Introducing MLflow: an Open Source Machine Learning Platform
Learn more about Managed MLflow on Databricks Everyone who has tried to do machine learning development knows that it is complex. Beyond the...
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...
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...
A Technical Overview of Azure Databricks
This is a joint blog post from Matei Zaharia, Chief Technologist at Databricks and Peter Carlin, Distinguished Engineer at Microsoft. Today at Microsoft...
Databricks Delta: A Unified Data Management System for Real-time Big Data
Combining the best of data warehouses, data lakes and streaming For an in-depth look and demo, join the webinar . Today we are...
Sharing Knowledge with the Community in a Preview of Apache Spark: The Definitive Guide
Apache Spark has seen immense growth over the past several years. The size and scale of this Spark Summit is a true reflection...
Databricks and Apache Spark 2016 Year in Review
Spark Summit will be held in Boston on Feb 7-9, 2017. Check out the full agenda and get your ticket before it sells...
Spark Structured Streaming
Apache Spark 2.0 adds the first version of a new higher-level API, Structured Streaming, for building continuous applications . The main goal is...
Continuous Applications: Evolving Streaming in Apache Spark 2.0
Since its release, Spark Streaming has become one of the most widely used distributed streaming engines, thanks to its high-level API and exactly-once...
Introducing Apache Spark 2.0
Today, we're excited to announce the general availability of Apache Spark 2.0 on Databricks. This release builds on what the community has learned...