apache/inlong

Health v2 · maintenance only

Adoption not part of the score

1497 stars · 570 forks observed · 2026-08-28

What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-30, confidence not recorded

Apache InLong is a one-stop, full-scenario integration framework for massive data, supporting data ingestion, synchronization, and subscription with reliable high-performance transmission. Originally TubeMQ and donated by Tencent, it graduated as an Apache top-level project and handles trillion-scale data streams for batch and stream processing.

Use cases

• ingest massive event streams from files, HTTP, SDKs, and databases
• synchronize data between sources and sinks in real time
• subscribe to data streams via topics
• run ETL and sorting on streaming data
• integrate with different message queue backends
• build real-time analytics and modeling pipelines
• monitor and alert on data flow health

When to choose

• you need a unified platform for high-volume data ingestion, sync, and subscription
• you process trillion-scale event streams and need proven production reliability
• you want pluggable MQ integration and rule-based ETL in one system
• you need both batch and streaming data processing

When to avoid

• you only need a simple single-source connector or lightweight ETL
• your data volumes are small and a basic message queue suffices
• you need a non-JVM-native stack with no Java operations expertise
• you want a fully managed cloud service rather than self-hosted infrastructure

Facets

framework · maturity stable

message-queue etl streaming data-science monitoring alerting big-data analytics jvm self-hosted cross-platform data-ingestion data-synchronization data-subscription tubemq apache-project massive-data event-streaming data-engineering messaging real-time docker kubernetes

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