Born to change

AntDB’s new-generation streaming processing engine

If the hyper-convergence framework is the basic architecture of database and does not solve a specific type of scenario problem, then AntDB-S streaming data engine of AntDB V7.2 completely overturns the design and development model of real-time computing applications.

The problems of difficult development and high cost of streaming business affect the rapid promotion and implementation of streaming computing in actual production. For developers, whether it is Apache Storm, Spark Streaming, or Flink and other mainstream streaming processing framework design, all focus on the "processing" itself. Since they do not have database capabilities, they require complex data extraction when they need to interact with other data for correlation and temporary storage,and manual processing operations is required inside the streaming processing engine via Java/Scala program code.

After more than ten years of practical experience in core business scenarios of carriers, AntDB found that some business scenarios cannot be realized by traditional technology and need real-time processing capabilities to support such as streaming computing.

Therefore, AntDB has done a lot of innovative explorations and researches from scratch to integrate streaming computing into the database kernel. Users can freely define the structure of data and real-time processing logic through standard SQL under the framework of one database engine; meanwhile, data can flow freely between stream objects and table objects inside the database; users can conduct performance optimization, data processing, cluster monitoring and business logic customization of data by establishing indexes, stream-table association, triggers, materialized views, etc. at any time.

 Figure: Hyperconvergence + Streaming

Under AntDB's all-in-one streaming engine mechanism, developers can get rid of the complexity of real-time business development and do not need to use Java/Scala code to define data processing logic; and for operation and maintenance personnel, they can achieve the goal of "one product to meet multiple data processing types", which greatly reduces the complexity of the overall technical framework, and the security stability and development efficiency of the system are improved.