
Trino/Presto
Alternative
Why users are migrating from Trino and Presto to StarRocks
Trino and Apache Presto are arguably the most popular open source engines for data lakehouse queries. Compared to their predecessors like Hive, Trino and Presto can reduce query latencies from tens of minutes to tens of seconds. While these performance improvements were good years ago, it's not enough for modern analytics work. Today, Trino and Presto users struggle with interactive query scenarios where query latency needs to be in the sub-second range to support their ad-hoc queries, operational analytics, and user-facing analytics.
This is just the tip of the iceberg when it comes to Trino and Presto's limitations. Other major challenges include:
Latency
analytics
StarRocks vs. Trino and Presto
Query external data sources.
No ingestion needed.
In addition to more efficient analysis of local data, StarRocks can work as the query engine to analyze data stored in data lakes such as Apache Hive, Apache Iceberg, Apache Hudi, and Delta Lake.
With StarRocks' external catalog, users are able to query external data sources seamlessly with zero-migration, analyzing data from different systems such as HDFS and Amazon S3, in various file formats such as Parquet, ORC, and CSV.
Deliver unparalleled performance in any scenario
StarRocks offers 3x greater performance when querying data on the data lake compared to Trino and Presto. StarRocks achieves this thanks to its unique vectorized execution engine, written in C++ to make full use of the SIMD instructions in modern CPUs. And because StarRocks includes an optimized native storage engine, you're able to unify data lake analytics, low latency, and highly concurrent workloads with one database.
Work with the freshest data, even on your data lake
Perform analytics on the freshest data possible, even on your data lake, without need for any data migration. Data lake users don't have to set up a separate data pipeline for real-time analytics. Streaming data from sources (such as Apache Kafka) are ingested into StarRocks and made available to analytics in real-time. StarRocks' storage engine also uses the Delete-and-insert pattern, which allows for efficient Partial Update and Upsert operations.
Accelerate your analytics with intelligent materialized views
With its breakthrough Intelligent Materialized View (IMV) technology, StarRocks can transparently accelerate queries and simplify data pipelines. IMVs are automatically refreshed to guarantee data consistency, and queries are automatically re-written to leverage IMVs. Expensive ETL jobs can also be replaced with IMVs to simplify data pipelines.
Compare Trino and Presto to StarRocks
Designed for the analytics needs of modern enterprises, StarRocks delivers the capabilities and performance. Trino and Presto can't say the same.
Trino | Presto
StarRocks
Featured success stories
These leading enterprises have made the move to StarRocks. Learn how they've supercharged query performance, eliminated maintenance work, and accelerated insights:
Analytics See why SF Express moved from a Presto-based big data platform to a modern one based on StarRocks' blazing-fast technology. Read More