2024-11-20 21:18:00
Author: Starburst Data / 2023-07-25 15:16 / Source: Starburst Data

Starburst Unlocks Data Mesh Framework for AWS Customers

New AWS Lake Formation support allows organizations to further federate data on AWS

BOSTON,Nov. 29,2022 -- Starburst,the analytics anywhere company,today announced a new Starburst Enterprise support with AWS Lake Formationto help joint customers implement the technical aspects of data mesh. Data Mesh is a socio-technological framework for distributed data management which can help ensure faster and more accurate access to critical data to drive business decisions. By federating data across multiple AWS and third-party environments with Starburst Enterprise,organizations can realize the full value of their hybrid cloud investments,regardless of where the data resides.

Configuring and managing data lakes can be a cumbersome,complex,and time-consuming process. Data lakes require organizations to load data from multiple,often disparate,sources,into a centralized location,while setting up the partitions and columnar format,deduplicating redundant data,matching linked records,and defining and monitoring transformation jobs. The need to grant fine-grained access to datasets and audit access over time across a wide range of tools and services adds another layer of complexity,preventing organizations from quickly accessing data. And while nearly every enterprise or startup today is global or has users in different geographies,helping ensure secure access to data across clouds and geographies is now a requirement for proving compliance.

By liberating an organization's data with live,interactive queries directly on the data source,no matter where it lives,Starburst is empowering customers with a data mesh that allows cost-effective,multi-region analytics that doesn't compromise compliance or data integrity. The time and money saved on big data migration projects can be reinvested in building data products that can be easily accessed and analyzed by the business. This allows organizations to more efficiently and effectively respond to changing business requirements.

"AWS Lake Formation is a great benefit to organizations working to reduce data management complexity and management of their data lakes," said Toni Adams,SVP of Partners and Alliances at Starburst. "We're excited to work with AWS to serve our joint customers better. Data is typically highly distributed within organizations,and our new AWS Lake Formation support further helps customers securely access and leverage disparate data at scale,unlocking the value of the data mesh framework."

This support comes on the heels of a major growth moment for Starburst. The company marked the end of Q2 with 3x YoY annual recurring revenue (ARR) growth,122% YoY customer growth,and 61% YoY employee growth. Additionally,less than a year after its introduction,Starburst closed its first-ever seven-figure customer deal for Starburst Galaxy,the company's managed software as a service (SaaS) offering. The company also announced its first acquisitionin June 2022,acquiring data lake accelerator Varada,showing its steadfast commitment to innovation in the data lake,lakehouse,and data mesh space. To learn more,please visit starburst.io.

About Starburst

Starburst is the analytics engine for all your data. We provide the fastest,most efficient analytics engine for your data warehouse,data lake,or data mesh. We unlock the value of distributed data by making it fast and easy to access,no matter where it lives. Starburst queries data across any database,making it instantly actionable for data-driven organizations. With Starburst,teams can lower the total cost of their infrastructure and analytics investments,prevent vendor lock-in,and use the existing tools that work for their business. Trusted by companies like Apache Corporation,Comcast,Doordash,FINRA,Marks and Spencer,and VMware,Starburst helps companies make better decisions faster on all data.

For more information,press only:


Tucker Hallowell


Inkhouse


starburst@inkhouse.com


339-368-2290

Tags: Computer Software Computer/Electronics Data Analytics

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