21 posts tagged with "release"

Conduit v0.13.4 is out and comes with a couple of configuration fixes.

Today, we released Benchi, a minimal yet powerful benchmarking framework that makes it easy to configure and run performance benchmarks for any tool.

We are using Benchi to run performance benchmarks for Conduit and other data streaming tools, ensuring that all tools are tested under the same conditions and that the results are comparable. Check out how we use it in the Streaming Benchmarks repository.

Today, we released a new version of Conduit v0.13.3, adding new builtin processors and fixing a bug when using batching delay on the connector with an older version of our Conduit Connector SDK.

Today, we released Conduit v0.13.2 to fix the possibility of building custom Conduit applications after the introduction of our Conduit CLI.

Check out this page for more information on how to build custom Conduit applications.

We're introducing the new MySQL Connector for Conduit, which allows extraction of data from and loading data into MySQL databases. This connector supports dual operation modes, including snapshot and Change Data Capture (CDC) for the source connector, as well as a destination connector for upserting records.

After we released Conduit v0.13.0, there were a couple of things that weren't working as we had planned.

Thanks to the quick reports from our users, we were able to fix them promptly and release a new version: Conduit v0.13.1.

New year, new release! We're excited to announce that Conduit v0.13.0 is off the press. This one includes some features we've been eager to ship for a while now.

We'd like to let you know that Conduit v0.12.3 is now out. It contains a fix for an issue related to batching as well as internal improvements.

Conduit v0.12.2 comes with up to 5x more throughput, new CLI command for initializing Conduit and pipelines, as well as bug fixes.

We’re excited to announce the release of Conduit v0.12.0, which introduces Pipeline Recovery! This new feature enhances the resilience of your data streaming pipelines, ensuring they can recover from temporary errors without manual intervention.