar. “We’re looking forward to continuing to develop a world-class streaming platform that will make it easier for developers to incorporate real-time data into their applications and becoming part of an organization that can significantly amplify the reach and impact of event-driven applications for developers and end users.” We look forward to welcoming the Grainite team to MongoDB and sharing updates on Atlas Stream Processing and our broader streaming roadmap in the near future.

Throughout 2023, MongoDB has recognized the exceptional successes our APAC and North America customers realize when they build with MongoDB Atlas. Today, we are pleased to announce the recipients of the 2023 EMEA MongoDB Innovation Awards. These customers join a premiere group of organizations that have been recognized for boldly exploring the power of data and harnessing it to build the applications of tomorrow. The professionals behind these innovative projects span industries, use cases, and geographies. However, what remains constant is each organization's unfailing commitment to delivering deeper insights, powerful features, and capabilities, as well as seamless experiences, to their customers. We congratulate each of the EMEA MongoDB Innovation Award winners for delivering big results and invite you to find inspiration in their work below. Building the Next Big Thing Since being originally founded in Finland as a food delivery service, Wolt expanded their offering into groceries, gifts, and other items, and makes it possible for people living in hundreds of cities across 25 countries to get whatever they need, delivered quickly and reliably to their front door. Due to the rapidly increasing scale in their business and new partnerships with enterprise retailers, Wolt needed to rethink their existing tooling that is used by their tens of thousands of merchant partners to manage their offering inside Wolt’s delivery platform. To provide their merchants with multi-venue management capabilities, increased automation, and no limitations on amounts of menu items, Wolt chose fully-managed MongoDB Atlas due to its flexible data document model, support for Kafka and event-driven architectures, high performance, and limitless scalability. Industry Transformation Gong’s Revenue Intelligence Platform uses proprietary AI technology to enable revenue teams to utilize customer interactions to increase business efficiency, improve decision-making, and accelerate revenue growth. Gong chose MongoDB Atlas as a high-performing transactional database due to its ability to handle Gong’s complex data structures and algorithms, and indeed MongoDB Atlas was able to support 30-40 million daily interactions and mission-critical search queries. Through the adoption of MongoDB Atlas, Gong’s queries take only 20-30 milliseconds, and with Atlas’ sharding capabilities, Gong future-proofed its environment for ongoing growth and gained greater control over its customer data. Innovative Leadership in Diversity, Equity, and Inclusion As part of its "Inclusion for All" strategy, Vodafone is committed to ensuring our digital society is accessible to all, and that women feel empowered to participate in it. In addition, Vodafone’s mission is to have 40% of women in management roles by 2030. Earlier this year, Vodafone UK teamed up with MongoDB to host interactive sessions and networking for “Digital & IT Women in Tech Week.” With a shared goal of reducing the gender gap in technology and inspiring young women to build their careers by pursuing leadership roles, the week’s events brought together more than 200 Vodafone employees to discuss breaking workplace biases and enhancing gender equality in the industry. In addition, Vodafone spoke at the 2023 MongoDB.local London event in the IDEA Lounge. Inspiring Innovation Ernst & Young LLP (EY) manages high volumes of transactional data and its clients and internal teams work under strict timelines to file taxes and meet regulatory deadlines. Their cloud-based Global VAT Reporting Tool (GVRT) platform automates and digitizes the preparation of 242 different types of returns across 79 countries. With support from MongoDB Professional Services, EY planned and executed a data migration from their previous database solution to MongoDB Atlas so that the GVRT tool could fully benefit from MongoDB’s developer data platform. Since migrating to Atlas, EY experienced a significant performance boost, they reduced costs by as much as 50%, and they are able to scale without limitations to handle increased data volumes, transactional loads, and concurrent user requests during peak periods. Find out Who Uses MongoDB and read more about our customers’ MongoDB Atlas successes.

