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DolphinDB: Unleash the power of big data analytics with our high-performance, real-time platform. Gain valuable insights and stay ahead of the competition. Deploy on your own infrastructure. Try now!

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What is DolphinDB?

DolphinDB is a powerful analytics platform designed to handle big data. It is distributed, high-performance, and real-time, making it an excellent choice for organizations seeking to manage, analyze, and visualize large datasets. By utilizing an in-memory columnar database, DolphinDB enables users to process and analyze massive amounts of data quickly and efficiently. Its distributed architecture ensures scalability and reliability, while its cloud-native technology allows users to deploy the platform on their own infrastructure. DolphinDB offers a range of features including advanced data compression, a fast query engine, native support for machine learning algorithms, and more. With DolphinDB, users can effortlessly access, store, and process large amounts of data in real-time, enabling them to gain valuable insights and gain a competitive advantage through big data analytics.


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DolphinDB Use Cases

Real-time Platform for Analytics and Stream Processing, Powered by High-performance Time Series Database

Faster than traditional databases by 100x or more; Millisecond response time for queries on petabytes of data.

As one of the few ACID-compliant time series databases, DolphinDB ensures strong data consistency.

Native support for horizontal scaling, load-balancing, and fault tolerance.

High-availability solutions for data nodes, controller, streaming, and API clients to ensure uninterrupted services.

Faster than traditional solutions by 10-100x or more with streamlined in-database analytics and optimized built-in functions.

Offer 1500+ built-in functions to handle complex analytical tasks.

Enable rapid development with various programming paradigms: imperative, vectorized, functional, SQL, and more.

Compatible with ANSI SQL. Offer new SQL clauses for generation of pivot tables, calculation within groups, and more.

Both batch and stream processing can use the same metric expression, significantly reducing the development costs.

Over 10 out-of-the-box streaming engines for real-time processing, which can also be pipelined for computing tasks with complex logic.

Blazingly fast in stream processing with incremental computing, parallel computing, and JIT compilation.

Advanced high availability based on the Raft consensus protocol to ensure uninterrupted streaming services.

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