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A complete comparison of Starburst and Dremio

Discover how Starburst and Dremio compare across platform access, scalability, simplicity, and optionality, including real customer reviews and G2 Crowd ratings.

What is Starburst?

Starburst brings the power and performance of data warehouses to your modern data lake, offering a full-featured data lake analytics platform built on open-source Trino – the MPP SQL query engine used by some of the largest internet companies. The Starburst platform enables teams to discover, govern, organize, analyze, and consume data with self-service analytics in on-premises, hybrid, or cloud-centric data architectures. Starburst is used for both interactive ad-hoc analytics, as well as long-running workloads like batch and ETL/ELT.

What is Dremio?

Dremio is a data lakehouse platform providing self-service SQL analytics, data warehouse performance and functionality, and data lake flexibility. As the original creators of Apache Arrow, Dremio supports ad-hoc and interactive analytics for data engineering and data science use case.

Starburst is a Leader in Enterprise Big Data Analytics

Don’t take our word for it. Starburst is named #1 for Quality of Support and Ease of Use in G2 Crowd’s Grid Report based on real customer reviews. Additionally, customers said Starburst beat out Dremio in all of these categories: 

  • Meets Requirements
  • Ease of Use
  • Ease of Admin
  • Quality of Support
  • Data Visualization
  • Multi-Source Analysis 

Simplicity

Going beyond key platform governance and management capabilities, a modern data analytics platform empowers data teams to increase productivity without adding complexity, allow you to use a range of existing investments in just a few clicks, and allow you to build data products, no matter where the data lives, once and scale usage and adoption across the organization – creating a trusted single version of the truth.

Starburst Galaxy

Dremio Cloud

Data products

Data products

GenAI text-to-SQL

GenAI text-to-SQL

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Built-in universal data sharing

Built-in universal data sharing

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Automated data lake optimization

Automated data lake optimization

Automated AWS compute plane set-up

Automated AWS compute plane set-up

Cross-cloud and cross-region analytics

Cross-cloud and cross-region analytics

Comparison based on publicly available information as of November 3o, 2023.

* In preview. Contact us to learn more.

Access

Empower data teams with the ability to securely use all their data assets, no matter where they live, across data lakes, data warehouses, and databases. With your modern data lake analytics platform easily discover, create, govern, share, and collaborate on curated data sets by connecting your data silos before, during, and after your modernization journey.

Starburst Galaxy

Dremio Cloud

Attributed based access control (ABAC), role-based access control (RBAC), row-level filters, and column masking

Attributed based access control (ABAC), role-based access control (RBAC), row-level filters, and column masking

Multi-region access control and governance

Multi-region access control and governance

Time bases access control

Time bases access control

Integration with AWS Lakeformation

Integration with AWS Lakeformation

Multi-cloud data catalog and searchability

Multi-cloud data catalog and searchability

Popular data sources for federation

Popular data sources for federation

Multiple cloud regions across AWS, Azure, and GCP

Multiple cloud regions across AWS, Azure, and GCP

Optimized connectors - parallelism, cached views, dynamic filtering, and security and authentication

Optimized connectors - parallelism, cached views, dynamic filtering, and security and authentication

Streaming ingest

Streaming ingest

Comparison based on publicly available information as of November 3o, 2023

* In preview. Contact us to learn more.

Scalability

A modern data lake analytics platform with high concurrency puts the control in your hands to ensure performant scalability is available when you need it most while optimizing price-to-performance for all analytics workloads.

Optionality

A modern data lake analytics platform takes the lakehouse architecture beyond the basics of open file and table formats by providing choice in hybrid or cloud environments, more data federation, seamless cross-cloud and cross-region analytics, choice in data catalogs without compromising the user experience and offering an enhanced MPP SQL query engine based on open standards and supported by the largest internet companies in the world.

Starburst Galaxy

Dremio Cloud

Open source MPP SQL query engine

Open source MPP SQL query engine

Supports popular file formats

Supports popular file formats

Supports all major open table formats

Supports all major open table formats

Supports popular data catalogs

Supports popular data catalogs

Dataframe API for Python

Dataframe API for Python

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Enterprise grade 24x7 support

Enterprise grade 24x7 support

Support for Apache Ranger

Support for Apache Ranger

Comparison based on publicly available information as of November 3o, 2023

* In preview. Contact us to learn more.

Free test drive | Watch | Contact us

Access and analyze your data with elastic scale and high performance your business demands. Take Starburst Galaxy for a free test drive, watch the on-demand demo (no form fill needed), or contact us.

Some additional exploration

What is Dremio used for?

Dremio is used to run interactive and ad-hoc analytics on federated data. However, with Starburst, you can access more data sources, cross-cloud and cross-region analytics, internet scale performance, universal search and discovery, enterprise-grade support SLAs, and more.

What kind of tool is Dremio?

Dremio and Starburst offer an open data lakehouse platform that provides self-service SQL analytics, data warehouse performance and functionality, and data lake flexibility across your data. However, with Starburst, you gain a similar experience across AWS, Azure, and GCP, more data sources for federated data products, and a highly performant MPP SQL query engine with optimized open-source Trino.

Is Dremio an ETL tool?

Similar to Starburst, Dremio supports a wide range of data types for analysis. Some of the data types that can be analyzed include:

  • Numeric data types such as DECIMAL, INT, BIGINT, FLOAT, and DOUBLE
  • String and binary data types, such as VARCHAR and VARBINARY
  • Boolean data type BOOLEAN
  • Date and time data types such as DATE
  • Semi-structured data types like LIST and STRUCT, as well as data type mappings for external sources, time zone support, and coercions support

However, Starburst can support additional types via plugins. Connectors to data sources are not required to support all Trino data types described. If there are data types similar to Trino’s that are used on the data source, the connector may map the Trino and remote data types to each other as needed.

 

What is Dremio Cloud?

It is Dremio’s SaaS-based GUI data lakehouse tool. Compute is deployed in the customer’s own cloud account. Dremio Cloud is supported on AWS in 5+ cloud regions (Microsoft Azure is in preview). Compute can only be provisioned in the region selected at setup; customers may incur costs even when not writing queries.

Start Free with
Starburst Galaxy

Up to $500 in usage credits included

  • Query your data lake fast with Starburst's best-in-class MPP SQL query engine
  • Get up and running in less than 5 minutes
  • Easily deploy clusters in AWS, Azure and Google Cloud
For more deployment options:
Download Starburst Enterprise

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