Bridging the big data analytics gap with Presto

Combining the power of Presto’s MPP SQL query engine that allows access to all data where it resides with Looker’s data analytics platform cultivates a data informed organization.

Speed of access to all data

Looker and Starburst both subscribe to the philosophy and technical architecture of not having to move data and being able to access and analyze data where it is stored. The power of Presto with Starburst’s distribution services allows for a single point of access to data that Looker can tap into for analytics in the hands of every user.

High performance and security

The Presto SQL query engine offers unparalleled performance to access large volumes of complex data at source (consolidated or federated). Looker leverages that single point of access to enable users to analyze the data to make informed business decisions in real time. This further expands the use cases where Looker and Startburst offer incremental value.

Superior scalability

Presto’s distributed query engine and Starburst’s federated cost-based query optimizer allows for greater scalability and high user concurrency. The separation of storage and compute eliminates the need for additional ETL or data integration and speeds up analytical insights for the Looker user base.

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Leverage Presto with Looker and Starburst

Starburst solves for the intersection of ever-increasing data volumes and data consumers. Through a data consumption layer, organizations de-prioritize data movement, while giving their teams consistent, easy, and fast SQL based access to all their data. Starburst’s single point of access allows Looker to bring analytics and data visualizations to the masses.

Fast and secure access to all data

  • Starburst’s MPP query engine gives organizations the ability to access all data, where it lives, with high concurrency
  • Purpose-built for large scale data discovery & ad hoc analytics, Starburst with Looker, brings analytics to all end users
  • Fine-grained access control at the connector, table, column, and row-level

Works for today and tomorrow

  • Separate data access from where data is stored, avoid data lock-in, and significantly reduce ETL
  • Get big data projects running in days, not months - with the ability to execute hundreds of thousands of queries per day, against petabytes of data
  • Use a language your team already knows: SQL
  • Allows users consistency of data access, as you migrate data to new forms of storage

Optimized price and performance

  • Give your data team optionality in how they execute queries to control costs
  • Separate SQL compute from data storage and scale each independently
  • In-memory, columnar architecture for fast query response
  • Starburst’s Presto distribution includes updated cost-based query optimizer, and optional caching of frequently accessed data

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