Jad Jarouche

7 results

MongoDB, Microsoft Team Up to Enhance Copilot in VS Code

As modern applications grow increasingly complex, developers face the challenge of meeting market demands for faster, smarter solutions. To stay ahead, they need tools that streamline their workflows, available directly in the environments where they build. According to the 2024 Stack Overflow Developer Survey , Microsoft’s Visual Studio Code (VS Code) is the integrated development environment (IDE) of choice for 74% of professional developers, serving as a central hub for building, testing, and deploying applications. With the rise of AI-powered tools like GitHub Copilot—which is used by 44% of professional developers—there’s a growing demand for intelligent assistance in the development process without disrupting flow. At MongoDB, we believe that the future of development lies in democratizing the value of these experiences by incorporating domain-specific knowledge and capabilities directly into developer flows. That’s why we’re thrilled to announce the public preview of MongoDB’s extension to GitHub Copilot in VS Code. With this integration, developers can effortlessly generate MongoDB queries, inspect collection schemas, and get answers from the latest MongoDB docs—all without leaving their IDE. Our collaboration with MongoDB continues to bring powerful, integrated solutions to developers building the modern applications of the future. The new MongoDB extension for GitHub Copilot exemplifies a shared commitment to the developer experience, leveraging AI to ensure that workflows are optimized for developer productivity by keeping everything developers need within reach, without breaking their flow. Isidor Nikolic, Senior Product Manager for VS Code, Microsoft But we’re not stopping there. As AI continues to evolve, so will the ways developers interact with their tools. Stay tuned for more exciting developments next week at Microsoft Ignite , where we’ll unveil more ways we’re pushing the boundaries of what’s possible with AI through MongoDB and Microsoft’s partnership! What is MongoDB's Copilot extension? MongoDB’s Copilot extension supercharges your GitHub Copilot in VS Code with MongoDB domain knowledge. The Copilot integration is built into the MongoDB for VS Code extension , which has more than 1.8M downloads in the VS Code marketplace today. Type ‘@MongoDB’ in Copilot chat and take advantage of three transformative commands: Generate queries from natural language (/query) —this generates accurate MongoDB queries by passing collection schema as context to Github Copilot Query MongoDB documentation (/docs) —this answers any documentation questions using the latest MongoDB documentation through Retrieval-Augmented Generation (RAG) Browse collection schema (/schema) —this provides schema information for any collection and is useful for data modeling with the Copilot extension. Generate queries from natural language This command transforms natural language prompts into MongoDB queries, leveraging your collection schema to produce precise, valid queries. It eliminates the need to manually write complex query syntax, and allows developers to quickly extract data without taking their focus away from building applications. Whether you run the query directly from the Copilot chat or refine it in a MongoDB playground file, we’ve sped up the query-building process by deeply integrating these capabilities into the existing flow of MongoDB VS Code extension. Query MongoDB documentation The /docs command answers MongoDB documentation-specific questions, complemented by direct links to the official documentation site. There’s no need to switch back and forth between your browser and your IDE; the Copilot extension calls out to the MongoDB Documentation Chatbot API that leverages retrieval-augmented generation technology to generate responses that are informed by the most recent version of the MongoDB documentation. In the near future, these questions will be smartly routed to documentation for the specific server version of the cluster you are connected to in the MongoDB VS Code extension. Browse collection schema The /schema command offers quick access to collection schemas, making it easier for developers to access and interact with their data model in real-time. This can be helpful in situations where developers are debugging with Copilot or just want to know valid field names while developing their applications. Developers can additionally export collection schemas into JSON files or ask follow-up questions directly to brainstorm data modeling techniques with the MongoDB Copilot extension. On the Horizon This is just the start of our work on MongoDB’s Copilot extension. As we continue to improve the experience with new features—like translating and testing queries to and from popular programming languages, and in-line query generation in Playgrounds—we remain focused on democratizing AI-driven workflows, empowering developers to access the tools and knowledge they need to build smarter, faster, and more efficiently, right within their existing environments. Download MongoDB’s VS Code extension and enable the MongoDB chat experience to get started today.

