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Starburst Announces New Product Release Which Extends Flexibility When Building Data Lakehouse Architecture
Starburst announced the availability of the latest version of Starburst Enterprise. With enhanced performance, connectivity and security, Starburst Enterprise streamlines and expands data access across cloud and on-prem environments. Support for Apache Iceberg and MinIO with enhancements to materialized views empowers both data teams and domain experts with new data lake functionality that accelerates the journey to a data mesh architecture. 

"Apache Iceberg is a rapidly growing open table format designed for petabyte scale datasets. With the addition of Starburst support for querying data stored in Apache Iceberg, Starburst now provides its customers the optionality to use Iceberg or Delta Lake (or both) table formats for their data lakehouse architecture," said Matt Fuller, VP, Product and co-founder of Starburst. "Additionally, as companies continue to adopt hybrid and cross-cloud architectures, their data gravity is both in the cloud and on-prem. Businesses with data stored on-prem are opting for S3-compatible storage, such as MinIO as they build their private, cloud-like architecture. With official Starburst support for querying data stored in MinIO, MinIO users can enhance their hybrid and cross-cloud strategies."

"We created Iceberg to fix the scalability of Hive tables, and ended up making a larger impact on productivity for our data engineers," said Ryan Blue, Co-Creator of Apache Iceberg and Co-Founder & CEO of Tabular. "We're excited to partner with Starburst to support companies that want to embrace open standards and bring performance, scale, and productivity gains."

"As hybrid and multicloud architectures become pervasive, MinIO has emerged as the standard for object storage due to its performance, resilience, scalability and security characteristics," noted Ugur Tigli, Chief Technology Officer of MinIO. "With comprehensive support for the S3 API, Starburst customers can run their performance-oriented analytical workloads on data stored in MinIO, no matter the scale."

The release includes integration support with dbt. dbt is a popular and rapidly growing data transformation workflow tool. This functionality allows data teams to use SQL to create data transformations using Starburst in their data lakehouse. 

"dbt and Trino are a SQL-based marriage made in heaven. Both projects are key ingredients of the modern data stack and make it easy to use the language everyone knows to advance analytics," said Nikhil Kothari, Head of Technology Partnerships at dbt Labs. "We're happy to have dbt Labs working together with Starburst to make sure joint customers get the right support as they pursue fast analytics across distributed data that needs to be joined and transformed."

For companies building data products, whether as part of a data mesh architecture or otherwise, this release also delivers new features for building and optimizing data products via materialized views. This capability greatly improves domain experts' capacity to control how their data products are presented to data consumers.

In addition to new data lake and data product capabilities, this release of Starburst Enterprise includes these new and enhanced offerings:

  • This release significantly improves user experience by enhancing troubleshooting workflow with real-time transparency into server activity. Specific enhancements include updates to Worksheets and Live Queries, helping data engineers pinpoint issues related to performance of a particular cluster or a data source.
  • The enhanced Apache Ranger integrated experience makes initial set-up even easier. This improvement allows for a more frictionless experience by syncing the Starburst user store directly with Ranger.
  • Starburst continues to enhance integrations with various business intelligence tools. This release adds Kerberos support in Starburst's Tableau Connector.

In this release, Starburst Enterprise has also added connectivity to Vertica and Splunk along with a series of enhancements to existing connectors. Starburst Enterprise's new connector to Vertica provides additional capability to access large datasets. The new Splunk connector provides IT and DevOps teams with the ability to query their machine-generated data for use cases such as cyber security threat detection. In addition to the new Vertica and Splunk connectors, Starburst has continued investing in its existing portfolio of connectors with new updates on performance and security for a number of proprietary connectors.

Published Tuesday, November 16, 2021 10:52 AM by David Marshall
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