Introducing Brickchain: Planet-scale Unified Analytics
Today we are excited to announce Brickchain , the next generation technology for zettabyte-scale analytics, by harnessing all the compute power on the...
Introducing Apache Spark 2.4
UPDATED: 11/19/2018 We are excited to announce the availability of Apache Spark 2.4 on Databricks as part of the Databricks Runtime 5.0...
Benchmarking Apache Spark on a Single Node Machine
Apache Spark has become the de facto unified analytics engine for big data processing in a distributed environment. Yet we are seeing more...
Introducing Apache Spark 2.3
Today we are happy to announce the availability of Apache Spark 2.3.0 on Databricks as part of its Databricks Runtime 4.0. We want...
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...
Benchmarking Big Data SQL Platforms in the Cloud
For a deeper dive on these benchmarks, watch the webinar featuring Reynold Xin. Performance is often a key factor in choosing big data...
A Vision for Making Deep Learning Simple
Try this notebook on Databricks When MapReduce was introduced 15 years ago, it showed the world a glimpse into the future. For the...
Top 5 Reasons for Choosing S3 over HDFS
At Databricks, our engineers guide thousands of organizations to define their big data and cloud strategies. When migrating big data workloads to the...