November 13, 2024

Introducing AI-Powered Natural Language Mode in Atlas Charts

At MongoDB, our mission is to empower developers to seamlessly and efficiently build modern applications. To that end, we’ve announced a number of tools and improvements to help developers build faster , from AI-powered SQL query conversion in Relational Migrator to the MongoDB Provider for Entity Core Framework. In the same spirit, today at MongoDB.local Sydney we’re excited to announce the general availability of Natural Language Mode in Atlas Charts . Not only does this release help developers move faster with AI, it also showcases the work of MongoDB’s nimble Sydney engineering team. Intelligent developer experiences: The next level of productivity Over the past year, we’ve introduced a range of intelligent developer experiences across our platform, all of which aim to simplify and accelerate development processes. Overall, our goal is to make tools faster, better, and more connected for our developers, and to enable developers to leverage the power of AI to enhance their experience. As IBM highlights , true developer productivity involves delivering high-quality outputs that satisfy customers but also avoid developer burnout. By reducing learning curves, saving time, and providing easily accessible insights, intelligent features enable developers to focus on their most important work: building modern applications that solve real-world problems through outputs that are truly worth developers’ time and effort. Here’s what we’ve introduced: MongoDB Compass —Developers can use natural language to compose everything from simple queries to sophisticated, multi-stage aggregations. MongoDB Relational Migrator —With natural language, developers can convert SQL queries to MongoDB Query API syntax, streamlining migration projects. MongoDB Documentation —An intelligent chatbot, built on top of MongoDB Atlas and Atlas Vector Search, enables lightning-fast information discovery and troubleshooting during software development. By integrating AI into our most important developer tools, we’re helping developers cut through the noise and focus on creating innovative solutions. Simplifying data visualization with Natural language Mode Visualizing data can be an incredibly effective way of gleaning insights from application data, but creating effective visualizations can require specialized knowledge and experience with business intelligence (BI) tools. Atlas Charts was built to level the playing field. Now, with Natural Language Mode, developers can create visualizations simply by asking questions in plain English. Natural Language Mode reduces technical barriers and makes data visualization accessible to anyone with data in MongoDB Atlas. This means faster chart creation at an advanced scale—all within the Atlas ecosystem. Since announcing its development in the fall of 2023, we’ve made significant enhancements to Natural Language Mode, including an expanded suite of chart types built for all kinds of data from patient records to financial trading flows. We’ve also improved performance to ensure faster and more accurate chart generation, including the ability to handle more sophisticated prompts, filtering, sorting, binning, and limiting. In the next few weeks, we will add more chart variation, as well as another upgrade to our model that will increase accuracy and responsiveness by up to 50%. Natural Language Mode in action Now let’s walk through a few examples of what using Natural Language Mode in an Atlas Charts looks like: Generating a chart using Natural Language Mode With a simple query like "Show me the sales performance by country and product for Q4 FY2023," developers can instantly generate a relevant chart. Customizing charts in Classic Mode After generating a chart, developers can pull it into Classic Mode to fine-tune and customize it to fit their dashboard needs. Scheduling Dashboards Developers can also schedule their dashboards to be shared via email, ensuring that key stakeholders receive up-to-date insights automatically. More data, more insights Customers are already excited about the possibilities of Atlas Charts and Natural Language Mode, from operational analytics to embedded analytics. For example, one of MongoDB’s early customers has been using Natural Language Mode to track server performance across various regions. Business analysts leverage the feature to gain insights into server performance and share these insights internally. They plan to embed these visualizations into their customer portal using the embedding SDK offered by Atlas Charts . Another customer said: "As a developer with no prior experience in analytics, I was excited to see Natural Language Mode generate a clear value proposition that showcased what the product is capable of. It makes me want to throw more data in the database to get more insights." So check out Natural Language Mode in Atlas Charts today, and experience firsthand how AI can simplify and accelerate your data visualization workflows. Try out Natural Language Mode in Atlas Charts to transform your data visualization process. New to Charts? Register for MongoDB Atlas , deploy a cluster, and activate Charts for free.

