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Food & Beverage Giant Shifts to a Single Point of Access for All Data with Starburst and Microsoft

When one of the world’s leading food and beverage companies, with multiple brands generating more than $1B each in estimated annual retail sales, recognized the need to upgrade their data storage and analytics capabilities, they turned to Starburst and Microsoft. 

This global conglomerate’s diverse portfolio of brands totalled massive quantities of data siloed in different proprietary systems. Their brands had the goal of learning more about each other’s businesses and customers but analyzing this trapped data was a challenge. Prior to being introduced to Starburst, the team was leveraging Hive to query their Hadoop data sets. This was incredibly slow, costly to manage, and didn't allow them to access other data sources.

Before connecting with Starburst, the company’s Data Engineering Services team initiated a plan to stream all new data into Microsoft’s Azure Data Lake Storage (ADLS). When Starburst was introduced to the architecture, a perfect compliment, the architecture was efficiently structured for higher performance and faster time to insight which resulted in lower costs and a scalable infrastructure for the future. 

By switching from Hive to Starburst, the company was able to achieve 42% faster queries and cut down their Hadoop infrastructure costs by 75%.

Starburst and ADLS

Starburst Enterprise includes high-performance connectors to ADLS, Teradata warehouses, and other common data storage platforms. Designed to analyze data where it lies, Starburst Enterprise allows Business Intelligence and Data Analytics teams to simultaneously query company data in ADLS and on-premise warehouses without costly ETL.

Starburst Enterprise is a versatile partner to Microsoft and a powerful addition to its larger cloud ecosystem. This general architecture diagram demonstrates Starburst’s integration with multiple Azure data sources, in addition to relational and non-relational databases, and various BI tools. This broad range makes Starburst especially appealing to large global enterprises like the beverage giant.



Faster Time-to-Insight

Both ADLS and Starburst are designed to accelerate time-to-insight. Previously, it would take weeks to get data out of this company’s Teradata warehouses into their data lake. Now business units, wholesalers, and brands can immediately access and query data wherever it lies and join it with larger data sets for faster insights.

Cost Savings via Autoscaling

When the team spun up a cluster with HDInsight, they had to leave it running, which resulted in them paying for this cloud infrastructure 24/7. The auto scaling feature in Starburst Enterprise allowed the company to easily meet user needs by automatically scaling up during busy times and gracefully scaling down at nights and weekends – saving money and taking advantage of the Azure cloud infrastructure. This way, the company only pays for the Azure services it uses, making the deployment far more cost-effective.

Cloud Analytics and Scalable Infrastructure for the Future

Starburst Enterprise and Microsoft ADLS have empowered this global food and beverage leader with a more efficient and scalable architecture for the future. The inexpensive, resilient, highly scalable storage of ADLS, along with the security enhancements and analytics anywhere capabilities of Starburst Enterprise are helping to move the company closer to its goal of becoming the global leader in convenient foods and beverages.

Read the full study here.


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Latifah Obaid

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By | on 18, Feb 2021 |   hive Trino

After a decade of running Hive queries on their data lakes, many companies are astonished at the speeds in which they are able to query their existing Hive tables by just replacing Hive with Starburst[...]

By | on 12, Feb 2021 |   hive technical features

TL;DR: The Hive connector is what you use in Starburst Enterprise for reading data from object storage that is organized according to the rules laid out by Hive, without using the Hive runtime code.