Ya llevamos más de tres meses de nuestra gira mundial MongoDB.local que comenzó en Nueva York a principios de junio. Desde entonces, hemos seguido introduciendo mejoras de productos y nuevas capacidades, desde GA de MongoDB para VS Code hasta MongoDB 7.0 y Queryable Encryption. Hoy, me complace compartir los aspectos más destacados de los anuncios de productos recientes de nuestra conferencia de Londres de esta mañana. Experiencias de desarrollador eficientes e inteligentes para construir con MongoDB Siempre nos hemos comprometido a brindar la mejor experiencia a los desarrolladores porque sabemos que el tiempo del desarrollador es uno de los bienes más preciados de cualquier organización. Cuando analizamos las tareas más comunes que realizan los desarrolladores a diario, reconocimos dos áreas de mejora: hacer que el desarrollo contra Atlas sea más eficiente y facilitar la escritura de consultas MongoDB. Queremos brindarles a los desarrolladores la forma más ergonómica de trabajar con MongoDB Atlas durante todo su recorrido. Para muchos desarrolladores, ese viaje comienza trabajando con MongoDB localmente antes de pasar a la nube, razón por la cual estamos invirtiendo en una excelente experiencia de desarrollo local. A partir de hoy, los desarrolladores pueden utilizar Atlas CLI para gestionar entornos de desarrollo locales con la misma experiencia que los clústeres de Atlas en la nube. Más allá de facilitar la implementación y gestión de instancias de desarrollo, también queremos llevar la amplitud de nuestra plataforma de datos de desarrollador a entornos locales. La nueva experiencia Atlas CLI, disponible en versión preliminar pública, también viene con Atlas Search y Atlas Vector Search integrados para que los desarrolladores puedan crear y administrar índices de búsqueda y consultas dentro de sus flujos de trabajo de desarrollo. Esta es la primera de más inversiones por venir a medida que continuamos creando una experiencia perfecta para los servicios en Atlas, desde el sandbox hasta las pruebas y la producción. El otro problema que queremos resolver es la velocidad y estamos entusiasmados de utilizar la tecnología de IA generativa para presentar varias experiencias nuevas e inteligentes para desarrolladores. Consultar datos debería ser tan fácil como hacer una pregunta en un lenguaje que le resulte natural. Los desarrolladores ahora pueden hacer preguntas en inglés sencillo y Compass, nuestra GUI de MongoDB, generará la consulta correspondiente en la sintaxis del lenguaje de consulta de MongoDB. Desde consultas simples hasta agregaciones más complejas, esta experiencia reducirá la fricción de aprender el lenguaje de consulta de MongoDB y ayudará a los desarrolladores a iterar y crear nuevas funciones más rápidamente. También presentamos una nueva interfaz de idioma para Atlas Charts para que los desarrolladores puedan visualizar fácilmente los datos en MongoDB y un chatbot de IA para nuestros recursosde documentación. Para los clientes que se embarcan en un viaje de migración desde el uso de bases de datos relacionales al uso de MongoDB, uno de los pasos más difíciles e importantes es convertir cientos, si no miles, de consultas y códigos de aplicaciones. Disponible ahora en versión preliminar privada, la conversión de consultas SQL en Relational Migrator puede convertir consultas y procedimientos almacenados a la sintaxis del lenguaje de consulta MongoDB a escala, trasladando recursos de la creación de consultas a la revisión e implementación. Ejecute MongoDB en cualquier lugar: desde el borde hasta la nube Uno de los beneficios de MongoDB del que hemos estado orgullosos desde el principio es la flexibilidad para construir con él en cualquier lugar: en una máquina local para desarrollo, completamente administrado a través de múltiples nubes públicas, en las instalaciones o en una nube privada, e incluso en dispositivos móviles y de borde. A medida que la movilidad y el IoT se vuelven más esenciales para las operaciones en todas las industrias, uno de los requisitos clave es poder sincronizar y mover datos entre entornos. Hoy, nos complace anunciar Atlas for the Edge, que acerca las capacidades de procesamiento y almacenamiento de datos a donde más se necesitan: justo donde se generan los datos. Con los servidores Atlas Edge que se pueden implementar en cualquier lugar y la resolución de conflictos incorporada, los clientes pueden crear fácilmente arquitecturas radiales para potenciar las experiencias de los clientes que requieren una latencia ultrabaja o una computación más intensa cerca de donde se generan los datos. Desde la fabricación hasta el comercio minorista y la atención médica, Atlas for the Edge permite a los clientes desbloquear más casos de uso que dependen de una capa de datos conectada a través de nubes públicas, ubicaciones informáticas locales o de borde, y sensores y dispositivos. Cree la próxima generación de aplicaciones impulsadas por IA con una plataforma de datos para desarrolladores Desde nuestro anuncio público de vista previa a principios de este año, hemos visto mucho interés en Atlas Vector Search, particularmente en la creación de arquitecturas RAG (generación aumentada de recuperación) para aplicaciones impulsadas por IA generativa. Desde nuevas empresas hasta empresas establecidas, los clientes están ansiosos por crear aplicaciones más inteligentes con el respaldo de una plataforma moderna, altamente escalable y de alto rendimiento. La capacidad de almacenar incrustaciones de vectores junto con fuentes y metadatos ha simplificado la forma en que los desarrolladores integran GenAI en aplicaciones nuevas y existentes, y con la introducción de la etapa de agregación $vectorSearch, será aún más fácil prefiltrar y ajustar los resultados utilizando el lenguaje de consulta MongoDB. , todo en una única plataforma en Atlas. Finalmente, reconocemos la necesidad de brindar a los desarrolladores recursos prácticos para ampliar sus habilidades y conocimientos. Además del nuevo contenido disponible en MongoDB University, anunciamos MongoDB Press, un medio para publicar conocimientos técnicos y de liderazgo sobre MongoDB. Los dos primeros libros tratan sobre agregaciones y dominio de MongoDB 7.0. También agregamos una biblioteca de soluciones en nuestro sitio web con casos de uso organizados por sectores verticales de la industria para mostrar el arte de lo que es posible con nuestra plataforma de datos para desarrolladores. Para ver más anuncios y obtener las últimas actualizaciones de productos, visite nuestra página Novedades. Dirígete al centro MongoDB.local para ver dónde apareceremos a continuación.

