How adding a functional utility helps to avoid code duplications and leads to more readable code.

In Spring Data Redis, we support multiple Redis clients – Jedis and Lettuce.
Commands can be invoked either directly, in a transaction, or using pipelining.

Direct commands get invoked – as the name probably reveals – directly by calling a client method and returning the result. In some cases, results require post-processing because the Redis driver reports a Long while Spring Data Redis would like to return Boolean or the driver returns a driver-specific type that requires conversion in a Spring Data type.

R2DBC Tour took place in Mid- and North-parts of Germany. R2DBC standardizes reactive integrations with SQL databases as Open Source initiative.

Reactive Relational Database Connectivity (R2DBC) started out as idea to see what’s possible when thinking about reactive programming and SQL databases. Since the last months, R2DBC grew beyond that idea. It inspired driver maintainers and client library authors as common language: A specification for drivers and an interface for library authors so they can build client libraries on top of a vendor-independent SPI. Client libraries are tools that we as application developers need to keep productivity high and not to solve problems that are solved already.

In my previous blog post I started an experiment with using Project Loom. The post outlined the first steps to make use of virtual Threads on a best-effort basis (i.e., without rewriting the entire libraries involved, instead fixing issue by issue until it works™).

Last year I announced the R2DBC Java User Group and recently I started the tour visiting various user groups and conferences. Reactive Relational Database Connectivity lifts a roadblock when integrating with SQL databases. It’s an Open Source standardized API across multiple database drivers and an ongoing specification effort hosted on GitHub.

This article walks you through a experiment that uses a Spring Boot application with Virtual Threads. Having access to early access builds is the perfect opportunity to take a look what it takes to use virtual threads as worker threads. With all customizations in place, we issue a few request to verify that our application is running. Finally, we put a bit of load onto the application to see how memory consumption and the number of kernel threads develop over time.

Follow-up post: Carrier Kernel Thread Pinning of Virtual Threads (Project Loom).

Imperative code eats threads at the pace of incoming requests while Software is eating the world. This post discusses the assumptions for reactive programming on the JVM and what this means for integrations – in particular, relational databases.

The motivation to come up with a post is the constant increase in reactive programming adoption while some major building blocks are not yet available – in particular, the question: What about relational databases?

This blog post explains the motivation behind removing Project Lombok from one of the projects to which I contribute. It reflects my personal opinion and is not discouraging particular technologies.

About three years ago, I got to know Project Lombok, a library that spices up Java code. I liked it from the beginning as it contributes so much useful functionality. I work a lot with entities (data classes) and value objects, so it does not come as a surprise that @Data or Kotlins data class are very convenient. You get more bang for the buck – literally.
I’m mentioning Kotlin here because it shares some of the properties that we also get from Lombok.

R2DBC is an endeavor to bring a reactive programming API to relational data stores and stands for Reactive Relational Database Connectivity. It was first announced at SpringOne Platform 2018. I’m happy to announce my R2DBC tour across Java User Groups in Germany, Switzerland, and Austria. I will explain what R2DBC is, how it was founded and what to expect from a reactive relational database integration. We will speak about the SPI, various drivers, and about Spring.

Spring Framework announced recently to ship with support for reactive transaction management.
Let’s take an in-depth look at how this works for R2DBC, the reactive specification for SQL database access.

Redis Streams have made it into Redis’ unstable branch since the beginning of this year, and the first clients start with the adoption of Redis Streams APIs. That makes it an excellent time to take a look what Redis Streams provide and how you can use them from a client perspective.