Databricks Expands Feature Set to Bring Apache Spark to More Enterprise Users

Databricks is enhancing its cloud based platform to strengthen its security, manageability and ease of application development.

According to the vendor, the new features securely manage data access for large teams while streamlining Spark application development and deployment for enterprises dealing with complex and fast-paced environments. 

“Databricks in the spirit of making big data simple is a couple things: what it offers is a managing infrastructure and instead of forcing people to write code, we offer an integrated environment for people to explore data in a more interactive fashion,” said David Wang, senior product marketing manager at Databricks.

The 2.0 platform will feature a variety of new functions including access control, R language support, integration with multiple Spark versions, and Notebook versioning.

Access control will further tighten security and manageability for large teams with diverse roles and responsibilities. Users will now be able to grant and restrict access of code and data on a flexible basis

R control will now allow users to explore Spark while using R to utilize one-click visualizations and instantly deploy R code.

“There is a lot of usage of the program in language R and that’s driven by a lot of people who are getting started with data science that learn R as part of their curriculum so that’s the first new thing we added,”

Additionally, the updated platform will support multiple versions of Spark, accommodating diverse production environments.

Notebook versioning will allow users to now manage and track the evolution of the codebase by integrating with popular version control tools, such as GitHub.

“We see these new needs coming up so we are attacking them based on feedback we’re seeing from customers as well as this prior roadmap we’ve envisioned about spreading Spark towards larger enterprises,” Wang said.

Developers and data scientists in large teams who work in complex production environments will benefit from this update, Wang explained.

“This is only the beginning,” Wang said. “This cadence of updates is something we intend to keep up and there is a lot more to come.”

For more information about Databricks, click here.


Subscribe to Big Data Quarterly E-Edition