Já completamos mais de três meses de nossa turnê mundial MongoDB.local, que começou em Nova York no início de junho. Desde então, continuamos a introduzir melhorias no produto e novos recursos, desde o GA do MongoDB para VS Code até o MongoDB 7.0 e Queryable Encryption. Hoje, tenho o prazer de compartilhar os destaques dos recentes anúncios de produtos da nossa conferência em Londres esta manhã. Experiências de desenvolvedor eficientes e inteligentes para construção com MongoDB Sempre estivemos comprometidos em fornecer a melhor experiência ao desenvolvedor porque sabemos que o tempo do desenvolvedor é um dos bens mais preciosos em qualquer organização. Quando analisamos as tarefas mais comuns que os desenvolvedores realizam diariamente, reconhecemos duas áreas que precisam ser melhoradas: tornar o desenvolvimento no Atlas mais eficiente e facilitar a gravação de consultas no MongoDB. Queremos oferecer aos desenvolvedores a maneira mais ergonômica de trabalhar com o MongoDB Atlas durante toda a sua jornada. Para muitos desenvolvedores, essa jornada começa trabalhando com o MongoDB localmente antes de migrar para a cloud – e é por isso que estamos investindo em uma excelente experiência de desenvolvimento local. A partir de hoje, os desenvolvedores podem usar a CLI do Atlas para managed ambientes de desenvolvimento local com a mesma experiência do Atlas cluster na cloud. Além de facilitar a implantação e managed de instâncias de desenvolvimento, também queremos levar a amplitude de nossa plataforma de dados de desenvolvedor para ambientes locais. A nova experiência Atlas CLI, disponível em versão prévia pública, também vem com Atlas Search e Atlas Vector Search integrados para que os desenvolvedores possam criar e managed índices de pesquisa e consultas em seus fluxos de trabalho de desenvolvimento. Este é o primeiro de mais investimentos que virão à medida que continuamos a construir uma experiência perfeita para serviços no Atlas, desde sandbox até testes e produção. O outro problema que queremos resolver é a velocidade, e estamos entusiasmados em usar a tecnologia de IA generativa para apresentar diversas novas experiências inteligentes para desenvolvedores. Consultar dados deve ser tão fácil quanto fazer uma pergunta em uma linguagem que lhe pareça natural. Os desenvolvedores agora podem fazer perguntas em inglês simples e o Compass, nossa GUI do MongoDB, gerará a consulta correspondente na sintaxe da linguagem de consulta do MongoDB. Desde consultas simples até agregações mais complexas, esta experiência reduzirá o atrito de aprender a linguagem de consulta do MongoDB e ajudará os desenvolvedores a iterar e construir novos recursos mais rapidamente. Também estamos introduzindo uma nova interface de linguagem para Atlas Charts para que os desenvolvedores possam visualizar facilmente os dados no MongoDB e um chatbot de IA para nossos recursos de documentação. Para clientes que estão embarcando em uma jornada de migração do uso relational database para o MongoDB, uma das etapas mais difíceis e importantes é a conversão de centenas, senão milhares, de consultas e códigos de aplicativos. Disponível agora em visualização privada, a conversão de consulta SQL no Relational Migrator pode converter consultas e procedimentos armazenados em sintaxe de linguagem de consulta MongoDB em escala, transferindo recursos desde a criação de consultas até a revisão e implementação. Execute o MongoDB em qualquer lugar – da borda à cloud Um dos benefícios do MongoDB do qual nos orgulhamos desde o início é a flexibilidade de construir com ele em qualquer lugar - em uma máquina local para desenvolvimento, totalmente managed em diversas cloud públicas, no local ou em uma cloud privada, e até mesmo em dispositivos móveis e de ponta. À medida que a mobilidade e a IoT se tornam mais essenciais para as operações em todos os setores, um dos principais requisitos é ser capaz de sincronizar e mover dados entre ambientes. Hoje, temos o prazer de anunciar o Atlas for the Edge, que aproxima os recursos de processamento e armazenamento de dados de onde eles são mais necessários – exatamente onde os dados são gerados. Com os servidores Atlas Edge que podem ser implantados em qualquer lugar e com resolução de conflitos integrada, os clientes podem criar facilmente arquiteturas hub and spoke para potencializar