Apache Arrow defines an in-memory columnar data format that accelerates processing on modern CPU and GPU hardware, and enables lightning-fast data access between systems. Working with big data can be ...

In-memory data systems have have had a panache for several years now. From SAP HANA to Apache Spark, customers and industry watchers have been continually intrigued by systems that can operate on data ...

Apache's new project leverages columnar storage to speed data access not only for Hadoop but potentially for every language and project with big data needs A new top-level project for the Apache ...

The core reason for implementing in-memory technology is to improve performance. To help accelerate adoption of in-memory technologies and provide a universal standard for columnar in-memory ...

A monthly overview of things you need to know as an architect or aspiring architect. Unlock the full InfoQ experience by logging in! Stay updated with your favorite authors and topics, engage with ...

There are significant performance optimizations available for systems that consume and process primarily analytical data, but seldom are software applications written in a way that can take advantage ...

Hadoop, Spark and Kafka have already had a defining influence on the world of big data, and now there’s yet another Apache project with the potential to shape the landscape even further: Apache Arrow.

A few years back, we noted the emergence of Apache Arrow; what piqued our attention was that the backers consisted of "a who's who list" of over 20 committers from the likes of Cloudera, MapR, ...

Value stream management involves people in the organization to examine workflows and other processes to ensure they are deriving the maximum value from their efforts while eliminating waste — of ...