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starburst, provider of enterprise platform offerings for optimizing Trino’s distributed SQL query engine, recently marked a milestone anniversary of the original open source code family from which the engine’s development stems. Trino is a highly parallel, open-source distributed SQL query engine designed to perform interactive analytics on large amounts of data. VentureBeat spoke to co-creator Dain Sundstrom about the growth and future of the project.
Open Source Project Line
Ten years ago, the original Presto/Trino open-source code family was founded by Sundstrom and co-creators Martin Traverso, David Phillips and Eric Hwang at Facebook to quickly solve the problem of analytics and queries across Facebook’s large data sets. In 2018, the creators separated from Facebook and the original family of code was split into two lines, the leftover under Facebook being called PrestoDB and the creators targeted by the creators called PrestoSQL. In December 2020, the PrestoSQL lineage of the code was renamed Trino, under which name this lineage of code is still being developed today.
The engine was originally created to quickly query huge data sets, and it has: grown and very refined since its early days. Features such as security, which barely existed in the first few releases, are now at the heart of the project. The ecosystem of supported tools and integrations has expanded, as has the number of data connectors. These include connectors to relational data sources such as: PostgreSQL, Oracle and SQL serveras well as non-traditional sources such as Elastic search, OpenSearch, MongoDB and Apache Kafka. Sundstrom described additional refinements currently in the works, such as redesigning the function language for improved extensibility, improving support for ETL workloads, and making this functionality work out-of-the-box to improve productivity for non-users. experts to improve.
Sundstrom says the creators decided to open source the project based on the shared open source background between them. Some of the challenges they faced and overcome included expanding and scaling the system – not just the software, which is a difficult enough problem in itself, but also the community: helping open the communication between different members of the community to encourage collaboration around solving a common problem, rather than developing solutions to the same problem at the same time.
Trino usage scenarios
Trino is used by many companies, including Netflix and LinkedIn, for internal analytics, and some of these companies also contribute to the open source project, such as Bloomberg and Comcast. Sundstrom discussed how Trino is especially popular with real-time, internet dispatch/taxi-like services and food delivery services, including Lyft and DoorDash, because it can perform extremely fast, low-latency queries over large data sets. Sundstrom said it also performs extremely well on geospatial data, which is increasingly common and can be difficult to analyze.
Future vision of Trino
Looking to the future, Sundstrom said he is excited about Trino and its future as the pace of innovation continues to accelerate and its use cases are able to cover extensive workloads and data types. He expects greater growth in the problems that Trino can approach. For example, by adding the ability to process geospatial data, card companies, mobile carriers and food delivery companies can derive added value from analyzing customer data.
The Trino community has already proven to be very capable of finding innovative solutions to the problems of its users. It’s hard to believe that the Presto/Trino platforms are now 10 years old, but it’s easy to imagine that Trino will become applicable to more use cases and user requirements over time.
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