databus
A source-agnostic distributed change data capture system for reliably capturing and streaming primary data changes.
What is databus?
Databus is a source-agnostic distributed change data capture system built by LinkedIn to reliably capture and stream primary data changes from databases like Oracle and MySQL. It solves the problem of keeping secondary data stores, caches, and indexes consistent with primary data mutations by mining database transaction logs, avoiding the consistency issues of application-driven dual writes.
Data engineers and architects at technology companies building complex data ecosystems with multiple specialized data stores (e.g., relational databases, NoSQL, caches, search indexes) that need reliable, low-latency data change propagation.
Developers choose Databus for its source-agnostic approach that prevents technology lock-in, its strong consistency guarantees by using database logs as a single source of truth, and its ability to handle high throughput with low latency while supporting infinite data lookback.
Overview
Source-agnostic distributed change data capture system
Use Cases
Best For
- Building reliable data pipelines between primary OLTP databases and secondary stores like search indexes or caches
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