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Apache
Automatic
Safety
High performance
Distributed

Apache InLong is a one-stop integration framework for massive data that provides automatic, secure and reliable data transmission capabilities. InLong supports both batch and stream data processing at the same time, which offers great power to build data analysis, modeling and other real-time applications based on streaming data.

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PRODUCT
ADVANTAGES
  • Ease of Use

    Apache InLong is 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

    Apache InLong is 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

    Apache InLong 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. Apache InLong also allows you to plug features to extend system capabilities

  • Service Integration

    Apache InLong 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. You can also configure the alert service based on your business requirements so that users can be alerted when errors occur

  • Scalability

    Apache InLong adopts a pluggable architecture that allows you to plug modules into the system based on specific protocols. You can replace components and add features based on your business requirements

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PRODUCT
STRUCTURE

Any questions

Features request, ask questions or report bugs? Feel free to GitHub Discussion or submit an issue.

Join our slack workspace

Send ‘Request to join Apache InLong’ mail to the mail list dev@inlong.apache.org , we will invite you in.

Contributions welcome

Everyone is welcome to create Pull Request and contribute their own code at any time!

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Follow the latest developments of the project on @ApacheInlong .