Snowflake alternatives are cloud data platforms for storing and querying large amounts of business data. They fall into three camps: cloud data warehouses, lakehouse platforms that query open table formats such as Apache Iceberg, and fast OLAP engines built for real-time analytics. Ten options follow in no particular order.
Here's the short version. Swapping a data warehouse is a big job, so the first decision isn't which vendor but which architecture. A warehouse, a lakehouse and an OLAP engine all answer SQL queries, but they store data differently and suit different workloads.
The ten platforms below are listed alphabetically and in no particular order, and every description comes from each vendor's own website, read as of Oct 2026.
Snowflake alternatives at a glance
I checked the free plan column on each vendor's own website, as of Oct 2026. Yes means the page names a free plan, a free version or an open source edition. Trial only means it names a time-limited free trial. Not stated means the page I read named neither, so check the vendor's own site before you sign up.
| Tool | Type | Good for | Free plan |
|---|---|---|---|
| Azure Synapse | Microsoft analytics service | Warehousing and big data on Azure | Not stated |
| BigQuery | Google Cloud data platform | Warehouse and lakehouse on Google Cloud | Not stated |
| ClickHouse | Open source OLAP database | Real-time analytics at speed | Yes |
| Databricks | Data and AI lakehouse | Unified data engineering, warehousing and AI | Not stated |
| Dremio | Agentic lakehouse | Open Iceberg lakehouse analytics | Not stated |
| MotherDuck | DuckDB cloud warehouse | Analytics for small teams | Not stated |
| Redshift | AWS cloud warehouse | Querying warehouses and data lakes on AWS | Not stated |
| Starburst | Trino-based query platform | Querying data without moving it | Trial only |
| Teradata | Enterprise data platform | Large enterprise warehouses with AI | Not stated |
| Yellowbrick | SQL data platform | Warehousing with data residency control | Not stated |
Ten cloud data platforms to compare
Azure Synapse
Best for: Microsoft shops running enterprise data warehouses and big data together, with a migration assistant now pointing towards Fabric.
BigQuery
Best for: Google Cloud teams wanting a platform that automates the data life cycle from ingestion to AI insights, with Iceberg lakehouse upkeep handled for them.
ClickHouse
Best for: Engineering teams needing fast, open source real-time analytics, self-run or managed on AWS, Google Cloud or Azure, including inside their own cloud account.
Databricks
Best for: Data and AI teams that want one platform for warehousing, ETL pipelines, governance and AI apps, built on the lakehouse model.
Dremio
Best for: Enterprises wanting an open lakehouse on Apache Iceberg and Polaris, in the cloud or self-managed on Kubernetes, now part of SAP.
MotherDuck
Best for: Small data teams, engineers and founders who want a cloud warehouse built on DuckDB without enterprise overhead.
Redshift
Best for: AWS customers wanting a managed warehouse that queries across warehouses and data lakes and supports agentic AI workloads.
Starburst
Best for: Analysts who need to query data across lakes, databases and warehouses without copying it, on Trino and Apache Iceberg.
Teradata
Best for: Large enterprises with established warehouses that want autonomous AI and knowledge tools working on top of their data.
Yellowbrick
Best for: Public sector and regulated organisations needing a SQL data platform that runs anywhere, with data residency and streaming analytics.
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Warehouse, lakehouse or OLAP engine, not a ranking
Here's what stood out reading the vendor pages. Ownership is changing: Dremio's page says it's now part of SAP, and the ClickHouse page notes that Langfuse has joined it. Snowflake itself now sells what it calls the AI Data Cloud, and Teradata has renamed its pitch an autonomous knowledge platform.
Microsoft's page for Azure Synapse now points readers to Fabric, with a migration assistant for data warehouses, so check where the roadmap is heading before you build on it. And Databricks makes the lakehouse case bluntly, saying the best warehouse is still a lakehouse.
Which kind of data platform fits your workload?
- Cloud data warehouses. Managed SQL warehouses for reporting and BI, sold by the big clouds and long-standing warehouse vendors.
- Lakehouse platforms. These query data where it lives in open formats such as Apache Iceberg, often without copying it into a warehouse first. One vendor here is built on Trino, the open source query engine.
- OLAP engines. Built for fast, real-time analytics on huge event tables, often open source at the core.
- Small-team warehouses. One option here is built on DuckDB and aimed at data teams, engineers and founders who don't need an enterprise platform.
Questions to settle before you migrate off Snowflake
- Which cloud are you on? A native warehouse from your cloud provider is simpler to connect.
- Do you want open formats? If you want to avoid lock-in, look for Iceberg support and engines that read it.
- How fresh does data need to be? Real-time dashboards point to an OLAP engine; nightly reports don't.
- Where must data live? Some vendors run in your own cloud account or on-premises for residency rules.
- What breaks in the move? List your pipelines, transformations, permissions and BI connections before you plan the switch.
Pipelines are usually the hardest part of a warehouse move. My guide to ETL tools covers how data gets in.
Do you make a data warehouse or lakehouse platform? Tool makers can ask to be considered for a featured place on this list.
My plain advice on choosing a Snowflake alternative
Decide the architecture before the vendor. If your team mainly runs SQL reports on one cloud, that cloud's own warehouse is the simplest swap. If you want open formats and less lock-in, look at the lakehouse platforms and test them on your own Iceberg tables. If speed on huge event data is the problem, trial an OLAP engine on one dashboard. And if you're a small team, a lightweight warehouse may cover everything you need.
Once data moves, you'll want to watch it. My list of data observability tools covers that, and my roundup of data integration tools covers loading it.
Want your tool on this list? Featured spots and reviews here are paid partnerships. Here's how to partner with me.
Frequently asked questions
What's the difference between a data warehouse and a lakehouse?
A warehouse stores data in its own managed format for fast SQL. A lakehouse queries data kept in open formats such as Apache Iceberg in cloud storage, so several engines can use the same tables.
Is there an open source alternative to Snowflake?
Yes. One OLAP database on this list is open source, and several lakehouse platforms build on open source projects such as Trino, Apache Iceberg and Apache Arrow.
Which Snowflake alternative suits real-time analytics?
An OLAP engine built for real-time queries on large event tables is the usual fit, rather than a general-purpose warehouse.
Do small teams need an enterprise data warehouse?
Often not. Lighter cloud warehouses, such as one built on DuckDB, cover reporting and app analytics for small teams without enterprise setup.
How hard is it to migrate off Snowflake?
The SQL usually moves fastest. Pipelines, transformations, permissions and BI connections take the most work, so list them all before you set a date.
