New cost savings option for Azure Databricks with DBU pre-purchase

Posted Leave a commentPosted in Announcements, Company Blog

The rapid adoption of Azure Databricks through our strategic partnership with Microsoft has been remarkable, and it’s proven to be a compelling service for our customers’ big data, analytics and machine learning initiatives. To further help our customers save costs and improve budgeting for Azure Databricks, we are pleased to share a new pricing option […]

Announcing Databricks Runtime 5.5 and Runtime 5.5 for Machine Learning

Posted Leave a commentPosted in Announcements, Apache Spark, Machine Learning

Databricks is pleased to announce the release of Databricks Runtime 5.5.  This release includes Apache Spark 2.4.3 along with several important improvements and bug fixes as noted in the latest release notes [Azure|AWS].  We recommend all users upgrade to take advantage of this new runtime release.  This blog post gives a brief overview of some […]

Getting Data Ready for Data Science: On-Demand Webinar and Q&A Now Available

Posted Leave a commentPosted in Announcements, Company Blog

On June 25th, our team hosted a live webinar — Getting Data Ready for Data Science — with Prakash Chockalingam, Product Manager at Databricks. Successful data science relies on solid data engineering to furnish reliable data. Data lakes are a key element of modern data architectures. Although data lakes afford significant flexibility, they also face […]

Scaling Genomic Workflows with Spark SQL BGEN and VCF Readers

Posted Leave a commentPosted in Announcements, Apache Spark, BGEN, Ecosystem, Engineering Blog, Genomics, HLS, Spark SQL, VCF

In the past decade, the amount of available genomic data has exploded as the price of genome sequencing has dropped. Researchers are now able to scan for associations between genetic variation and diseases across cohorts of hundreds of thousands of individuals from projects such as the UK Biobank. These analyses will lead to a deeper […]

Announcing Databricks Runtime 5.4 – The Databricks Blog

Posted Leave a commentPosted in Announcements, Company Blog, Databricks Connect, Library Utilities, Product, Runtime, Runtime 5.4

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 […]

Databricks Connect: Bringing the capabilities of hosted Apache Spark™ to applications and microservices

Posted Leave a commentPosted in Announcements, CoLab, Company Blog, Connect, Databricks Connect, Eclipse, Intellij, jupyter, Platform, Product, PyCharm, RStudio, Zeppelin

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 […]

Announcing the MLflow 1.0 Release

Posted Leave a commentPosted in Announcements, Company Blog, Data Science, Ecosystem, Engineering Blog, Lifecycle, Machine Learning, MLflow, Model Management, Product

MLflow is an open source platform to help manage the complete machine learning lifecycle. With MLflow, data scientists can track and share experiments locally (on a laptop) or remotely (in the cloud), package and share models across frameworks, and deploy models virtually anywhere. Today we are excited to announce the release of MLflow 1.0. Since […]

Enhanced Hyperparameter Tuning and Optimized AWS Storage with Databricks Runtime 5.4 ML

Posted Leave a commentPosted in Announcements, AutoML, Company Blog, Data Science, Databricks Runtime 5.4 ML, Deep Learning, Ecosystem, Engineering Blog, Hyperopt, Hyperparameter Tuning, Machine Learning, MLflow, MLlib, Platform, Product

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 […]

Introducing Databricks Runtime 5.4 with Conda (Beta)

Posted Leave a commentPosted in Announcements, Company Blog, Data Science, Databricks Runtime, Deep Learning, Ecosystem, Engineering Blog, Machine Learning, Product

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 […]