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Compatibility with Apache Kafka
AutoMQ is a next-generation Apache Kafka® distribution redesigned based on cloud-native concepts. It is compatible with the Apache Kafka® protocol and features. This article provides a detailed overview of the compatibility of different AutoMQ versions.
In terms of technical architecture, AutoMQ reuses the compute layer code of Apache Kafka® and only replaces minimal components at the storage layer. This ensures complete compatibility with relevant versions of Apache Kafka®. Applications based on Apache Kafka® can be seamlessly replaced with AutoMQ.
During the compatibility verification phase, AutoMQ used Apache Kafka® test case projects and successfully passed the relevant version tests. The specific data is as follows:
Apache Kafka® Test Module |
Passed Test Cases |
Total Test Cases |
Failed Test Cases |
Reason for Failure |
---|---|---|---|---|
sanity_check |
41 |
48 |
7 |
Failure cases only apply to Zookeeper mode. Since AutoMQ runs in KRaft mode, these cases can be ignored. |
client |
37 |
86 |
49 |
|
tools |
8 |
9 |
1 |
|
benchmark |
58 |
120 |
62 |
|
core |
95 |
348 |
253 |
|
connect & streams |
100 |
291 |
191 |
|
Total |
339 |
902 |
563 |
The compatibility relationship between AutoMQ and Apache Kafka is as follows:
AutoMQ |
Apache Kafka Server |
Kafka Client |
Kafka Connector |
HTTP Proxy |
---|---|---|---|---|
v1.1.x (Upcoming release) |
|
|
Compatible |
Compatibility |
v1.0.x |
|
|
AutoMQ versions align directly with Apache Kafka versions, ensuring each AutoMQ version is compatible with Kafka Client, Connector, Proxy, and other components within the Apache Kafka ecosystem.
AutoMQ employs a micro-layer storage replacement method to adapt to Apache Kafka, enabling rapid updates to new community versions and supporting the latest Apache Kafka version updates as quickly as within T+1 month.
- What is automq: Overview
- Difference with Apache Kafka
- Difference with WarpStream
- Difference with Tiered Storage
- Compatibility with Apache Kafka
- Licensing
- Deploy Locally
- Cluster Deployment on Linux
- Cluster Deployment on Kubernetes
- Example: Produce & Consume Message
- Example: Simple Benchmark
- Example: Partition Reassignment in Seconds
- Example: Self Balancing when Cluster Nodes Change
- Example: Continuous Data Self Balancing
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S3stream shared streaming storage
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Technical advantage
- Deployment: Overview
- Runs on Cloud
- Runs on CEPH
- Runs on CubeFS
- Runs on MinIO
- Runs on HDFS
- Configuration
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Data analysis
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Object storage
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Kafka ui
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Observability
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Data integration