Press release

Databricks Collaborates with Microsoft on MLflow Open Source Project

Sponsored by Businesswire

Databricks, the leader in Unified Analytics and founded by the original
creators of Apache Spark™, announced Microsoft is joining the open
source MLflow project as an active contributor and adding native support
for MLflow in Microsoft Azure Machine Learning service. MLflow is an
open source platform for the machine learning lifecycle. Since
Databricks unveiled MLflow in June 2018 at the Spark
+ AI Summit
, community engagement and contributions have led to
support for multiple programming languages and integrations with popular
machine learning libraries and frameworks. The community is working to
release MLflow 1.0.

Less than a year after the project was started, MLflow has more than
500K monthly downloads, over 80 code contributors and 40 contributing
organizations, confirming the need for an open source approach to
standardize the machine learning lifecycle across tools, teams, and

Azure Machine Learning is a popular machine learning service enabling
Azure customers to build, train, and deploy machine learning models. To
provide its customers with maximum flexibility, Microsoft supports open
source MLflow in Azure Machine Learning. This means that developers can
use the standard MLflow tracking API to track runs and deploy models
directly into Azure Machine Learning service.

Databricks is excited to announce that Managed MLflow is generally
available on Azure Databricks and it will use Azure Machine Learning to
track the full ML lifecycle. This approach enables organizations to
develop and maintain their machine learning lifecycle using a single
model registry on Azure.

“We’ve been thrilled by the contributions from Microsoft and the wider
MLflow community. These contributions include support for multiple new
programming languages, popular machine learning frameworks and
services,” said Matei Zaharia, co-founder and chief technologist at
Databricks, and original creator of Apache Spark and MLflow. “It is
inspiring to see the rapid adoption of the project. In terms of
contributor count, MLflow achieved in 9 months what Apache Spark took 3
years to achieve. We have an aggressive roadmap for MLflow in 2019 and
are excited to work with the community to expand the project.”

Rohan Kumar, Corporate Vice President, Azure Data at Microsoft, said,
“We’re committed to the MLflow open source project, and leveraging and
contributing to the innovations that are created in the community. We
will continue to contribute innovations to make the machine learning
lifecycle more efficient for Microsoft Azure customers.”

About Databricks
Databricks’ mission is to accelerate
innovation for its customers by unifying Data Science, Engineering and
Business. Founded by the original creators of Apache Spark, Databricks
provides a Unified Analytics Platform for data science teams to
collaborate with data engineering and lines of business to build data
products. Users achieve faster time-to-value with Databricks by creating
analytic workflows that go from ETL and interactive exploration to
production. The company also makes it easier for its users to focus on
their data by providing a fully managed, scalable, and secure cloud
infrastructure that reduces operational complexity and total cost of
ownership. Databricks has secured investments from Andreessen Horowitz,
Coatue Management, Microsoft, New Enterprise Associates (NEA), Battery
Ventures, Green Bay Ventures, and Geodesic, among others, and has a
global customer base that includes Viacom, Shell and HP.

Apache, Apache Spark and Spark are trademarks of the Apache Software