MongoDB Announces Four New AI-Powered Capabilities to Improve Developer Productivity and Accelerate Application Modernization
MongoDB Relational Migrator now converts SQL to MongoDB Query API syntax using AI to further automate migrations from relational databases
MongoDB Compass now generates queries and aggregations from natural language to build data-driven applications more quickly and easily
MongoDB Atlas Charts now creates rich data visualizations from natural language to speed up dashboard creation and business intelligence
New AI chatbot feature in MongoDB Documentation provides answers to technical questions to reduce the time it takes to build and troubleshoot applications
"Generative AI is creating new opportunities for developers to build better applications. By automating repetitive tasks, AI-powered tools and features can help developers save significant time and effort and deliver higher-quality applications faster," said
Organizations today face growing demands from customers to build highly engaging applications that can react in real time to shifting demands and ever-changing data. Developers building these applications choose
The new set of generative AI capabilities now offered in MongoDB Relational Migrator, MongoDB Compass, MongoDB Atlas Charts, and MongoDB Documentation help remove much of the heavy lifting of application development and modernization:
- Further accelerate application modernization with MongoDB Relational Migrator: MongoDB Relational Migrator makes it significantly faster and easier to migrate from legacy database technologies to MongoDB Atlas using intelligent data schema and code recommendations. One common challenge of migrating legacy applications is working with SQL queries and stored procedures that are often undocumented and must be manually converted to MongoDB Query API syntax. Now, organizations can accelerate their migration efforts using new AI-powered capabilities in MongoDB Relational Migrator that automatically convert SQL queries and stored procedures in legacy applications to development-ready MongoDB Query API syntax. Using MongoDB Relational Migrator, customers can now accelerate application modernization projects, and developers can speed up migrations by automating tedious conversion tasks with no MongoDB Query Syntax API knowledge required. To learn more about MongoDB Relational Migrator, visit mongodb.com/products/relational-migrator.
- Generate queries and aggregations more quickly in MongoDB Compass: MongoDB Compass is one of the most popular tools developers use to interact with data because of its easy-to-use capabilities for data querying and aggregation in
MongoDB . Now, developers can use natural language to quickly generate executable MongoDB Query API syntax within MongoDB Compass and incorporate sophisticated, data-intensive features into applications with less time and effort. For example, a developer can input 'Filter pizza orders by size, group the remaining documents by pizza name, and calculate the total quantity' and MongoDB Compass will suggest code to execute the stages of the required aggregation pipeline needed to process the data. With new natural language capabilities for MongoDB Compass, developers can focus more time and effort on shipping data-driven applications instead of manually writing complex queries and aggregations. To learn more about MongoDB Compass, visit mongodb.com/products/tools/compass.
- Visualize data in MongoDB Atlas Charts using natural language: MongoDB Atlas Charts is a modern data visualization tool that allows developers to easily create, share, and embed visualizations using data stored in MongoDB Atlas. With new AI-powered capabilities, developers can build data visualizations, create graphics, and generate dashboards within MongoDB Atlas Charts using natural language. For example, developers can input 'Show me a comparison of annual revenue by country and product' and MongoDB Atlas Charts will gather data and quickly generate the requested visualization. Developers can then use the familiar drag and drop interface in MongoDB Atlas Charts for further refinement and customization. To learn more about MongoDB Atlas Charts, visit mongodb.com/products/charts.
- Get answers from MongoDB Documentation more quickly and intuitively: MongoDB Documentation provides developers with tutorials, code samples, and reference libraries needed to build applications with
MongoDB . With the addition of an AI-powered chatbot within MongoDB Documentation, developers can now ask questions and receive answers aboutMongoDB's products and services, in addition to troubleshooting during software development—all within a few seconds. For example, developers can ask 'How do I index data with Atlas Vector Search' and the chatbot will provide step-by-step instructions, example code, and links to references to learn more and get started quickly. The MongoDB Documentation chatbot is an open source project that uses MongoDB Atlas Vector Search for AI-powered information retrieval of curated data to answer questions with context, and developers can use the project code to build and deploy their own chatbots for a variety of use cases. To get started with the MongoDB Documentation chatbot, visit mongodb.com/docs.
The new AI-powered features in MongoBD Relational Migrator, MongoDB Compass, and MongoDB Atlas Charts are available in preview. The MongoDB Documentation chatbot is generally available today.
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