July 29, 2024

What’s New From MongoDB at Microsoft Build 2024

This week, thousands of engineers, database administrators, and developers are gathering in Seattle for Microsoft Build , Microsoft’s annual developer event. In addition to being on site for meetings and learning sessions, MongoDB is excited to showcase our latest innovations for building generative AI apps and more. First, we’re happy to announce that MongoDB now offers dedicated Search Nodes on Microsoft Azure . We offer both compute-optimized nodes for text or application search workloads, and memory-optimized nodes for vector, semantic search, or gen AI workloads. Search Nodes enhance performance and availability through workload isolation while reducing architectural complexity. The availability of Search Nodes on Azure is the latest example of how the partnership between MongoDB and Microsoft helps organizations of all sizes boost developer productivity and build modern applications faster. Keep reading for more on how MongoDB’s capabilities and integrations with Microsoft are helping customers create, innovate, and scale applications. Integrating services and technology to speed AI development The last year of AI innovation set a clear imperative for every organization—to meet customer expectations, they need to modernize their applications. However, many companies aren’t sure where to start with AI, so MongoDB recently announced the launch of the MongoDB AI Application Program (MAAP) alongside industry-leading AI partners. MAAP will provide customers with strategic advisory, professional services, and an integrated end-to-end technology stack from MongoDB and key partners like Microsoft. We’ve also made several technology announcements to enable building gen AI applications, including native support for MongoDB Atlas Vector Search in Microsoft Semantic Kernel , and a dedicated MongoDB Atlas integration for OpenAI’s ChatGPT Plugin . With the new integration, developers can seamlessly and securely enhance the power of large language models from OpenAI, Azure OpenAI, and Hugging Face with proprietary data in Atlas to build powerful retrieval-augmented generation applications using Python or C#. Developing faster with intelligent tools and frameworks In addition to helping developers build powerful gen AI applications through services like Atlas Vector Search, we’ve been working to enhance developer productivity, making it easier than ever to build applications with MongoDB. For example, we’ve introduced intelligent features to first-party tools like MongoDB Compass and Atlas Charts that support natural language. We also recently announced AI-powered SQL query conversions in Relational Migrator to help teams easily move their workloads to MongoDB. MongoDB is expanding the use of AI to enhance its integration with the world’s most popular integrated development environment, Visual Studio Code. We’re excited to announce the MongoDB Participant for the Github CoPilot chat experience, designed to empower developers to generate queries from natural language, understand collection schemas, and instantly access MongoDB documentation. Sign up for the private preview here . MongoDB also supports a variety of programming frameworks to improve productivity and accelerate application development—while ensuring data consistency and quality. Now generally available, the MongoDB Provider for Entity Framework Core (EF Core), encourages C# developers to build their next project on MongoDB. This new offering helps C# developers—39% of whom use EF Core—unlock the full power of MongoDB using the EF Core APIs and design patterns they already know and love. Streamlining comprehensive data analysis For years, MongoDB and Microsoft have facilitated the large-scale analysis of application-generated data to aid business development. Tools like Microsoft Power BI provide a comprehensive view of business intelligence data for developers and analysts with complex data estates using relational databases alongside MongoDB. MongoDB’s Power BI Connector for Atlas —previously supporting Import Mode—now also supports DirectQuery, which we announced a few weeks ago at MongoDB.local NYC . This allows for real-time querying of MongoDB data and is ideal for large datasets. To further enable customers working in the Microsoft ecosystem, we’ve recently made Atlas Data Federation and Atlas Online Archive generally available on Azure . These services enable users to query, transform, and create views across multiple Atlas databases and Azure cloud storage solutions, like Blob Storage and Data Lake Storage Gen2, simplifying data management and archiving within the Azure ecosystem. Building the future together MongoDB's partnership with Microsoft has made developing modern applications faster and easier. We're thrilled to announce these new capabilities at Microsoft Build 2024 , and look forward to helping our joint customers build amazing things together this year. “MongoDB’s relationship with Microsoft has never been better, and with these latest integrations, our momentum continues to grow,” said Alan Chhabra, MongoDB’s EVP of Worldwide Partners. “Already, many of the largest enterprises and most advanced startups in the world run MongoDB Atlas on Microsoft Azure. These latest innovations will empower even more of our customers to take full advantage of their data to build truly transformational generative AI-powered applications.” MongoDB’s partnership with Microsoft sets projects up for success today and tomorrow by delivering robust, integrated solutions that cater to developers' needs. MongoDB and Microsoft are pushing the boundaries for innovation and service for the developer community. To learn more about our recent announcements and for the latest product updates, visit our What’s New page. And head to our campaign page to learn more about how to build smarter and develop faster with MongoDB Atlas on Microsoft Azure.

