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Tag: imdg

Hazelcast Platform to Bring Historical, Real-Time Data Together

Hazelcast is best known as a developer of in-memory data grid (IMDB) technology, a RAM-loving layer for speeding up operational applications. But with the Hazelcast Platform launch currently slated for September, the San Read more…

GridGain Claims Huge Performance Boost with Intel Optane PMem

Companies running the in-memory computing platform from GridGrain Systems will see their machine learning, HPC, and analytics applications’ performance increase by 10x to 100x as a result of the use of Intel Optane per Read more…

The Past and Future of In-Memory Computing

When Nikita Ivanov co-founded GridGain Systems back in 2005, he envisioned in-memory computing going mainstream and becoming a massive category unto itself within a few years. That obviously didn’t pan out, but on the Read more…

Stream Processing Is a Great Addition to Data Grid, Hazelcast Finds

In-memory data grids (IMDGs) historically have exceled in applications that require the fastest processing times and the lowest latencies. By adding a stream processing engine, called Jet, to its IMDG, Hazelcast is findi Read more…

The Critical Element for a Successful Digital Transformation? HTAP Powered by In-Memory Computing

Many of today’s digital transformation and omnichannel customer experience initiatives demand real-time analysis of data. For example, banks need to analyze transactions across their systems in real time to detect and Read more…

ScaleOut Pushes the Bottleneck in Latest IMDG Update

Each computer architecture, by definition, has a bottleneck that prevents it from performing faster. With the latest release of its in-memory data grid (IMDG) for performing data-parallel analytics, ScaleOut Software has Read more…

How In-Memory Data Grids Can Analyze Fast-Changing Data in Real-Time

The ability to continuously analyze operational data unlocks the potential for organizations to extract important patterns. Popular big data systems are not well suited for this challenge. However, in-memory data grid technology (IMDGs) offers important breakthroughs that enable real-time analysis of operational data. Benchmarks have demonstrated that an IMDG can complete map/reduce analyses every four seconds across a changing, terabyte data set. This article discusses how IMDGs deliver this new capability to analyze fast-changing, operational data. Read more…

How In-Memory Data Grids Can Analyze Fast-Changing Data in Real-Time

Continuous analysis of fast-changing operational data unlocks the potential to extract important patterns. Big data systems such as Hadoop are not well suited for this challenge, however, in-memory data grids (IMDGs) offer breakthroughs that enable real-time analysis of fast-changing data. Recent measurements demonstrate that an IMDG can deliver a complete map/reduce analysis every four seconds across a terabyte data set which is being updated continuously.<br /> Read more…

Using In-Memory Data Grids for Global Data Integration

By enabling extremely fast and scalable data access even under large and growing workloads, in-memory data grids (IMDGs) have proven their value in storing fast-changing application data, such as financial trading data, shopping data, and much more. As organizations work to efficiently access their critical business data across multiple sites or scale their processing into the cloud, the need rapidly has grown to quickly and seamlessly migrate data where it is needed. The use of IMDGs creates an exciting opportunity for organizations to employ powerful global strategies for data sharing. Federating IMDGs across multiple sites enables seamless, transparent access to data from any site and provides an ideal solution to the challenge of global data integration. Read more…

Using an In-Memory Data Grid for Near Real-Time Data Analysis

With the ever increasing explosion in data for analysis and the need for fast insights on emerging trends, in-memory data grids (IMDGs) offer a highly attractive platform for hosting map/reduce analysis. In comparison to disk-based map/reduce platforms such as Hadoop, IMDGs reduce analysis times by reducing data motion while simplifying the development model. For applications which need to analyze fast-changing application data, such as shopping or financial trading data, IMDGs can provide near real-time results. Read more…

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