10 Best PrestoDB Alternatives and Competitors in 2025

PrestoDB is an open-source, distributed SQL engine designed for running interactive queries across large datasets. Originally developed at Facebook, Presto lets users query data from multiple sources — like Hive, S3, MySQL, and Cassandra — without needing to move or transform it. It supports ANSI SQL, works at petabyte scale, and is popular in data lake and federated analytics environments.

But in 2025, many data teams are exploring PrestoDB alternatives that offer better performance, cloud-native deployment, unified batch + stream processing, or stronger governance. Whether you need faster lakehouse queries, easier scaling, or compatibility with Apache Iceberg or Delta Lake — modern SQL engines offer more flexibility with less tuning.

This article covers the best alternatives to PrestoDB, including successors like Trino and tools purpose-built for lakehouse, analytics, and federated SQL workloads.

What is PrestoDB?

PrestoDB is an open-source distributed SQL engine optimized for interactive analytics. It allows users to run fast SQL queries on data stored across multiple backends — including object stores, relational databases, NoSQL systems, and Hadoop clusters. Presto uses a memory-based architecture with a coordinator and worker nodes, making it ideal for federated querying and lakehouse architectures. While flexible, Presto can be challenging to tune and lacks built-in data governance or scheduling tools.

Why Look for PrestoDB Alternatives?

1. Performance Limitations: Presto is fast for lightweight queries but may struggle with large joins or long-running queries at high concurrency.

2. Complex Cluster Management: Operating Presto at scale requires careful tuning of memory, workers, and query configuration.

3. No Built-in Storage: Presto is a query engine only — it doesn’t manage data formats or handle ACID transactions natively.

4. Fork Confusion: The Presto ecosystem now includes multiple forks (PrestoDB vs. Trino), creating confusion around roadmap and community.

5. Newer Engines Support Iceberg/Delta Better: Modern tools like Dremio, Databricks, and Starburst are better optimized for table formats like Apache Iceberg and Delta Lake.

Top PrestoDB Alternatives (Comparison Table)

#	Tool	Open Source	Best For	Deployment
#1	Trino	Yes	Successor to PrestoDB	Cloud / Self-hosted
#2	Starburst	Partially	Enterprise Trino + governance	Cloud / Hybrid
#3	Dremio	Yes	Lakehouse SQL on Iceberg	Cloud / Self-hosted
#4	Databricks SQL	No	Delta Lake + unified analytics	Cloud
#5	ClickHouse	Yes	OLAP + real-time analytics	Cloud / Self-hosted
#6	Google BigQuery	No	Serverless SQL analytics	Cloud
#7	Amazon Athena	No	SQL over S3 (serverless)	Cloud
#8	Apache Drill	Yes	Schema-free SQL queries	Self-hosted
#9	Apache Spark SQL	Yes	Batch + SQL + lakehouse	Cloud / Self-hosted
#10	DuckDB	Yes	In-process SQL engine	Desktop / Local

Top 10 Alternatives to PrestoDB

#1. Trino

Trino is the community-led fork of PrestoDB (formerly known as PrestoSQL). It is faster, more active, and offers full support for modern lakehouse formats like Iceberg and Delta Lake — making it the most direct PrestoDB alternative.

Features:

• Fast distributed SQL engine
• Iceberg, Delta, Hive, Kafka, and S3 support
• Better memory management and joins
• Cloud-native architecture
• Active community + stable roadmap

#2. Starburst

Starburst is the commercial platform built on top of Trino, offering enterprise support, security, governance, and performance tuning. Ideal for replacing PrestoDB in mission-critical workloads.

Features:

• Based on Trino with extra features
• Built-in data catalog + access controls
• Cost-based query optimizer
• Federated queries across sources
• Available as Starburst Galaxy (SaaS)

#3. Dremio

Dremio is a lakehouse SQL engine that accelerates queries directly on data lake storage using Apache Iceberg and Arrow. It replaces PrestoDB with better query performance, semantic layers, and a modern UI.

Features:

• Query S3, ADLS, HDFS directly
• Apache Iceberg-native support
• Data reflections for acceleration
• Semantic layer + self-service UI
• Connects to Tableau, Power BI, etc.

#4. Databricks SQL

Databricks SQL is the SQL engine on top of the Databricks Lakehouse Platform. It provides lightning-fast Delta Lake queries, governance, and BI connectivity — replacing PrestoDB for analytics teams in the Databricks ecosystem.

Features:

• Delta Lake ACID support
• Photon engine for fast queries
• Serverless SQL endpoints
• Unity Catalog for governance
• Power BI, Tableau, and JDBC support

#5. ClickHouse

ClickHouse is a high-performance OLAP engine optimized for real-time analytics. While not federated like Presto, it outperforms it on log analytics, time-series queries, and dashboard backends.

Features:

• Columnar storage + compression
• Sub-second queries at scale
• Streaming ingestion (Kafka, S3, etc.)
• Horizontal scalability
• Used in observability + monitoring

#6. Google BigQuery

BigQuery is a serverless data warehouse that supports federated queries and massive scale analytics. It’s a managed alternative to PrestoDB for teams on Google Cloud.

Features:

• Pay-per-query or flat-rate pricing
• Federated query support (GCS, Sheets)
• Streaming ingestion + ML integration
• No cluster management
• Integrated with Looker + GCP stack

#7. Amazon Athena

Athena is AWS’s serverless query service that runs Presto under the hood. It provides SQL access to data in S3 without setting up infrastructure — ideal for replacing Presto with managed simplicity.

Features:

• Query S3 in-place with SQL
• Pay-per-query billing
• Supports Iceberg + Hive + Glue
• Integrates with QuickSight + Redshift
• No setup or tuning required

#8. Apache Drill

Apache Drill is a schema-free SQL engine that supports semi-structured data formats like JSON, Parquet, and Avro. It’s an open-source alternative to Presto for ad hoc queries over varied data types.

Features:

• No schema definition needed
• Query JSON, Parquet, HBase, Hive
• REST and JDBC/ODBC support
• Self-hosted deployment
• Lightweight and extensible

#9. Apache Spark SQL

Spark SQL is part of the Apache Spark ecosystem and supports distributed SQL processing, especially for batch ETL and analytics. It replaces Presto in teams that also need ML or streaming pipelines.

Features:

• Distributed DataFrame + SQL engine
• Integration with Delta Lake and Hive
• Supports structured streaming
• Runs on YARN, K8s, Mesos
• Part of larger Spark ecosystem

#10. DuckDB

DuckDB is an in-process, embedded SQL OLAP engine optimized for analytics on local data files (CSV, Parquet). It replaces Presto for data exploration, dev environments, and small-scale dashboards.

Features:

• Run SQL on local files with no server
• Parquet, CSV, and JSON support
• Python, R, CLI, and JDBC clients
• Fast on small-to-mid scale analytics
• Great for notebooks and prototyping

Conclusion

PrestoDB pioneered federated SQL queries, but in 2025, many modern engines offer faster performance, better governance, and simpler operations. Trino is its direct successor and most common upgrade path. Starburst adds enterprise features. Tools like Dremio and Databricks SQL optimize for lakehouses, while ClickHouse and DuckDB offer unmatched speed for OLAP use cases.

Whether you need serverless simplicity, streaming support, or better integration with Iceberg and Delta, there’s a PrestoDB alternative that fits your architecture and growth goals.

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