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make stream processing easier!!!

An amazing framework makes stream processing easier.

🚀 What is StreamX

StreamX is an easy-to-use stream processing application development framework and one-stop stream processing operation platform, Aimed at ease building and managing streaming applications, StreamX provides scaffolding for writing streaming process logics with Apache Flink and Apache Spark. StreamX also provides a professional task management including task development, scheduling, interactive query, deployment, operation, maintenance, etc.

Why StreamX

Apache Flink and Apache Spark are widely used as the next generation of big data streaming computing engines. Based on a bench of excellent experiences combined with best practices, we extracted the task deployment and runtime parameters into the configuration files. In this way, an easy-to-use RuntimeContext with out-of-the-box connectors would bring easier and more efficient task development experience. It reduces the learning cost and development barriers, hence developers can focus on the business logic. On the other hand, It can be challenge for enterprises to use Flink & Spark if there is no professional management platform for Flink & Spark tasks during the deployment phase. StreamX provides such a professional task management platform, including task development, scheduling, interactive query, deployment, operation, maintenance, etc.

🎉 Features

  • Apache Flink & Spark application development scaffolding
  • Supports multiple versions of Flink & Spark
  • A range of out-of-the-box connectors
  • one-stop stream processing operation platform
  • Support catalog、olap、streaming-warehouse etc.
  • ...

🏳‍🌈 Architecture of StreamX

The overall architecture of StreamX is shown in the following figure. Streamx consists of three parts, they are streamx-core, streamx-pump, and streamx-console.

Streamx Archite

1️⃣ streamx-core

The positioning of streamx-core is a framework uesd while developing, it focuses on coding development, regulates configuration files, and develops in the convention over configuration guide. streamx-core provides a development-time RunTime Content and a series of out-of-the-box Connectors. Cumbersome operations are simplified by extending DataStream-related methods and integrating DataStream and Flink sql api . development efficiency and development experience will be highly improved because users can focus on the business.

2️⃣ streamx-pump

streamx-pump is a component similar to flinkx which is used for data extraction. It is developed based on various connectors provided in streamx-core and will be integrated into streamx-console. The purpose of developing streamx-pump is to create a convenient, fast, out-of-the-box extraction and migration component for real-time big data. We expect it could solve the real-time data source fetching problem. streamx-pump is still in planning.

3️⃣ streamx-console

streamx-console is a comprehensive real-time low code data platform that can manage Flink tasks more convenient. It integrates the experience of many best practices and integrates many functions such as project compilation, release, parameter configuration, startup, savepoint, flame graph, Flink SQL, monitoring, etc., which greatly simplifies the daily operation of Flink tasks and maintenance. The ultimate goal is to create a one-stop big data platform, which can provide a solution that integrates flow and batch, and integrates lake and warehouse. This platform uses technologies including but not limited to:

Thanks for the respect given by the above excellent open source projects and many unmentioned excellent open source projects

👻 Why not ...❓

Apache Zeppelin

Apache Zeppelin is an excellent open source project that supports Flink well. Zeppelin's innovative notebook function allows developers to easily program on-line and submit tasks quickly. At the language level, Zeppelin supports java, scala, and python at the same time.Whether it is a DataStream task or a Flink SQL task, most tasks will go through the development stage, the testing stage, the packaging stage, the uploading server stage, and the starting task stage, this is a process with a long link, the whole process takes a long time, and the user experience is very unfriendly: even if a symbol is modified, the task has to go through the above process from the completion of the modification to the launch. We expect these steps could be completed by One-click solution—moving the mouse and have at least one task list, which can manage tasks conveniently、could clearly see which tasks are running, which tasks are stopped、the resource consumption of each task、one-click start or stop tasks and manage savePoint automatically.

These problems are also problems that developers will encounter in actual development. streamx-console can solve these pain points very well. It is positioned as a one-stop real-time data platform and has more exciting functions (such as Flink SQL WebIDE, dependency isolation, task rollback, flame graph, etc.)


FlinkX is a distributed data synchronization tool based on Flink, which realizes efficient data migration between various heterogeneous data sources, and its positioning is relatively clear - it is specially used for data extraction and migration. It could be used as a service component. StreamX focuses on the management of the development stage and the post-task stage, the positioning is different. The streamx-pump module is also being planned. It is wished to solve data source extraction and migration problem, and will eventually be integrated into the streamx-console.