as experiências do cliente que exigem latência ultrabaixa ou computação mais pesada perto de onde os dados são gerados. Da fabricação ao varejo e à saúde, o Atlas for the Edge permite que os clientes descubram mais casos de uso que dependem de uma camada de dados conectada em cloud pública, locais de computação no local ou na borda, além de sensores e dispositivos. Crie a próxima geração de aplicativos baseados em IA com uma plataforma de dados de desenvolvedor Desde nosso anúncio de visualização pública no início deste ano, vimos muito interesse no Atlas Vector Search, particularmente na construção de arquiteturas RAG (geração aumentada de recuperação) para aplicativos alimentados por IA generativa. Desde startups até empresas estabelecidas, os clientes estão ansiosos para construir aplicações mais inteligentes com o apoio de uma plataforma moderna, altamente escalável e de alto desempenho. A capacidade de armazenar incorporações de vetores junto com fontes e metadados simplificou a forma como os desenvolvedores incorporam GenAI em aplicativos novos e existentes e, com a introdução do estágio de agregação $vectorSearch, será ainda mais fácil pré-filtrar e ajustar os resultados usando a linguagem de consulta MongoDB , tudo em uma única plataforma no Atlas. Finalmente, reconhecemos a necessidade de capacitar os desenvolvedores com recursos práticos para expandir suas habilidades e conhecimentos. Além dos novos conteúdos disponíveis na MongoDB University, anunciamos o MongoDB Press, um meio para publicação de conhecimento técnico e de liderança sobre o MongoDB. Os dois primeiros livros são sobre agregações e domínio do MongoDB 7.0. Também adicionamos uma biblioteca de soluções em nosso site com casos de uso organizados por setores verticais do setor para mostrar a arte do que é possível fazer com nossa plataforma de dados de desenvolvedores. Para ver mais anúncios e obter as atualizações mais recentes do produto, visite nossa página Novidades. Vá para o hub MongoDB.local para ver onde apareceremos em seguida.

Wir sind jetzt mehr als drei Monate auf unserer MongoDB.local-Welttournee , die Anfang Juni in NYC begann . Seitdem haben wir weiterhin Produktverbesserungen und neue Funktionen eingeführt, von der GA von MongoDB für VS Code bis hin zu MongoDB 7.0 und Queryable Encryption. Heute freue ich mich, Ihnen die Highlights der jüngsten Produktankündigungen unserer Londoner Konferenz heute Morgen mitzuteilen. Effiziente und intelligente Entwicklererfahrungen für die Erstellung mit MongoDB Wir sind seit jeher bestrebt, die beste Entwicklererfahrung zu bieten, weil wir wissen, dass Entwicklerzeit eines der wertvollsten Güter in jedem Unternehmen ist. Als wir uns die häufigsten Aufgaben angesehen haben, die Entwickler täglich ausführen, haben wir zwei Bereiche mit Verbesserungsbedarf erkannt: die Entwicklung gegenüber Atlas effizienter zu gestalten und das Schreiben von MongoDB-Abfragen einfacher zu machen. Wir möchten Entwicklern während ihrer gesamten Reise die ergonomischste Möglichkeit bieten, mit MongoDB Atlas zu arbeiten. Für viele Entwickler beginnt dieser Weg mit der lokalen Arbeit mit MongoDB, bevor sie in die cloud wechseln – deshalb investieren wir in ein großartiges lokales Entwicklungserlebnis. Ab heute können Entwickler die Atlas CLI verwenden, um managed lokale Entwicklungsumgebungen mit der gleichen Erfahrung wie Atlas cluster in der cloud. Wir möchten nicht nur die Bereitstellung und managed von Entwicklungsinstanzen vereinfachen, sondern auch die Breite unserer Entwicklerdatenplattform in lokale Umgebungen übertragen. Das neue Atlas CLI-Erlebnis, das in der öffentlichen Vorschau verfügbar ist, verfügt außerdem über integrierte Atlas Search und Atlas Vector Search, sodass Entwickler managed Index und Abfragen innerhalb ihrer Entwicklungsworkflows erstellen und können. Dies ist die erste von weiteren Investitionen, die noch folgen werden, während wir weiterhin ein nahtloses Erlebnis für Dienste in Atlas aufbauen, von der Sandbox bis hin zu Tests und Produktion. Das andere Problem, das wir lösen möchten, ist die Geschwindigkeit, und wir freuen uns, die generative KI-Technologie zu nutzen, um mehrere neue intelligente Entwicklererlebnisse einzuführen. Das Abfragen von Daten sollte so einfach sein wie das Stellen einer Frage in einer Sprache, die sich für Sie