Unified data platform for developers | TechBuzz

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MongoDB wants to expand its data platform for developers. Plans include addressing a broader range of use cases, covering more of the data lifecycle, optimizing for modern architectures, and better data encryption.

Dev Ittycheria, President & CEO of MongoDB: “Our vision is to offer a data platform for developers that offers a modern and elegant developer experience, supports a wide variety of use cases, and offers the performance and scale to meet the most demanding requirements.”

MongoDB has announced a number of features designed to make it easier for developers to create in-app analytics and enable richer application experiences. Column store indexing, available later this year, aims to enable users to create and maintain a custom index that accelerates many common analytical queries without requiring changes to document structure or moving data to another system . Additionally, analytics nodes will now be able to scale separately, allowing teams to independently balance the performance of their operational and analytical queries without over- or under-provisioning. Here are some highlights:

MongoDB time-series collections are designed to make it easier to build applications that monitor physical systems, track assets, or deal with financial data, faster and more cost-effectively. In the upcoming version 6.0 of MongoDB, time series collections are expected to support secondary indexes for measurements and provide read performance improvements and optimizations for faster sorting of time-based data.

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Atlas Search is recognized as the fastest and easiest way to integrate relevancy-based search capabilities into applications. With Search Facets, developers can now create search experiences that allow end users to seamlessly search, narrow, or refine their results by different categories.

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Atlas’ SQL interface provides data analysts who primarily work with SQL tools a way to interact with Atlas data in a read-only interface. This is intended to make it easier to natively query and visualize Atlas data using SQL-based tools while maintaining the flexibility of the document model. It can also be used to query data in Atlas clusters and cloud object stores using SQL without the need for data manipulation, schema definition, or data flattening.

The Data API allows access to Atlas data over HTTPS with no operational overhead. This gives developers the ability to easily integrate Atlas data into other apps and services in the cloud or into their serverless architectures.

For the full list of new features and improvements, visit: https://www.mongodb.com/new.
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