May 21, 2024

Announcing DirectQuery Support for the MongoDB Atlas Connector for Power BI

Last year, we introduced the MongoDB Atlas Power BI Connector , a certified solution that has transformed how businesses gain real-time insights from their MongoDB Atlas data using their familiar Microsoft Power BI interface. Today, we’re excited to announce a significant enhancement to this integration: the introduction of DirectQuery support. DirectQuery mode provides a direct connection to your MongoDB Atlas database, allowing Power BI to query data in real-time. This means that your Power BI visualizations and reports will always reflect the latest data without importing and storing data within Power BI. This is especially beneficial for analyzing large datasets where up-to-date information is crucial, ensuring decisions are made efficiently without losing performance due to repetitive data imports and storage complexities. How DirectQuery in MongoDB Atlas Power BI Connector works: The Power BI Connector is supported through MongoDB’s Atlas SQL Interface , which is easily enabled from the Atlas console. Atlas SQL, powered by Atlas Data Federation , allows you to integrate data across sources and apply transformations directly, enhancing your analytics. Once enabled, you’ll receive a SQL Endpoint or URL to input into your MongoDB Atlas SQL Connection Dialog within Power BI Desktop. Here, you can choose between two connectivity modes: Import or DirectQuery. Once connected through DirectQuery, Query folding takes place with Power Query , which is how data retrieval and transformation of source data is optimized. You can also achieve data transformation using a SQL Statement, either with the SQL Statement option in the Atlas SQL Interface or within the M Code script accessed via the Power Query Advanced Editor. After your data is transformed and ready for analysis, start building reports with your Atlas data within the Power BI Desktop! Then, simply save, publish, and distribute within the Power BI online app, which is now part of the Microsoft Fabric platform. Watch our comprehensive tutorial below covering how to connect your Atlas data to Power BI , control SQL schemas in Atlas, and use DirectQuery to gain real-time access to your data for business insights. Power BI Connector for MongoDB Atlas is a Microsoft-certified solution. It not only supports the advanced capabilities of DirectQuery but also continues to offer Import Mode for scenarios where data volume is manageable and detailed data modeling is preferred. Whether you’re analyzing real-time data streams or creating comprehensive reports, the Atlas Power BI Connector adapts to your needs, ensuring your business leverages the full power of MongoDB Atlas. DirectQuery Support is available now and can be accessed by updating your existing MongoDB Atlas Power BI Connector or downloading it here . Start transforming your data analysis and making more informed decisions with real-time Atlas data. Log in and activate the Atlas SQL Interface to try out the Atlas Power BI Connector ! If you are new to Atlas or Power BI, get started for free today on Azure Marketplace or Power BI Desktop .