natürlich anfühlt. Entwickler können jetzt Fragen in einfachem Englisch stellen und Compass, unsere MongoDB-GUI, generiert die entsprechende Abfrage in der Syntax der MongoDB-Abfragesprache. Von einfachen Abfragen bis hin zu komplexeren Aggregationen wird diese Erfahrung den Aufwand beim Erlernen der Abfragesprache von MongoDB verringern und Entwicklern helfen, neue Funktionen schneller zu iterieren und zu erstellen. Wir führen außerdem eine neue Sprachschnittstelle für Atlas Charts, damit Entwickler Daten einfach in MongoDB visualisieren können, sowie einen KI-Chatbot für unsere Dokumentationsressourcen. Für Kunden, die sich auf eine Migrationsreise von der Verwendung relational database zur Verwendung von MongoDB begeben, ist die Konvertierung von Hunderten, wenn nicht Tausenden von Abfragen und Anwendungscode einer der schwierigsten und wichtigsten Schritte. Die SQL-Abfragekonvertierung in Relational Migrator ist jetzt in der privaten Vorschau verfügbar und kann Abfragen und gespeicherte Prozeduren bei Skalierung in die MongoDB-Abfragesprachensyntax konvertieren, wodurch Ressourcen von der Abfrageerstellung auf die Überprüfung und Implementierung verlagert werden. Führen Sie MongoDB überall aus – vom Edge bis cloud Einer der Vorteile von MongoDB, auf den wir von Anfang an stolz waren, ist die Flexibilität, überall damit zu bauen – auf einem lokalen Computer für die Entwicklung, vollständig managed über mehrere öffentliche Clouds, vor Ort oder in einer privaten cloud und sogar auf mobilen und Edge-Geräten. Da Mobilität und IoT für den Betrieb in allen Branchen immer wichtiger werden, besteht eine der wichtigsten Anforderungen darin, Daten umgebungsübergreifend synchronisieren und verschieben zu können. Wir freuen uns, heute Atlas for the Edge ankündigen zu können, das Datenverarbeitungs- und Speicherfunktionen näher dorthin bringt, wo sie oft am meisten benötigt werden – genau dort, wo Daten generiert werden. Mit Atlas Edge Servers, die überall eingesetzt werden können, und integrierter Konfliktlösung können Kunden ganz einfach Hub-and-Spoke-Architekturen erstellen, um Kundenerfahrungen zu ermöglichen, die eine extrem niedrige Latenz oder aufwändigere Berechnungen in der Nähe des Ortes erfordern, an dem die Daten generiert werden. Von der Fertigung über den Einzelhandel bis hin zum Gesundheitswesen ermöglicht Atlas for the Edge Kunden die Erschließung weiterer Anwendungsfälle, die auf einer verbundenen Datenschicht über öffentliche Cloud-, On-Premise- oder Edge-Computing-Standorte sowie Sensoren und Geräte hinweg basieren. Erstellen Sie die nächste Generation KI-gestützter Anwendungen mit einer Entwicklerdatenplattform Seit unserer öffentlichen Vorschau ankündigung Anfang dieses Jahres haben wir großes Interesse an Atlas Vector Search festgestellt, insbesondere am Aufbau von RAG-Architekturen (Retrieval Augmented Generation) für Anwendungen, die auf generativer AI basieren. Von Startups bis hin zu etablierten Unternehmen sind Kunden bestrebt, intelligentere Anwendungen mit der Unterstützung einer modernen, hoch skalierbaren und leistungsstarken Plattform zu entwickeln. Die Möglichkeit, Vektoreinbettungen neben Quell- und Metadaten zu speichern, hat die Art und Weise vereinfacht, wie Entwickler GenAI in neue und bestehende Anwendungen integrieren, und mit der Einführung der $vectorSearch-Aggregationsstufe wird es noch einfacher, Ergebnisse mithilfe der MongoDB-Abfragesprache vorzufiltern und abzustimmen , alles auf einer einzigen Plattform auf Atlas. Schließlich sind wir uns der Notwendigkeit bewusst, Entwicklern praktische Ressourcen zur Erweiterung ihrer Fähigkeiten und Kenntnisse zur Verfügung zu stellen. Zusätzlich zu den neuen Inhalten, die auf der MongoDB University verfügbar sind, haben wir MongoDB Press angekündigt, ein Medium zur Veröffentlichung von Fach- und Führungswissen über MongoDB. In den ersten beiden Büchern geht es um Aggregationen und die Beherrschung von MongoDB 7.0. Wir haben auf unserer Website außerdem eine Lösungsbibliothek mit nach Branchen geordneten Anwendungsfällen hinzugefügt, um zu zeigen, was mit unserer Entwicklerdatenplattform möglich ist. Weitere Ankündigungen und die neuesten Produktaktualisierungen finden Sie auf unserer Seite „What's New“. Gehen Sie zum MongoDB.local Hub, um zu sehen, wo wir unsere nächste lokale Konferenz veranstalten.

