Databricks Lakehouse Platform combines cost-effective data storage with machine learning and data analytics, and it's available on AWS, Azure, and GCP.

Databricks can run Python, Spark Scholar, SQL, NC SQL, and other platforms. It comes packaged with its own user interface as well as ways to connect to endpoints such as JDBC connectors.

Databricks also announced updates to its Unity Catalog that expand support for Apache Iceberg — the open-source table format designed for large analytical datasets in data lakes — and introduce new ...

In a demo, Ghodsi showed me what the new SQL Analytics workspace looks like. It’s essentially a stripped-down version of the standard code-heavy experience with which Databricks users are familiar.

Databricks provides options for data visualization for users’ stored data. Image: Databricks. With the Snowflake web interface, Snowsight, users can visualize their data and query results as charts.

With Apache Spark Declarative Pipelines, engineers describe what their pipeline should do using SQL or Python, and Apache Spark handles the execution.

Fivetran Extends Integration With Databricks, Accelerating SQL Analytics, Data Science and Machine-Learning Applications . November 12, 2020 06:00 AM Eastern Standard Time.

With today’s announcement, Databricks is now officially supporting TensorFrames running on those AWS GPUs. Common Spark machine learning tasks, such as image processing and text analysist, run up to ...

StreamSets, a provider of a DataOps data integration platform, is partnering with Databricks, a provider of unified data analytics, to support data teams with rapid, no-code development using Apache ...

Amazon, Microsoft, Databricks, Google, HPE, and IBM machine learning toolkits run the gamut in breadth, depth, and ease ...