Category: Hazelcast

Feed: Hazelcast Blog. Author: Hazelcast Community. dotkam recently published a blog post entitled, “Hubble Space Mission Securely Configured“. In the post, dotkam presents a strategy for building better security and flexibility for our space missions. This week we learned of a recent alien hacking into Earth. We have a suspect but unsure about the true source. Could be The Borg, could be Klingons, could be Cardassians. One thing is certain: we need better security and flexibility for our space missions. We’ll start with the first line of defense: science based education. The better we are educated, the better we are ... Read More

Feed: Hazelcast Blog. Author: Hazelcast Community. Tomas Kloucek recently published a bitbucket post entitled, Cluster Leader Election with Spring Integration in Hazelcast. In the post, Tomas demonstrates a method for fine-grained control of Microservice and IMap interaction with Hazelcast and Spring. Recently when checking Spring Integration area I noticed of pretty nice integration with Hazelcast datagrid. Check this out at: https://github.com/spring-projects/spring-integration-extensions/tree/master/spring-integration-hazelcast If you use Hazelcast then you can feed your Spring Integration channel infrastructure from various distributed datastructures backed by Hazelcast like: com.hazelcast.core.IMap, com.hazelcast.core.MultiMap, com.hazelcast.core.IList, com.hazelcast.core.ISet, com.hazelcast.core.IQueue, com.hazelcast.core.ITopic, com.hazelcast.core.ReplicatedMap Sweet, but what really impressed me is the implementation of cluster ... Read More

Feed: Hazelcast Blog. Author: Vladimir Shreiner. High performance has always been a major design goal of Hazelcast Jet. In order to verify various performance aspects of Jet, we’ve introduced the following benchmarks: Word count, to measure and compare the raw computational power during batch processing. Trade monitor, which is based on a streaming aggregation and involves windowing and event-time based processing. 5,000 jobs benchmark which was motivated by use cases where thousands of various data processing feeds run on the same cluster. Parallelism is achieved by sharing the resources among sequential jobs rather than parallelizing one job. Let’s have a ... Read More

Feed: Hazelcast Blog. Author: Jaromir Hamala. Hello Hazelcasters! First off I would like to introduce myself – I started contributing to the project about 4 years ago, later on I joined as a performance engineer and in last 2 years I led the core engineering team. I am very excited to be stepping to the position of head of engineering at here at Hazelcast. Now on to the BIG news. We just released an Early Access version of Hazelcast IMDG 3.9! The whole Engineering team worked incredibly hard to make it happen and in this post I would like to ... Read More

Feed: Hazelcast Blog. Author: Greg Luck. I am very excited to announce that after months of engineering work and assistance from Pivotal, Hazelcast Jet is now available as a Tile on Pivotal Cloud Foundry (PCF) – the first general purpose data processing platform available on PCF. As a member of the Cloud Foundry community we are determined to enhance the services available on the platform by equipping developers with an open distributed processing engine for big data streams driven by a mature and stable tribe of contributors. Deploying Hazelcast in the cloud has never been easier. Hazelcast Jet for Pivotal ... Read More

Feed: Hazelcast Blog. Author: Denis Sukhoroslov. Q: What is your primary task when you start a new project? A: To choose the right set of tools for the job, I believe. This is the story about how I had to “choose the right tool” and how that lead me to build Bagri, the document DB. At one time, I decided to build my own XML database because there were no suitable solutions on the market at that time. RDBMS extensions like Oracle XML DB, DB2 XML were quite limited and had no full XQuery support. Native XML DBs like BaseX, ... Read More

Feed: Hazelcast Blog. Author: Greg Luck. We recently conducted a second performance benchmark between Redis 3.2.8 cluster and a Hazelcast IMDG 3.8 cluster, following on from an earlier benchmark we did last year against 3.0.7. Check out the benchmark. Hazelcast Faster In summary, when comparing get performance, Hazelcast IMDG was up to 56% faster than Redis. For set performance, the Hazelcast IMDG was up to 44% faster than Redis. We extended our lead from last year where we were 32% faster on gets. This was with Near Cache disabled for Hazelcast, so it was an over the network for each ... Read More

Feed: Hazelcast Blog. Author: Christoph Engelbert. We had the chance to speak with Ben Evans, Java Champion, author for O’Reilly and InfoQ, as well as co-founder of JClarity, a startup which delivers performance tools and services to help development and ops teams. Together with his recent whitepaper on Hazelcast in combination with Spark, he also delivered a small application, BetLeopard, to demonstrate the integration between the two technologies. Chris Engelbert: You’re around in the Java world for quite some time, when did you start with Java and why? Ben Evans: Well, one of the things about me is that I ... Read More

Feed: Hazelcast Blog. Author: Mesut Celik. IBM has a cache abstraction called Dynacache in Websphere Application Server(WAS) Distributions. That abstraction is handy if you want to use a configurable built-in cache solution in your JEE application deployed into WAS environment. Following is the basic retrieval of built-in Dynacache provider via JNDI private static DistributedObjectCache cache = retrieveDynacache(); static DistributedObjectCache retrieveDynacache(){ try { InitialContext ic = new InitialContext(); return (DistributedObjectCache) ic.lookup("services/cache/distributedmap"); } catch (NamingException e) { // catch the exception } } IBM Dynacache is used internally to improve performance of WAS Deployment. Here are the list of features to boost ... Read More

Feed: Hazelcast Blog. Author: Hazelcast Community. DataMountaineer recently published a blog post entitled, “Hazelcast – Low Latency Datastores for IOT“. In the post, DataMountaineer presents a strategy for building low latency datastores for Internet of Things using Kafka and Hazelcast. The Internet of Things is on the rise, it was certainly a buzzword of 2016. Gartner thinks so, they say there will be 20 billion devices online by 2020 with all of them transmitting (streaming) data. These devices are not limited to new devices, more and more we are seeing our clients want to connect into manufacturing control systems such ... Read More