May 13, 2024

What's New in Atlas Charts: Summer 2023 Release Roundup

Today, we’re excited to announce a series of updates to Atlas Charts . The Charts team is constantly adding enhancements to make visualizing data from MongoDB Atlas collections quick, easy, and powerful. With this summer’s release, we are introducing: Expanded chart customization options in the Charts Embedding SDK An out-of-the-box billing dashboard for easily monitoring your Atlas billing data Support for a new chart type with candlestick charts, and Query execution improvements for more reliable visualization of even your largest datasets. Let’s go through these updates one by one. Expanded charts customization options in the Charts embedding SDK Embedded charts and dashboards can be a useful way to share information across an organization and even with your customers. Over the last year, we have made many improvements to getting started with and implementing embedded charts and dashboards. With this release, we focused on the look and feel of your embedded charts. The Charts Embedding SDK now allows for greater customization across attributes like chart titles, descriptions, axes options, channel options, chart color palette, and conditional formatting options. Providing access to these chart specifications matches many of the customization options that developers rely on when building charts inside Atlas. An out-of-the-box Atlas billing dashboard Next, let’s talk about discovering insights from your Atlas billing data. Over the past two years, MongoDB has made visualizing billing data in Atlas Charts possible . Implementing this dashboard required quite a bit of effort in the past, but we heard from many teams that this dashboard is essential to the monitoring of their Atlas bill. So, we worked to build a more streamlined process for enabling these insights. Enter the new billing dashboard. The new billing dashboard in Atlas Charts is as simple as a button click on our new Ingestions page. Simply click Add and open and you’ll see a billing dashboard ready for exploration. The new billing dashboard allows for customization, adding dashboard filters, and getting new views into your data with the ability to add other charts based on your interests. Support for a new chart type: Candlestick charts The third update in this release is support for candlestick charts. While many developers leverage the wide variety of chart types available in Charts, we are always paying attention to additional chart types that can enable even more use cases for visualizing your Atlas data. This is why we have added candlestick charts with this latest release. Candlestick charts are commonly used for financial data, richly representing financial trading trends and price fluctuations. Query execution improvements for more reliable visualization of even your largest datasets Finally, let’s talk about query execution in Charts. One of the key characteristics of Charts is that it works natively with your Atlas data, requiring no data movement or duplication. Developers can simply select a data source to explore and immediately discover insights about application data. However, that doesn’t mean things are simple on the backend when creating a chart. Charts does a lot of work to efficiently render your visualizations as seamlessly as possible. And depending on your cluster configuration and the complexity of the chart you are creating (and the query driving it), Charts can take some time to render and produce the information you are aiming to visualize. Historically, Charts had a timeout duration of 120 seconds. Queries taking longer than this, would fail and not render the desired visualization. With this update, Charts users will see: Improved rendering of more complex queries as we have extended the timeout duration to 10 minutes, and More helpful in-product notification that lets you know when a query may take additional time to run, so you can continue either creating other visualizations or doing other work, until your query finishes. If you have queries requiring a longer timeout duration than 10 minutes, you can contact the Charts team through support. Note: Query Execution will initially be available through contacting Customer Support, or your existing Customer Success team, to opt-in. The feature will become Generally Available to all accounts in October, 2023. With that, we hope these enhancements make Charts even easier and more powerful to use. Over the coming weeks, we’ll go a level deeper, diving into some of these features with more detail. In the meantime, go build some visualizations in Charts to get hands-on and see for yourself! New to Atlas Charts? Get started today by logging into or signing up for MongoDB Atlas , deploying or selecting a cluster, and activating Charts for free.

August 21, 2023

Real-Time Insights Through the Atlas SQL Interface, Now Generally Available with Custom Connectors for Tableau and Power BI

