What CAP Theorem Means to a Business Leader
...type of response is required to the end user when the system is under duress. Is accurate or the latest information more critical than available information? If I’m checking my...
Riding the Streaming Analytics Wave
...stream processing while also delivering the lowest latency. Fast forward to today when Forrester’s latest Wave for Streaming Analytics, The Forrester Wave™: Streaming Analytics, Q2 2021, places Hazelcast in a...
Asynchronous C++ Client
Asynchronous C++ Client The latest release of the Hazelcast C++ client API features so many changes and there may be only a few APIs we didn’t touch. We kept the...
5 Must-Read Articles on Kubernetes, Microservices and Stream Processing
Each month the Hazelcast team writes and curates articles to help executives, architects and developers stay up-to-date on the latest news and information. With that in mind, here are five...
Non-Stop Client with Near Cache
...of a shutdown of a server, crash or a disconnection issue with the cluster, the client with Near Cache will continue to serve with the latest version of values. The...
Change Data Capture (CDC)
...is useful for storing the latest state of data, CDC preserves the various states of data over time by providing an audit trail, and it can provide incremental changes to...
High-Speed Transaction Processing with No Compromise on Fraud Detection
...and tax variables, add-ons like premium support, etc. When a major device provider announces the latest offer, millions of people hit the site at the same time, and all those...
The One Beam to Rule Them All
...set. Announcing Hazelcast Jet Beam Runner As of May 2019, Hazelcast Jet has become the latest runner for Apache Beam. Even though we too have to pay the costs of...
5 Must-Read Articles on 2019 Predictions, IBM Cloud Private and Digital Transformation
Each month the Hazelcast team writes and curates articles to help executives, architects and developers stay up-to-date on the latest news and information. With that in mind, here are five...
Announcing Jet 0.6
...= Pipeline.create(); p.drawFrom(Sources.<Trade, Integer, Trade>mapJournal(TRADES_MAP_NAME, alwaysTrue(), EventJournalMapEvent::getNewValue, START_FROM_CURRENT)) .addTimestamps(Trade::getTime, 3000) .groupingKey(Trade::getTicker) .window(WindowDefinition.sliding(SLIDING_WINDOW_LENGTH_MILLIS, SLIDE_STEP_MILLIS)) .aggregate(counting(), (winStart, winEnd, key, result) -> String.format("%s %5s %4d", toLocalTime(winEnd), key, result)) .drainTo(Sinks.logger()); jet.newJob(p).join(); Stateful transforms with...