Understanding Trino & Presto
Looking for a SQL Engine for your Data Lakehouse?
The Open Data Lakehouse brings the reliability and performance of the data warehouse together, with the flexibility and better price performance, of the data lake. This allows for enabling SQL and machine learning and artificial intelligence use cases on your data.
At the center of the data lakehouse is the SQL engine. While there are a few options you can choose from, Presto tends to be the leading choice. Because of its speed and ability to handle impressive amounts of data, Presto has become a more popular as the SQL engine for the data lakehouse.
Understanding Trino and Presto allows you to make the best decision for your data lakehouse and your use cases.
Curious why more users are picking Presto over Trino? Learn more about the benefits Presto provides data teams when utilized on the data lakehouse.
Understanding Trino & Presto
Trino is an apache 2.0 licensed, distributed SQL query engine. Trino was forked from the original Presto project, whose Github repo was called PrestoDB. Similar to Presto, Trino was designed and created from the ground up for fast queries against any amounts of data. Like Presto, Trino also supports any types of data sources including relational and non-relational sources via its connector architecture.
Presto is a federated, distributed SQL query engine that runs on a cluster of machines. It enables interactive, ad-hoc analytics on incredibly large amounts of data. Presto SQL queries are simple to execute on your data. PrestoDB enables querying data where it lives, including Hive, AWS S3, Hadoop, Cassandra, relational databases, NoSQL databases, or even proprietary data stores for analytics across an entire organization.
Blinkit, India’s delivery system committed to speed, chose Ahana Cloud & Presto for their Open Data Lakehouse.
Blinkit overcame the challenges associated with their data warehouse, including cost, lack of scale, and vendor lock-in. Blinkit was able to remedy these issues by moving to an Open Data Lakehouse with Ahana for Presto. Blinkint, after understanding Trino in comparison to Presto, decided to employ Presto as their SQL engine. This decision gave them a managed service, more flexibility, and a dramatic increase regarding price performance. Presto, as the heart of the Open Data Lakehouse, assisted Blinkit to move faster so they could meet their SLA’s. Currently the data lakehouse is assisting Blinkit with handling 200K orders per day and completing deliveries in 10 minutes.
Which to Choose? Trino or Presto
Understanding Trino and Presto allows you to notice some differences between them, but primarily, these differences lie within the services that facilitate either Trino or Presto; particularly, Starburst and Ahana. Trino, as a divergent of Presto, offers the same level of speed as Presto, as well as the ability to handle mass amounts of data. As a user, selection will typically be based on the SaaS offering. Below are some of the key differences between the SaaS offerings of Starburst and Ahana.
Taking the complexity out of these engines is not easy. Only Presto has a managed service through Ahana. Trino, through Starburst, does not offer this to users.
Presto has a strong following with a difference in outward credibility. Check out the list of companies using Presto, including Uber, Twitter, and Facebook.
Starburst’s pricing, for their standard tier runs about $2.80 per credit. Ahana’s pricing is $0.25 per credit. Ahana also offers their free Community Edition, which is forever-free.
Currently, this is the biggest differentiator. Ahana offers a free onboarding session with technical engineer and Enterprise SLA-based support (24/7).
Ahana offers AWS Lake Formation integration, as well as Apache Ranger integration. Starburst offers Hive catalog security and Authentication and authorization in Trino.
Looking for More Information about Trino and Presto?
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