Matei Zaharia’s 5 predictions about big data and AI in 2018
Over the past few years, the demand for artificial intelligence (AI) and machine learning capabilities has surged with innovations in natural language processing...
Meltdown and Spectre: Exploits and Mitigation Strategies
In an earlier blog post , we analyzed the performance impact of Meltdown and Spectre on big data workloads in the cloud. In...
Meltdown and Spectre's Performance Impact on Big Data Workloads in the Cloud
Last week, the details of two industry-wide security vulnerabilities, known as Meltdown and Spectre , were released. These exploits enable cross-VM and cross-process...
Databricks Cache Boosts Apache Spark Performance
We are excited to announce the general availability of Databricks Cache, a Databricks Runtime feature as part of the Unified Analytics Platform that...
Databricks and Apache Spark™ 2017 Year in Review
At Databricks we welcome the dawn of the New Year 2018 by reflecting on what we achieved collectively as a company and community...
Unifying People Processes and Platform – The Movie
Today we released our Databricks Unified Analytics Platform video. This short video illustrates to analytics leaders how Databricks can unify their analytics efforts...
The Architecture of the Next CERN Accelerator Logging Service
This is a community guest blog from Jakub Wozniak , a software engineer and project technical lead at CERN physics laboratory, further expounding...
Spark Summit is Becoming the Spark + AI Summit
We’re excited to announce that Spark Summit is expanding its coverage in 2018 to include in-depth content on artificial intelligence. We are also...
Improving Threat Detection in a Big Data World
High-profile cybersecurity breaches dominated headlines in 2017. In the first half of the year, over 1.9B records were stolen . That’s more than...
Transparent Autoscaling of Instance Storage
Big data workloads require access to disk space for a variety of operations, generally when intermediate results will not fit in memory. When...