Nous sommes maintenant à plus de trois mois de notre tournée mondiale MongoDB.local qui a débuté à New Yorkau début du mois de juin. Depuis lors, nous avons continué à présenter des améliorations de produits et de nouvelles capacités, de l'AG de MongoDB for VS Code à MongoDB 7.0 et Queryable Encryption. Aujourd'hui, je suis ravi de partager les points forts des récentes annonces de produits lors de notre conférence de Londres ce matin. Des expériences de développement efficaces et intelligentes pour construire avec MongoDB Nous nous sommes toujours engagés à offrir la meilleure expérience aux développeurs, car nous savons que leur temps est l'une des denrées les plus précieuses de toute organisation. Lorsque nous avons examiné les tâches les plus courantes effectuées par les développeurs au quotidien, nous avons identifié deux domaines d'amélioration : rendre le développement contre Atlas plus efficace et faciliter l'écriture des requêtes MongoDB. Nous voulons donner aux développeurs la façon la plus ergonomique de travailler avec MongoDB Atlas tout au long de leur parcours. Pour de nombreux développeurs, ce parcours commence par une utilisation locale de MongoDB avant de passer au cloud - c'est pourquoi nous investissons dans une excellente expérience de développement local. Dès aujourd'hui, les développeurs peuvent utiliser le Atlas CLI pour managed environnements de développement locaux avec la même expérience que Atlas cluster dans le nuage. En plus de faciliter le déploiement et le développement de managed instance, nous voulons aussi apporter l'étendue de notre plateforme de données pour les développeurs aux environnements locaux. La nouvelle expérience Atlas CLI, disponible en avant-première publique, intègre également Atlas Search et Atlas Vector Search afin que les développeurs puissent créer et managed des index et des requêtes de recherche dans le cadre de leurs processus de développement. C'est le premier d'une série d'investissements à venir, car nous continuons à construire une expérience transparente pour les services dans Atlas, du bac à sable aux tests et à la production. L' autre problème que nous voulons résoudre est celui de la rapidité, et nous sommes ravis d'utiliser la technologie de l'IA générative pour introduire plusieurs nouvelles expériences intelligentes pour les développeurs. L'interrogation des données devrait être aussi simple que de poser une question dans un langage qui vous semble naturel. Les développeurs peuvent désormais poser des questions en anglais et Compass, notre interface graphique MongoDB, générera la requête correspondante dans la syntaxe du langage de requête MongoDB. Des requêtes simples aux agrégations plus complexes, cette expérience réduira la friction liée à l'apprentissage du langage de requête de MongoDB et aidera les développeurs à itérer et à construire de nouvelles fonctionnalités plus rapidement. Nous introduisons également une nouvelle interface linguistique pour Atlas Charts afin que les développeurs puissent facilement visualiser les données dans MongoDB, ainsi qu'un chatbot IA pour nos ressources documentaires. Pour les clients qui se lancent dans une migration de relational database vers MongoDB, l'une des étapes les plus difficiles et les plus importantes consiste à convertir des centaines, voire des milliers, de requêtes et de codes d'application. Disponible dès à présent en avant-première privée, la conversion de requêtes SQL dans Relational Migrator peut convertir les requêtes et les procédures stockées en syntaxe de langage de requête MongoDB au répartir, transférant ainsi les ressources de la création de requêtes à la révision et à l'implémentation. Exécuter MongoDB n'importe où - de la périphérie à l'intérieur cloud L'un des avantages de MongoDB dont nous sommes fiers depuis le début est la flexibilité de construire avec lui n'importe où - sur une machine locale pour le développement, entièrement managed à travers plusieurs nuages publics, sur site ou dans un nuage privé, et même sur des appareils mobiles et périphériques. Alors que la mobilité et IoT deviennent de plus en plus essentiels aux opérations dans tous les secteurs, l'une des principales exigences est de pouvoir synchroniser et déplacer les données entre les environnements. Aujourd'hui, nous sommes heureux d'annoncer Atlas for the Edge, qui rapproche les capacités de traitement et de stockage des données de l'endroit où elles sont le plus souvent nécessaires, c'est-à-dire là où les données sont générées. Grâce aux serveurs Atlas Edge qui peuvent être déployés n'importe où et à la résolution de conflits intégrée, les clients peuvent facilement créer des architectures en étoile pour alimenter les clients d'expérience qui ont besoin d'une latence ultra-faible ou de calculs plus lourds à proximité de l'endroit où les données sont générées. De la fabrication à la vente au détail en passant par la santé, Atlas for the Edge permet aux clients de débloquer davantage de cas d'utilisation qui s'appuient sur une couche de données connectées à travers des emplacements de cloud public, sur site ou d'informatique périphérique, ainsi que des capteurs et des appareils. Créez la prochaine génération d'applications alimentées par l'IA avec une plateforme de données pour développeurs. Depuis notre annonce en avant-première publique en début d'année, nous avons constaté un grand intérêt pour Atlas Vector Search, en particulier pour la construction d'architectures RAG (retrieval augmented generation) pour les applications alimentées par AI générative. Qu'il s'agisse de startups ou d'entreprises établies, les clients sont impatients de créer des applications plus intelligentes avec le soutien d'une plateforme moderne, hautement évolutive et performante. La possibilité de stocker des embeddings vectoriels avec les sources et les métadonnées a simplifié la façon dont les développeurs intègrent la GenAI dans les applications nouvelles et existantes. Avec l'introduction de l'étape d'agrégation $vectorSearch, il sera encore plus facile de pré-filtrer et d'ajuster les résultats en utilisant le langage de requête MongoDB, le tout dans une plateforme unique sur Atlas. Enfin, nous reconnaissons la nécessité d'offrir aux développeurs des ressources pratiques pour développer leurs compétences et leurs connaissances. En plus du nouveau contenu disponible sur MongoDB University, nous avons annoncé MongoDB Press, un moyen de publier des connaissances techniques et de leadership sur MongoDB. Les deux premiers livres sont consacrés aux agrégations et à la maîtrise de MongoDB 7.0. Nous avons également ajouté une bibliothèque de solutions sur notre site web avec des cas d'utilisation organisés par secteur d'activité afin de montrer ce qu'il est possible de faire avec notre plateforme de données pour les développeurs. Pour voir d'autres annonces et obtenir les dernières mises à jour de produits, visitez notre page "Nouveautés". Rendez-vous sur le hub MongoDB.local pour voir où nous nous rendrons ensuite.

