MongoDB Relational Migrator now converts SQL to MongoDB Query API syntax using AI to further automate migrations from relational databases
MongoDB, Inc.at MongoDB.local London announced new intelligent developer experiences that use generative AI to help developers more quickly and easily build applications on MongoDB—the world’s most popular document-based data platform that millions of developers and tens of thousands of customers rely on for their business-critical applications. The new generative AI features in MongoDB Relational Migrator, MongoDB Compass, MongoDB Atlas Charts, and MongoDB Documentation reduce the time and effort developers spend on undifferentiated tasks and allow them to instead focus on hard-to-solve problems and building modern 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 Sahir Azam, Chief Product Officer at MongoDB. “By integrating AI-powered features into MongoDB products and services that millions of developers use everyday, we’re empowering developers to reduce time spent on lower-value tasks so they can focus on the things that matter the most to them and their organizations—building and shipping modern applications that end users love.”
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 MongoDB because of its flexibility, scalability, and resilience. However, developers often spend a lot of time and effort creating queries and aggregations that help data-driven applications run effectively, generating visualizations from operational data to uncover insights and inform decision making, and troubleshooting unexpected database and application behavior. While important, these often undifferentiated tasks require significant developer resources that could be better spent on prototyping, shipping new features, and creating innovative end-user experiences.
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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.
- 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.
- 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.
- 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 about MongoDB’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.
SOURCE: PRNewswire
