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Tag: OLAP

Building a Cost-Effective, High-Performing BI Ecosystem on the Cloud

The shift from on-premise environments to the cloud is happening at a tremendous pace. However, once enterprises move their data to the cloud and make it available to their business users, they face several challenges, s Read more…

Building a Cost-Effective, High-Performing BI Ecosystem on the Cloud

The shift from on-premise environments to the cloud is happening at a tremendous pace. However, once enterprises move their data to the cloud and make it available to their business users, they face several challenges, s Read more…

Druid Developer Expands Query Options

The latest release of a real-time data analytics platform takes makes use of a new SQL feature in Apache Druid that combines data or rows from multiple tables based on common values. Imply, the real-time analytics sta Read more…

Kyligence Grows OLAP Business in the Cloud

Companies that need to analyze large amounts of data have many options available to them these days. One option they may want to be aware of is Kyligence, which develops a distributed OLAP query engine that can run on pr Read more…

AtScale Tackles Data Engineering with Virtualization Software

It’s often the prep work in analytics that kills you. Before any analysis can be run, engineers must assemble, transform, and standardize the data. In a world where data silos are proliferating in the cloud, on premise Read more…

Druid Developer Ramps Cloud-Native Approach

A real-time analytics startup founded by the authors of the Apache Druid database have raised additional funding as they ramp up product development based on the open-source data store. Imply said it has raised $30 mi Read more…

Probing Data’s Middle Ground

The rise of data lakes has in the process of consolidating data exposed a gap between databases, files and other data repositories and the ability to view, analyze and leverage those data. Targeting that middle ground 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…

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…

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…

Kyvos Debuts OLAP for Hadoop

Many technology pros view OLAP as a legacy technology, a holdover from the days of data warehousing that doesn't have a place in today's big data world. But several startups are fighting to change that perception, includ Read more…

AtScale Claims to Mask Hadoop Complexity for OLAP-Style BI

AtScale came out of stealth mode today with new software designed to trick business intelligence tools into thinking that Hadoop is a standard database upon which they can perform OLAP-style analysis, as opposed to the h 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…

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