Frequently Asked Questions About the Data Lakehouse
Question Index What is a Data Lakehouse? What is a Data Lake? What is a Data Warehouse? How is a Data Lakehouse different…
Monitoring ML Models With Model Assertions
This is a guest post from the Stanford University Computer Science Department. We thank Daniel Kang, Deepti Raghavan and Peter Bailis of Stanford…
Introducing Databricks Unity Catalog: Fine-grained Governance for Data and AI on the Lakehouse
Data lake systems such as S3, ADLS, and GCS store the majority of data in today’s enterprises thanks to their scalability, low cost,…
Introducing Delta Sharing: An Open Protocol for Secure Data Sharing
Data sharing has become critical in the modern economy as enterprises look to securely exchange data with their customers, suppliers and partners. For…
An Update on Project Zen: Improving Apache Spark for Python Users
Apache Spark™ has reached its 10th anniversary with Apache Spark 3.0 which has many significant improvements and new features including but not limited…
Spark + AI Summit Europe is Expanding and Getting a New Name: Data + AI Summit Europe
Back in 2013, we held the first Spark Summit — a gathering of the Apache Spark™ community with leading contributors and production users…
Introducing the Next-Generation Data Science Workspace
At today’s Spark + AI Summit 2020, we unveiled the next generation of the Databricks Data Science Workspace: An open and unified experience…
MLflow Joins the Linux Foundation to Become the Open Standard for Machine Learning Platforms
Watch Spark + AI Summit Keynotes here At today’s Spark + AI Summit 2020, we announced that MLflow is becoming a Linux Foundation…
Introducing Apache Spark 3.0
We’re excited to announce that the Apache SparkTM 3.0.0 release is available on Databricks as part of our new Databricks Runtime 7.0. The…
Evolving the Databricks brand
Some brands start out as, well, brands. A lot of work goes into the concept and painting the picture before the business is…
