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Databricks is pleased to announce the release of Databricks Runtime 5.4.  This release includes Apache Spark 2.4.3 along with several important improvements and bug fixes .   We recommend all users upgrade to take advantage of this new runtime release.  This blog post gives a brief overview of some of the new high value features that...

In this blog post we introduce Databricks Connect, a new library that allows you to leverage native Apache Spark APIs from any Notebook, IDE, or custom application. Overview Over the last several years, many custom application connectors have been written for Apache Spark. This includes tools like spark-submit, REST job servers, notebook gateways, and so...

We are excited to announce the release of Databricks Runtime 5.4 ML (Azure | AWS). This release includes two Public Preview features to improve data science productivity, optimized storage in AWS for developing distributed applications, and a number of Python library upgrades. To get started, you simply select the Databricks Runtime 5.4 ML from the...

We are excited to introduce a new runtime: Databricks Runtime 5.4 with Conda (Beta). This runtime uses Conda to manage Python libraries and environments. Many of our Python users prefer to manage their Python environments and libraries with Conda, which quickly is emerging as a standard. Conda takes a holistic approach to package management by...

Here at Databricks, we are excited to participate in the first Snowflake Summit as a Diamond Partner. The event takes place June 3-6 at the Hilton San Francisco Union Square and is another great opportunity to share how Databricks and Snowflake have partnered together to provide: Massively scalable data pipelines. Pipelines running on Databricks can...

The value of analytics and machine learning to organizations is well understood. Our recent CIO survey showed that 90% of organizations are investing in analytics, machine learning and AI. But we’ve also noted that the biggest barrier is getting the right data in the right place and in the right format. So we’ve partnered with...

Databricks' commitment to education is at the center of the work we do. Through Instructor-Led Training, Certification, and Self-Paced Training, Databricks Academy provides strong pathways for users to learn Apache Spark™ and Databricks to push their knowledge to the next level. Our latest offering is a series of short videos introducing the Natural Language Processing...

Every enterprise today wants to accelerate innovation by building AI into their business. However, most companies struggle with preparing large datasets for analytics, managing the proliferation of ML frameworks, and moving models in development to production. AWS and Databricks are presenting a series of Dev Day events where we will cover best practices for enterprises...

Spark + AI Summit 2019, the world’s largest data and machine learning conference for the Apache Spark™ Community, brought nearly 5000 registered data scientists, engineers, and business leaders to San Francisco's Moscone Center to find out what’s coming next. Watch the keynote recordings today and learn more about the latest product announcements for Apache Spark,...

At Spark+AI Summit 2019, we announced the GA of Managed MLflow on Databricks in which we take the latest and greatest of open source MLflow and make it easily accessible to all users of Databricks. In that blog post, we promised to build features which bridge Databricks and MLflow concepts to create a seamless integration...