Starburst Expands Support for Building Interactive Applications on the Data Lake
New functionality allows customers to ingest, govern, and share data in near real-time while leveraging the scale and cost-efficiency of a data lake
Note: TDWI's editors carefully choose vendor-issued press releases about new or upgraded products and services. We have edited and/or condensed this release to highlight key features but make no claims as to the accuracy of the vendor's statements.
Data lake analytics platform provider Starburst has announced new capabilities that enable organizations to build and scale data applications without compromising on performance or cost. With the increasing interest in building artificial intelligence (AI)-driven data applications, customers need to establish a solid data platform. New features in Starburst Galaxy help customers simplify development on the data lake by unifying data ingestion, data governance, and data sharing on a single platform.
Interactive applications often require the scalability and cost-efficiency of a data lake, but building and maintaining that data lake is complex and time-consuming for data teams. To overcome these challenges, Starburst has added support for:
- Near-real-time analytics with streaming ingestion. With streaming ingestion, customers can leverage Kafka to populate their data lake in near-real-time, ensuring applications have the most up-to-date insights for their users. Upcoming support for fully managed solutions, such as Confluent Cloud, is also planned.
- Automated data governance. As new data lands in the lake, machine learning models in Gravity -- a universal discovery, governance, and sharing layer in Starburst Galaxy -- will automatically apply classifications for certain categories. Depending on the class, Gravity will apply policies granting or restricting access. This automation is particularly useful for teams handling sensitive data such as personally identifiable information (PII). Now, Gravity will be able to identify and restrict access to PII as soon as it lands in the lake.
- Automated data maintenance. New automations make it easy for customers to optimize their data lake by abstracting away common management tasks such as data compaction and data vacuuming. Users can now maintain warehouse-like performance without adding brittle manual processes, as the volume and complexity of data in their data lake grows.
- Universal data sharing with built-in observability. With Gravity, users can easily package data sets into shareable data products to power end-user applications, regardless of source, format, or cloud provider. New functionality will allow users to securely share these data products with third parties, such as partners, suppliers, or customers.
- Self-service analytics powered by AI. Not only are data lakes notoriously hard to manage, but the majority of data teams are understaffed. New AI-powered experiences in Galaxy, such as text-to-SQL processing, will enable data teams to offload basic exploratory analytics to business users, freeing up their time to build and scale data pipelines.
Starburst’s position as an Amazon Web Services (AWS) Data and Analytics Competency Partner means that AWS customers can rest assured that these features will be made available on the fastest hardware AWS has to provide, including AWS Graviton3 and the newly launched Amazon Simple Storage Service (Amazon S3) Zonal storage class, and will integrate seamlessly with core tools like AWS QuickSight and new tools like Amazon Bedrock.
To learn more about Starburst, visit www.starburst.io/.