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Tag: oltp

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…

ScyllaDB Gives Cohabitation of OLAP and OLTP A Shot

ScyllaDB today announced the availability of a new feature of its Apache Cassandra-compatible database called "workload prioritization" that it says will eliminate the need for organizations to maintain separate database Read more…

Actian Stages Comeback With Hybrid Database

Actian Corp., which reportedly dropped out of the analytical database market last fall, is making a comeback with the release of a hybrid database that combines transaction processing with its analytics query engine A Read more…

Microsoft SQL Server Supports Linux

Microsoft widened its embrace of the Linux kernel with a preview release this week of its next SQL Server, further extending its business analytics platform to run on open-source distributions. Microsoft (NASDAQ: MSFT Read more…

Bridging the Gap between Insight and Action

In the past few years, IT leaders and C-level executives have associated ”big data” with looking at historical information with a fresh set of eyes. The concept has been to delve further into transactions retrospecti Read more…

Beyond Titan: The Evolution of DataStax’s New Graph Database

DataStax's 2015 acquisition of Aurelius--the company behind the TitanDB graph database--was a clear statement about the importance of graph databases to Cassandra customers. Today marks the official announcement of DataS Read more…

HP Spins Out Trafodion to Power Transactional Hadoop

The feasibility of running transactional workloads side by side with analytical workloads on Hadoop got a little clearer this summer when Hewlett-Packard spun out Trafodion, a "webscale SQL-on-Hadoop" solution. The new c Read more…

Now and Then: The Evolution of In-Memory Computing

The history of data warehousing, big data, and analytics can be described as a constant challenge to process and analyze ever-increasing volumes of data in shorter amounts of time. Fundamentally, the single biggest facto Read more…

Toward Comprehensive Big Data Benchmarking

It’s difficult enough to keep track of the ebb and flow of new tools that span the big data ecosystem, let alone keeping tabs on the latest measures and standards by which to evaluate the influx. While there are standards for a number of specific application areas, architectures, and programmatic approaches, it’s difficult to get a more comprehensive view across solutions and system-wide needs. Read more…

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