Today, we’re excited to announce our new integration with Confluent Cloud. MongoDB Atlas Vector Search users now have simple access to data streams across their entire business, enabling them to build cutting-edge Generative AI applications that are grounded in a real-time, contextual, and trustworthy knowledge base. Think of an application like ChatGPT, but if it knew everything about your private enterprise data, including constant awareness of what’s happening in the world and your business right now. Atlas Vector Search allows you to search intelligently across any unstructured data, using the power of Large Language models (LLMs). With Confluent’s data streaming platform, you can provide a continuous supply of AI-ready data for the development of sophisticated customer experiences, bridging the gap between legacy data systems and the modern data stack. High-value, trusted AI applications require real-time data Real-time AI needs real-time data from across your organization. The promise of real-time AI is only unlocked when models have all the freshest contextual data they need to respond just in time with the most accurate, relevant, and helpful information. However, building these real-time data connections across on-prem, multi-cloud, public, and private cloud environments for AI use cases is not trivial. Traditional data integration and processing tools are batch-based and inflexible, creating an untenable number of tightly coupled point-to-point connections that are hard to scale and lack governance. As a result, the data made available is stale and of low fidelity. This introduces unavoidable latency into the AI application and may outright block implementation altogether. The difficulty in gaining access to high-quality, ready-to-use, contextual, and trustworthy data in real-time is hindering developer agility and the pace of AI innovation. Confluent's data streaming platform fuels MongoDB Atlas Vector Search with real-time data With the MongoDB Kafka Connector, users can easily configure MongoDB Atlas as a destination for customer 360 data from Confluent Cloud. This data is converted into vector embeddings using various machine learning models (OpenAI, HuggingFace, and more) and orchestrated by Atlas Triggers. Then using Atlas Vector Search, this data can be indexed and searched efficiently to power use cases such as semantic search, recommendation engines, Q&A systems, and many others. We demonstrate a Chatbot for e-commerce that will allow users to ask natural language questions to discover what they need and then get recommendations on products to buy that suit their preferences. Some of the data required in this scenario includes the currently available inventory, the shipping options, and their session browsing history. The users can refine their product recommendations using a conversational interface, all the while ensuring that the products being recommended are rooted in real-time data. The benefits of being able to effectively use real-time data are immense, almost critical, in this scenario, since recommending a product that’s not available or can’t be delivered to a user’s location in the time frame they require would mean a lost sale and a dissatisfied customer. The inventory data is rapidly changing - products go in and out of stock constantly. Hence the customer chat/assistant application will need to quickly come up with new sets of recommendations. With Confluent, MongoDB Atlas Vector Search users can break down data silos, promote data reusability, improve engineering agility, and foster greater trust throughout their organization. This allows more teams to securely and confidently unlock the full potential of all their data with MongoDB Atlas Vector Search. Confluent enables organizations to make real-time contextual inferences on an astonishing amount of data by bringing well-curated, trustworthy streaming data to AI systems, vector databases, and AI-powered applications. With easy access to data streams from across their entire business, MongoDB Atlas Vector Search users can now: Create a real-time knowledge base: Build a shared source of real-time truth for all your operational and analytical data, no matter where it lives for sophisticated model building and fine-tuning Bring real-time context at query time: Convert raw data into meaningful chunks with real-time enrichment and continually update your embedding databases for your GenAI use cases Build governed, secured, and trusted AI: Establish data lineage, quality, and traceability, providing all your teams with a clear understanding of data origin, movement, transformations, and usage Experiment, scale, and innovate faster: Reduce innovation friction as new AI apps and models become available. Decouple data from your data science tools and production AI apps to test and build faster MongoDB Atlas Vector Search and Confluent enable simple development of real-time AI applications Our new Confluent integration enables all your teams to tap into a continuously enriched real-time knowledge base, so they can quickly scale and build AI-enabled applications using trusted data streams. Here’s a demo video to demonstrate how this works: Getting started Get started by creating a MongoDB Atlas account if you don't already have one. Just click on “Register.” MongoDB offers a free-forever Atlas cluster in the public cloud service of your choice. To learn more about Atlas Vector Search, visit the product page. Not yet a Confluent customer? Start your free trial of Confluent Cloud today. New sign-ups receive $400 to spend during their first 30 days—no credit card required.

