Born out of Microsoft’s SQL Server Big Data Clusters investments, the Apache Spark Connector for SQL Server and Azure SQL is a high-performance connector that enables you to use transactional data in ...

Google is promising a single notebook environment for machine learning and data analytics, integrating SQL, Python, and Apache Spark in one place. Readers might note that other prominent vendors in ...

Today, at its annual Data + AI Summit, Databricks announced that it is open-sourcing its core declarative ETL framework as Apache Spark Declarative Pipelines, making it available to the entire Apache ...

With the Hydrolix Spark Connector, Databricks users can use the Hydrolix streaming data lake to extract deeper insights faster and cheaper from their real-time and historical log data. According to a ...

I am currently working on a FastAPI application which calls Databricks using databricks-sql-connector, however the code appears to slow down massively on the engine creation stage. I've narrowed the ...

Databricks last week took the wraps off Databricks LakeFlow, which it says was designed to unify all aspects of data engineering, from data ingestion, transformation, to orchestration. According to ...

Since its launch in 2013, Databricks has relied on its ecosystem of partners, such as Fivetran, Rudderstack, and dbt, to provide tools for data preparation and loading. But now, at its annual Data + ...

See whether Databricks or Snowflake is the better ETL tool for you using our comprehensive guide to compare their features, pricing and more. With more and more solutions entering the enterprise ...