>> Announcement: Some features mentioned below will be deprecated on Sep. 30, 2025. Learn more . We are excited to announce the General Availability of the Atlas SQL Interface , a solution built to help analysts gain insights on live application data in real time! Built with a SQL-92 compatible dialect, mongosql, the Atlas SQL Interface, Connectors, and Drivers make it easy to natively query and visualize Atlas data with SQL-based tools while preserving the flexibility of the document model. Through two custom-built connectors – a Microsoft-certified Power BI Connector and a Tableau Connector built in partnership with Tableau – in addition to new versions of our Atlas JDBC and ODBC Drivers for other SQL-based tools, eliminate the need for complex ETL and data duplication. Use custom SQL and native BI tool functionality right in your tool’s interface to transform, analyze, and report on live application data! How it works With the Atlas SQL Interface enabled, download the appropriate JDBC/ODBC Driver and/or Custom Power BI/Tableau Connector to query and transform your document data in your SQL-based tool. The Atlas SQL Interface also leverages Atlas Data Federation as its query engine, so you can query across multiple Atlas databases and other sources, such as cloud storage buckets and HTTPs endpoints, with efficiency. Certified Atlas Power BI Connector The Power BI Connector for Atlas is an integration built by MongoDB and certified by our partners at Microsoft. This Connector makes it easy to model document data with native Power BI features and data modeling capabilities available in Power Query. Build up-to-date dashboards in Power BI Desktop and scale insights to your organization through Power BI Service with no duplication or delays. Check out the demo below to see it in action: Atlas Tableau Connector Built with the Tableau analyst in mind, this specialized Connector ensures a first-class querying experience of live Atlas data from within Tableau without the need to learn MQL, implement unnecessary data pipelines, or perform complex ETL. Directly interact with MongoDB’s JSON-like document data to quickly visualize, graph, and report on live data using native Tableau Features. Check out the demo below to see it in action: This is a fantastic product offering from the MongoDB team, something that the community has needed for years! I really see this feature as bridging the gap, especially for data science and BI people who talk primarily in SQL Software Solutions Architect, Ampcontrol The Atlas SQL Interface, Connectors, and Drivers enable businesses to fully harness the power of their Atlas data, ensuring that our platform not only serves the developers who build applications to help run your business, but that it also serves the teams finding data-driven insights to help scale the business. Log in today to activate the Atlas SQL Interface and get started. Go to our download center to retrieve your Connector and Driver files, or check out our docs for more information on how to put the Atlas SQL Interface, Connectors, and Drivers to use!

June 26, 2023

Introducing the Certified MongoDB Atlas Connector for Power BI

This is a collaborative post from MongoDB and Microsoft. We thank Alexi Antonino, Natacha Bagnard, Jad Jarouche from MongoDB, and Bob Zhang, Mahesh Prakriya, and Rajeev Jain from Microsoft for their contributions. Introducing MongoDB Atlas Connector for Power BI, the certified solution that facilitates real-time insights on your Atlas data directly in the Power BI interfaces that analysts know and love! Supporting Microsoft’s Intelligent Data Platform , this integration bridges the gap between Developers and Analytics teams, allowing analysts who rely on Power BI for insights to natively transform, analyze, and share dashboards that incorporate live MongoDB Atlas data. Available in June , the Atlas Power BI Connector empowers companies to harness the full power of their data like never before. Let’s take a deeper look into how the Atlas Power BI Connector can unlock comprehensive, real-time insights on live application data that will help take your business to the next level. Effortlessly model document data with Power Query The Atlas Power BI Connector makes it easy to model document data with native Power BI features and data modeling capabilities. With its SQL-92 compatible dialect, mongosql, you can tailor your data to fit any requirements by transforming heavily nested document data to fit your exact needs, all from your Power Query dashboard. Gain real-time insights on live application data By using the Power BI Connector to connect directly to MongoDB Atlas, you can build up-to-date dashboards in Power BI Desktop and scale insights to your organization through Power BI Service with ease. With no delays caused by data duplication, you can stay ahead of the curve by unlocking real-time insights on Atlas data that are relevant to your business. Empower cross-source data analysis The Power BI Connector's integration with MongoDB Atlas enables you to seamlessly model, analyze, and share insightful dashboards that are built from multiple data sources. By combining Atlas's powerful Data Federation capabilities with Power BI's advanced analytics and visualization tools, you can easily create comprehensive dashboards that offer valuable insights into your data, regardless of where it is stored. See it in action Log in and activate the Atlas SQL Interface to try out the Atlas Power BI Connector ! If you are new to Atlas or Power BI, get started for free today on Azure Marketplace or Power BI Desktop .

May 23, 2023