Infinispan 9

We decided it was time to revisit Infinispan’s performance and scalability. So we went back to our internals design and we made a number of improvements. Infinispan 9.0 is faster than any previous release by quite a sizeable margin in a number of key aspects:

We will have a post dedicated to benchmarks detailing the difference against previous versions and in various scenarios.

We’ve made several improvements in the cluster and persistent storage marshalling layer which has resulted in increased performance and smaller payloads. Also, the new marshaller layer makes JBoss Marshalling an optional component, which is only used when no Infinispan Externalizers (or AdvancedExternalizers) are available for a given type, hence relying on standard JDK Serializable/Externalizable capabilities to be marshalled.

We now ship alternate marshallers for remote clients based on Kryo and ProtoStuff.

Additionally, the Hot Rod protocol now supports streaming operations for dealing with large objects.

An In-Memory Data Grid likes to eat through your memory (because you want it to be fast!), but in the world of the JVM that is not ideal: that huge chunk of data gives Garbage Collectors a hard time when the heap goes into double-digit gigabyte territory. Long GC pauses can make individual nodes unresponsive, compromising the stability of your cluster.

Infinispan 9 introduces an improved data container which can optionally store entries off-heap.

Additionally, our bounded container has been replaced with Ben Manes' excellent Caffeine which provides much better performance. Check out Ben’s benchmarks where he compares, among other things, against Infinispan’s old bounded container.

Configuration-wise, the previously separate concepts of eviction, store-as-binary and data-container have been merged into a single 'memory' configuration element.

The JDBC cache store received quite an overhaul:

We have also replaced the LevelDB cache store with the better-maintained and faster RocksDB cache store.

We decided it was time for Infinispan to have a proper query language, which would take full advantage of our query capabilities. We have therefore grafted Lucene’s full-text operators on top of a subset of JP-QL to obtain Ickle. We have already started describing Ickle in a recent blog post. For a taste of Ickle, the following query shows how to combine a traditional boolean clause with a full-text term query:

select transactionId, amount, description from com.acme.Transaction where amount > 10 and description : "coffee"

Infinispan continues to play nicely in cloud environments thanks to a number of improvements that have been made to discovery (such as KUBE_PING for Kubernetes/OpenShift), health probes and our pre-built Docker images.

Infinispan Server is now capable of exposing multiple cache containers through a single Hot Rod or REST endpoint. The selection of the container is performed via SNI. This allows you to have a single cluster serve all your applications while maintaining each one’s data isolated.

The adminstration console has been completely rewritten in a more modular fashion using TypeScript to allow for greater extensibility and ease of maintanence. In addition to this refactor, the console now supports the following:

Our documentation has been completely overhauled with entire chapters being added or rewritten for readability and consistency.

We will be blogging in more detail about some of the things above, so watch out for more content coming soon !

We’ve already started working on Infinispan 9.1 which will bring a number of new features and improvements, such as clustered counters, consistency checker with merge policies, a new distributed cache for even better write performance, and more.

Head over to our download page to get binaries, sources, clients, etc.

Please join us to let us know what you think about this release.

The Infinispan team