Apache InLong - a one-stop data streaming platform

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  1. 6c2b869 [INLONG-1415][TubeMQ] Docker image expose zookeeper port for other component usages (#1416) by dockerzhang · 2 days ago master
  2. 85b5e61 [INLONG-1413][tubemq] init tubemq cluster for tubemq manager docker image (#1414) by dockerzhang · 2 days ago
  3. 36de54b [INLONG-1411] Adjust the project NOTICE content (#1412) by gosonzhang · 5 days ago
  4. ab407da [INLONG-1409]Sort out the LICENSE information of the 3rd-party components that the DataProxy submodule depends on (#1410) by gosonzhang · 6 days ago
  5. a978626 [INLONG-1407][DataProxy]Adjust the pom dependency of the DataProxy module (#1408) by gosonzhang · 6 days ago

Apache InLong

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What is Apache InLong?

Apache InLong(incubating) is a one-stop data streaming platform that provides automatic, secure, distributed, and efficient data publishing and subscription capabilities. This platform helps you easily build stream-based data applications.

InLong was originally built at Tencent, which has served online businesses for more than 8 years, to support massive data (data scale of more than 40 trillion pieces of data per day) reporting services in big data scenarios. The entire platform has integrated 5 modules: Ingestion, Convergence, Caching, Sorting, and Management, so that the business only needs to provide data sources, data service quality, data landing clusters and data landing formats, that is, the data can be continuously pushed from the source to the target cluster, which greatly meets the data reporting service requirements in the business big data scenario.

For getting more information, please visit our project documentation at https://inlong.apache.org/en-us/ .


Apache InLong offers a variety of features:

  • Ease of Use: a SaaS-based service platform, you can easily and quickly report, transfer, and distribute data by publishing and subscribing to data based on topics.
  • Stability & Reliability: derived from the actual online production environment, it delivers high-performance processing capabilities for 10 trillion-level data streams and highly reliable services for 100 billion-level data streams.
  • Comprehensive Features: supports various types of data access methods and can be integrated with different types of Message Queue (MQ) services, it also provides real-time data extract, transform, and load (ETL) and sorting capabilities based on rules, allows you to plug features to extend system capabilities.
  • Service Integration: provides unified system monitoring and alert services, it provides fine-grained metrics to facilitate data visualization, you can view the running status of queues and topic-based data statistics in a unified data metric platform, configure the alert service based on your business requirements so that users can be alerted when errors occur.
  • Scalability: adopts a pluggable architecture that allows you to plug modules into the system based on specific protocols, so you can replace components and add features based on your business requirements

When should I use InLong?

InLong is based on MQ and aims to provide a one-stop, practice-tested module pluggable data stream access service platform,based on this system, users can easily build stream-based data applications. It is suitable for environments that need to quickly build a data reporting platform, as well as an ultra-large-scale data reporting environment that InLong is very suitable for, and an environment that needs to automatically sort and land the reported data.

InLong is only a one-stop data reporting pipeline platform. It cannot be used as a persistent data storage, nor does it support complex business logic processing on data streams.

Build InLong

More detailed instructions can be found at Quick Start section in the documentation.


Compile and install:

$ mvn clean install -DskipTests

(Optional) Compile using docker image:

$ docker pull maven:3.6-openjdk-8
$ docker run -v `pwd`:/inlong  -w /inlong maven:3.6-openjdk-8 mvn clean install -DskipTests

after compile successfully, you could find distribution file at inlong-distribution/target.

Deploy InLong

InLong integrates a complete component chain for data reporting in big data scenarios, and does not support automatic installation of modules now, so we need to choose manually to install all or some modules according to actual needs. Please refer to Quick Start in our project documentation.

Contribute to InLong

Contact Us

  • Join Apache InLong mailing lists: | Name | Scope | | | | |:------------------------------------------------------------------------------|:--------------------------------|:----------------------------------------------------------------|:--------------------------------------------------------------------|:-----------------------------------------------------------------------------| | dev@inlong.apache.org | Development-related discussions | Subscribe | Unsubscribe | Archives |
  • Ask questions on Apache InLong Slack



© Contributors Licensed under an Apache-2.0 license.