Overview

Built on Trino and Apache Iceberg, Starburst lets users query more than 50 sources in one SQL statement without copying the data. Its connectors cover data lakes, warehouses, streaming systems, relational databases, and other sources, making it a fit for organizations whose data already spans several platforms. Federation can spare teams from moving data just to query it, but it does not replace the systems where that data lives.

The platform combines SQL analytics, ACID transactions, streaming ingestion, and a governance catalog. Starburst supports on-premises, cloud, and hybrid deployments, while its Galaxy service runs on AWS, Google Cloud, and Microsoft Azure. That flexibility suits mixed estates, although organizations still need to select the deployment model that fits their own operating needs.

Key features

Federated queries and connectors

Starburst’s connectors bring varied sources into a common SQL workflow. Parallelism, table statistics, dynamic filtering, and pushdown are designed to improve connector query execution. These capabilities can help teams work across a broad data estate, but the practical value depends on whether the relevant sources and query patterns are a good fit.

Governance and security

Galaxy supports SSO, SCIM, service principals, role- and attribute-based access controls, row filters, column masking, and end-to-end encryption. Starburst says Galaxy does not store customer data, a useful distinction for organizations assessing the service’s data-handling model. Its security page displays HIPAA and GDPR badges and says the company independently verifies its security, privacy, and compliance controls.

Galaxy’s security page lists a 99.5% uptime SLA, 24/7 expert support, and a 30-minute response time. Those are meaningful service commitments for teams with operational requirements, though the highest uptime guarantees are reserved for Mission-Critical.

Pricing

Starburst has a free tier, paid credit-based plans, and a 30-day trial. The trial includes $500 in Galaxy compute resources and Enterprise features; it then downgrades to the free tier. The free option is useful for ad hoc evaluation, while teams planning sustained use should account for credit consumption.

Plan	Price and terms	What it includes	Best fit
Free	Free forever	Up to 3 clusters and standard cluster execution mode for ad hoc queries	Initial exploration and occasional ad hoc work; the three-cluster cap and standard mode limit its scope.
Pro	0.50 USD per contact; starting at /credit	Flexible cluster execution modes, streaming ingest, and advanced cluster management	Teams that need more execution flexibility and ingestion than the free tier provides.
Enterprise	0.75 USD per contact; starting at /credit	Advanced autoscaling, ABAC and SCIM access controls, AWS PrivateLink, and Private Preview features; AIDA token usage billed separately	Organizations requiring stronger access controls and advanced cluster management; separate AIDA charges should be budgeted if used.
Mission-Critical	1.00 USD per contact; starting at /credit	Elite support and ticketing, advanced governance integrations, lakehouse security and compliance tools, and highest uptime guarantees; AIDA token usage billed separately	Teams prioritizing support, governance integrations, and uptime commitments.

Paid plan rates are starting credit prices, not fixed subscription totals. Pro is the lowest-cost route to flexible execution and streaming ingest, while Enterprise adds access controls and autoscaling. Mission-Critical costs more but adds elite support and the highest uptime guarantees.

Platforms

Starburst supports API, Linux, self-hosted, and web platforms. Its deployment choices span on-premises, cloud, and hybrid environments; Galaxy is available on AWS, Google Cloud, and Microsoft Azure. That range is useful for organizations with varied infrastructure, while Galaxy’s stated cloud availability is limited to those three providers.

Who it's for

Starburst is best suited to data and analytics teams that need governed SQL access across distributed sources, particularly organizations operating a mix of cloud and on-premises systems. Its breadth of connectors and deployment choices also makes it relevant to organizations using analytics, AI, and applications across varied data estates. It is less suited to buyers seeking a fixed-cost subscription: paid usage is credit-based, and the free tier is capped at three clusters and standard ad hoc execution.

Pros and cons

Pros: Queries across 50+ sources in one SQL statement without copying data, which can simplify analysis across distributed systems.
Pros: On-premises, cloud, and hybrid deployment choices, plus Galaxy availability across AWS, Google Cloud, and Microsoft Azure, suit mixed environments.
Pros: Galaxy offers detailed identity, access, and data controls, including row filters and column masking.
Cons: The free tier permits up to three clusters and standard execution for ad hoc queries, limiting its reach for sustained or advanced workloads.
Cons: Paid prices are credit-based starting rates, so total spend depends on consumption rather than a simple fixed subscription.
Cons: AIDA token usage is billed separately on Enterprise and Mission-Critical, adding another usage cost to consider.

Alternatives

Data Lakehouse Platforms is a useful starting point for comparing products in the broader category.

Oracle Autonomous AI Lakehouse is another freemium option with a free plan and free trial for readers considering an alternative in the same space.

Starburst Galaxy is the more focused choice for readers specifically evaluating Starburst’s Galaxy service; its free tier is also capped at three clusters with standard execution for ad hoc queries.

Amazon SageMaker Autopilot is worth considering for readers who prefer a paid, pay-as-you-go option with a free trial rather than a free plan.

Bauplan offers a free Sandbox with a shared environment, public datasets or uploads, CLI, SDK, API, and community support for readers who want to begin with a public sandbox.

LavaLake offers a free Core plan with up to 16 vCPU on a single machine and community support, a different fit for readers seeking a single-machine starting point.

Databricks Notebooks has a free edition with one serverless workspace and limited compute size and usage for readers who want a notebook-focused alternative.

Google Cloud Lakehouse for Apache Iceberg is a paid alternative for readers specifically considering a Google Cloud lakehouse for Apache Iceberg.

IOMETE offers a free plan capped at 100 vCPUs with self-hosted, on-premises deployment and community support, which may suit readers prioritizing those characteristics.

Verdict

Choose Starburst when your teams need governed SQL access across distributed data and deployment flexibility spanning on-premises, cloud, and hybrid environments. Its federation and broad connector capabilities are the strongest reasons to consider it. Look elsewhere if predictable fixed subscription pricing or a more generous free tier matters more than cross-source access and deployment choice.

	Qlik Open Lakehouse	Starburst Data Platform
Free plan		Yes
Free trial		Yes
Paid from		Free
Platforms	Web	api, Linux, self-hosted, Web
Free plan	No	Yes
Storage model	external	both
SQL analytics	Yes	Yes
ACID transactions	Yes	Yes
Table format support	open	both
Streaming ingestion	Yes	Yes
Governance catalog	Yes	Yes

Qlik Open Lakehouse vs Starburst Data Platform

Qlik Open Lakehouse

Starburst Data Platform