Wirekite Replicate
Stream every change. Catch up in minutes.
Wirekite Replicate keeps your warehouse in lockstep with production. Built for teams that can't accept four-hour reporting lag.
The CDC performance problem.
Change Data Capture is supposed to be the fast path between OLTP and analytics. In practice, most teams' CDC pipelines fall behind during peak hours, recover overnight, and run their reporting on eight-hour-old data.
The bottleneck is rarely the source. Postgres can emit changes from a logical slot at 300K rows/sec. MySQL's binlog reader can keep up with a busy primary. The problem is downstream: parsing, transforming, and applying those changes one at a time on the target.
Wirekite Replicate uses a binary change format, engine-tuned capture on the source, and batched MERGE on the target. The loader keeps up with what the source can produce, not what a typical CDC tool can consume.
How Wirekite Replicate works.
1
Saturate the source
Wirekite captures change data through paths tuned to each engine's internals, keeping every available channel busy. The source-side bottleneck disappears.
2
Binary change format
Captured changes go into Wirekite's own binary format, optimized for the loader to consume at line rate. No JSON parsing, no verbose intermediates.
3
Batched MERGE on target
Changes are de-duplicated per row-key and applied as batched MERGE statements on the target — taking advantage of the warehouse's bulk-apply path instead of row-at-a-time.
Lag, throughput, ordering — all live.
Drill into any table at any moment. The pipeline never goes dark on you.
What the numbers look like.
Lag measured under sustained production-shaped load.
Targets beyond databases
Stream changes to Kafka, Redpanda, or Pub/Sub.
Same Replicate pipeline. Per-table ordering. Exactly-once delivery.
Read about queues
Trust the pipeline
Validate the target row by row.
On demand, any time. Type-aware comparison across cross-database edge cases.
Read about validation
Need your warehouse current?
We'll set up a CDC pipeline against your sample workload during the demo.