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How In-Memory Computing Powers Artificial Intelligence

Dan Ortega

Artificial Intelligence (AI) as a concept has been around since the development of computational devices, as early as the creation of Turing machines during World War II. The term itself was first coined by University of Washington professor John McCarthy in 1956, and now, 60+ years later we see the actual commercialization of AI. Why […]

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How to Become More Productive with Hazelcast in Less Than 5 Minutes

Hazelcast Community

On Monday, Speedment and Hazelcast announced a partnership focused on accelerating application development when deploying an in-memory data grid alongside legacy databases. The following post was written by Speedment’s CTO, Per-Åke Minborg. What if you want to use a Hazelcast In-Memory Data Grid (IMDG) to speed up your database applications, but you have hundreds of […]

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Calculation in Hazelcast Cloud

Neil Stevenson

This is an example showing one way you might connect to Hazelcast Cloud, and how you can harness its power for improved performance. As a problem, we’re going to calculate the spread of customer satisfaction, as the average doesn’t give enough insight. The example shows a custom domain model and server-side code execution. It shows […]

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Hazelcast Responds to Redis Labs’ Benchmark

Greg Luck

Due to its underlying architecture and many years of optimization, Hazelcast is extremely fast and dramatically outperforms Redis Labs (and Redis open source), especially at scale. Last year, Redis Labs published a very misleading benchmark against Hazelcast. We have closely investigated Redis Labs’ test and discovered many misleading aspects of the benchmark. As a result, […]

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How to Use Hazelcast Auto-Discovery with Eureka

Rafal Leszko

Hazelcast IMDG supports auto-discovery for many different environments. Since we introduced the generic discovery SPI, a lot of plugins were developed so you can use Hazelcast seamlessly on Kubernetes, AWS, Azure, GCP, and more. Should you need a custom plugin, you are also able to create your own. If your infrastructure is not based on […]

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A Business Level View of Kubernetes, Cloud Migration and In-Memory Technologies

Dan Ortega
by Dan Ortega | April 04, 2019

There’s a trio of buzzwords that are starting to spend more time in proximity to each other, and are also beginning to surface from the technical to the business world. Each by itself is critical, and when you combine all three, the business-level effect becomes very noticeable. These buzzwords and the business descriptors are: Kubernetes: […]

Distributed Locks are Dead; Long Live Distributed Locks!

Ensar Basri Kahveci
by Ensar Basri Kahveci | April 02, 2019

“Distributed locks aren’t real”, some like to remind us. “Anyone who’s trying to sell you a distributed lock is selling you sawdust and lies.” This may sound rather bleak, but it doesn’t say that locking itself is impossible in a distributed system: it’s just that all of the system’s components must participate in the protocol. […]

Announcing Hazelcast Cloud GA

Enes Akar
by Enes Akar | March 26, 2019

Today, we are announcing the general availability of Hazelcast Cloud, our new managed service. I remember the day about 9-years-ago when I created my first cluster in Hazelcast and how impressed I was by the ease of the process and the limited need for configuration. A year later, I joined the company as a developer, […]

Hello JSON, Hello YAML and Goodbye XML!

Neil Stevenson
by Neil Stevenson | March 20, 2019

This is an example showing the use of YAML configuration, and populating a Hazelcast grid with data in JSON format that has been extracted from a traditional relational database. So the data goes from tables into “NoSQL” format. Hello YAML, Goodbye XML Hazelcast has many ways to be configured. Sensible defaults mean you don’t have […]

Riding the CP Subsystem

Ensar Basri Kahveci
by Ensar Basri Kahveci | March 18, 2019

The CP Subsystem of Hazelcast IDMG 3.12 offers a new linearizable implementation of Hazelcast’s concurrency APIs on top of the Raft consensus algorithm. These implementations live alongside AP data structures in the same Hazelcast IMDG cluster (new BFFs, yay!). You can store large data sets on hundreds of Hazelcast members and coordinate your operations using […]

In-Memory Data Grids Popularity Trend Continues Upward

David Brimley
by David Brimley | March 14, 2019

The past year has seen in-memory data grids (IMDG) continue to gain traction with the development community and large organisations alike. As you’ll see in the 2019 IMDG LinkedIn Survey results below, adoption of IMDG as a skill in LinkedIn profiles has risen by 43% YoY. Companies are turning to IMDGs as replacements for RDBMS […]

How Pairing In-Memory Streaming with IoT Will Fundamentally Change Your Business

Dan Ortega
by Dan Ortega | March 06, 2019

Knock-knock Your business is already under assault, whether you know it or not. It doesn’t matter whether you’re B2B or B2C; the same technology variables are driving pressure on your IT infrastructure. The growth of the global technology ecosystem has always been organic. While new technologies often layer on top of previous enablers (e.g. mobility […]

What CAP Theorem Means to a Business Leader

Dan Ortega
by Dan Ortega | February 28, 2019

The data we continuously generate and use operates on an incredibly vast scale (think of Google, Amazon, Facebook, that level of data). Because of the breadth and depth of infrastructure required to stream incoming data and execute against it (and to avoid single points of failure), the ingestion and processing of data is distributed across […]

Introducing Pipelining in Hazelcast IMDG 3.12

by Peter Veentjer | February 27, 2019

Hazelcast IMDG 3.12 contains a new performance optimization called pipelining. If you have a client/server with a 1ms round trip time, then a single thread will only be able to make 1/001=1000 operations per second. The most obvious way to improve performance is to add a second thread because with two threads you can do […]

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