Debezium Blog

This past summer has been a super exciting time for the team. Not only have we been working hard on Debezium 0.10 but we have unveiled some recent changes to debezium.io.

The temperatures are slowly cooling off after the biggest summer heat, an the Debezium community is happy to announce the release of Debezium 0.10.0.Beta4. In this release we’re happy to share some news we don’t get to share too often: with Apache Cassandra, another database gets added to the list of databases supported by Debezium!

In addition, we finished our efforts for rebasing the existing Postgres connector to Debezium framework structure established for the SQL Server and Oracle connectors. This means more shared coded between these connectors, and in turn reduced maintenance efforts for the development team going forward; but there’s one immediately tangible advantage for you coming with this, too: the Postgres connector now exposes the same metrics you already know from the other connectors.

Finally, the new release contains a range of bugfixes and other useful improvements. Let’s explore some details below.

The summer is at its peak but Debezium community is not relenting in its effort so the Debezium 0.10.0.Beta3 is released.

This version not only continues in incremental improvements of Debezium but also brings new shiny features.

All of you who are using PostgreSQL 10 and higher as a service offered by different cloud providers definitely felt the complications when you needed to deploy logical decoding plugin necessary to enable streaming. This is no longer necessary. Debezium now supports (DBZ-766) pgoutput replication protocol that is available out-of-the-box since PostgreSQL 10.

This post originally appeared on the WePay Engineering blog.

In the first half of this blog post series, we explained our decision-making process of designing a streaming data pipeline for Cassandra at WePay. In this post, we will break down the pipeline into three sections and discuss each of them in more detail:

This post originally appeared on the WePay Engineering blog.

Historically, MySQL had been the de-facto database of choice for microservices at WePay. As WePay scales, the sheer volume of data written into some of our microservice databases demanded us to make a scaling decision between sharded MySQL (i.e. Vitess) and switching to a natively sharded NoSQL database. After a series of evaluations, we picked Cassandra, a NoSQL database, primarily because of its high availability, horizontal scalability, and ability to handle high write throughput.

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