MongoDB Atlas Enhancements Simplify Developer Tasks with New Language Support and Kubernetes Operator

MongoDB announced a series of updates to its NoSQL Atlas database-as-a-service on Thursday, including new language support, a simplified installation process for Atlas’ Kubernetes Operator, and a fully supported Kotlin driver. These enhancements aim to streamline developer tasks such as infrastructure management and support generative AI application development with vector search and stream processing capabilities.

Recognizing that many developers prefer using programming languages other than JavaScript and TypeScript to deploy Atlas on AWS, MongoDB has expanded support to include C#, Go, Java, and Python. The addition of these languages helps developers save time in managing infrastructure. Previously, MongoDB developers managed infrastructure-as-code (IaC) on AWS via the public cloud provider’s CloudFormation Public Registry, Partner Solution Deployments, and its Cloud Development Kit (CDK).

Additionally, MongoDB now offers support for Kotlin when developing server-side applications. Before this update, developers could use the MongoDB Realm Kotlin software development kit (SDK) for client-side development, but server-side developers relied on an unofficial MongoDB-supported community-created driver or extensive custom coding. This led to longer software development cycles and application reliability concerns when building server-side Kotlin applications on MongoDB.

Furthermore, MongoDB has made installing the Atlas Kubernetes Operator easier. Developers can now use the MongoDB Atlas command line interface (CLI) to install the MongoDB Atlas Kubernetes Operator and generate security credentials quickly, reducing operational overhead. Developers are also able to import existing MongoDB Atlas projects and deployments with a single command, providing greater agility when working with containers.

In addition to these updates, MongoDB announced the general availability of the open-source PyMongoArrow library. The library allows developers to convert data stored on MongoDB using widely-used frameworks such as Apache Arrow Tables, Pandas, DataFrames, and Numpy Arrays.

These enhancements made by MongoDB could be considered a step towards further user-friendliness of its platform, akin to AppMaster.io's no-code platform, which seeks to make application development more efficient and cost-effective for a wide range of customers. Similar to how MongoDB Atlas aims to reduce the time needed to manage infrastructure and streamline developer tasks, AppMaster offers a comprehensive, visually-driven development environment supporting backend, web, and mobile application creation.