This post is also available in: Deutsch, Français, Español, Português. We’re now more than three months into our MongoDB.local world tour that kicked off in NYC earlier this June. Since then, we’ve continued to introduce product enhancements and new capabilities, from the GA of MongoDB for VS Code to MongoDB 7.0 and Queryable Encryption. Today, we're excited to share the highlights of recent product announcements from our London conference this morning. Efficient and intelligent developer experiences for building with MongoDB We’ve always been committed to providing the best developer experience because we know that developer time is one of the most precious commodities in any organization. When we looked at the most common tasks developers perform on a daily basis, we recognized two areas for improvement: making development against Atlas more efficient and making it easier to write MongoDB queries. We want to give developers the most ergonomic way to work with MongoDB Atlas throughout their entire journey. For many developers, that journey begins by working with MongoDB locally before moving to the cloud - which is why we’re investing in a great local development experience. Starting today, developers can use the Atlas CLI to manage local development environments with the same experience as Atlas clusters in the cloud. Beyond making it easy to deploy and manage development instances, we also want to bring the breadth of our developer data platform to local environments. The new Atlas CLI experience, available in public preview, also comes with integrated Atlas Search and Atlas Vector Search so developers can create and manage search indexes and queries within their development workflows. This is the first of more investments to come as we continue to build a seamless experience for services in Atlas from sandbox to testing and production. The other problem we want to solve is speed, and we’re excited to use generative AI technology to introduce several new intelligent developer experiences. Querying data should be as easy as asking a question in a language that feels natural to you. Developers can now ask questions in plain English and Compass, our MongoDB GUI, will generate the corresponding query in MongoDB query language syntax. From simple queries to more complex aggregations, this experience will reduce the friction of learning MongoDB’s query language and help developers iterate and build new features more quickly. We’re also introducing a new language interface for Atlas Charts so developers can easily visualize data in MongoDB and an AI chatbot for our documentation resources. For customers embarking on a migration journey from using relational databases to using MongoDB, one of the most difficult and important steps is converting hundreds, if not thousands, of queries and application code. Available now in private preview, SQL query conversion in Relational Migrator can convert queries and stored procedures to MongoDB query language syntax at scale, shifting resources from query creation to review and implementation. Run MongoDB anywhere - from edge to cloud One of the benefits of MongoDB that we’ve been proud of since the beginning is the flexibility to build with it anywhere - on a local machine for development, fully managed across multiple public clouds, on-premises or in a private cloud, and even on mobile and edge devices. As mobility and IoT become more essential to operations across industries, one of the key requirements is being able to sync and move data across environments. Today, we’re excited to announce Atlas for the Edge, which brings data processing and storage capabilities closer to where it’s often most needed - right where data is generated. With Atlas Edge Servers that can be deployed anywhere and built-in conflict resolution, customers can easily create hub and spoke architectures to power customer experiences that require ultra-low latency or heavier computation close to where data is generated. From manufacturing to retail to healthcare, Atlas for the Edge enables customers to unlock more use cases that rely on a connected data layer across public clouds, on-premise or edge computing locations, and sensors and devices. Build the next generation of AI-powered applications with a developer data platform Since our public preview announcement earlier this year, we’ve seen a lot of interest in Atlas Vector Search, particularly in building RAG (retrieval augmented generation) architectures for applications powered by Generative AI. From startups to established companies, customers are eager to build more intelligent applications with the backing of a modern, highly scalable, and performant platform. The ability to store vector embeddings alongside source and metadata has simplified how developers build GenAI into new and existing applications, and with the introduction of the $vectorSearch aggregation stage, it will be even easier to pre-filter and tune results using the MongoDB query language, all in a single platform on Atlas. Finally, we recognize the need to empower developers with practical resources to expand their skills and knowledge. In addition to new content available on MongoDB University, we announced MongoDB Press, a medium for publishing technical and leadership knowledge about MongoDB. The first two books are on aggregations and mastering MongoDB 7.0. We also added a solutions library on our website with use cases organized by industry verticals to show the art of what’s possible with our developer data platform. To see more announcements and get the latest product updates, visit our What’s New page. Head to the MongoDB.local hub to see where we'll be showing up next.

【.NET Core】|总结/Edison Zhou大家好，我是Edison。最近，在使用CAP事件总线时，碰到了这样一个需求：微服务采用的是MongoDB，而且还是带身份验证 和 SSL证书验证的。由于目前网上能找到的资料，都是不带身份验证的MongoDB，那么就需要自己研究一番了。CAP.MongoDB组件CAP是一个开源的事件总线项目，在.NET社区已经十分流行了，它提供了多种存储方式：M...