Snowflake alternatives: where to go based on your cloud, and how to get out cleanly
Six warehouses covered in depth, one cost comparison on the same workload, and an exit plan that starts with your contract.
The short answer: BigQuery if you already run on Google Cloud or your queries come in bursts, Redshift Serverless if the rest of your stack lives on AWS, Microsoft Fabric if the company runs on Power BI, Databricks SQL if Spark and machine learning are a big part of the work, ClickHouse Cloud for real-time dashboards over billions of events, and MotherDuck if your data fits in a few hundred GB. One warning first: plenty of Snowflake bills shrink with three settings, and prepaid capacity doesn't come back as a refund. We compared all six and pulled their prices from vendor rate cards in 2026, in US dollars and US East regions where published.
The ranking is editorial: a sponsored spot is always labeled on its card, and no affiliate link changes a rating.
Why teams leave Snowflake, even though it works
Snowflake is still the easiest warehouse to run, and nothing else matches its ecosystem of connectors, data sharing and marketplace. People rarely leave over quality. They leave because nobody can say what next month will cost. Here are the six reasons that keep showing up in forums and reviews.
You can't forecast the bill
There's no monthly plan. You buy compute credits and storage, and every warehouse size doubles the burn rate: X-Small uses 1 credit an hour, Small 2, Medium 4. In AWS US East a credit costs $2.00 on Standard and $3.00 on Enterprise. In review sites, cost predictability is the top complaint, ahead of anything about speed.
Every resume costs at least a minute
Billing is per second, with a 60-second minimum each time a warehouse starts. A BI tool that refreshes every couple of minutes keeps a warehouse awake all day. Add the test warehouses nobody suspended, and you've found the usual reason a bill doubles.
Prepaid capacity locks you in
You can buy on demand or as prepaid capacity over one or more years. Capacity gets you a better rate, but credits left at the end of the term are usually lost unless you negotiate a rollover, and rollovers tend to come with a renewal at the same amount or higher. The time to leave is the end of the term, not the week the invoice hurts.
You pay Snowflake to read your own data
One Hacker News commenter put it bluntly: "The trap you end up in is you have to pay snowflake to access your data." Every read runs on a warehouse. During a migration you pay both vendors, and another commenter noted that exporting a handful of terabytes can take hours.
A single pull request can cost real money
One engineer on Hacker News described a single pull request that "blew up into a $50k Snowflake bill." That's an outlier, but it shows the model: nothing stops a bad query or an oversized warehouse until someone sets resource monitors.
The company is consolidating on another cloud
A lot of exits aren't technical. Leadership standardizes on Microsoft 365 and Power BI, or moves everything to Google Cloud, and the warehouse follows. Then the real question is which option plugs into what you already pay for.
You're leaving because… go with…
Start with what you already have: your cloud, your BI tool, your data size. A warehouse in the same cloud as your apps saves you transfer fees and a second contract.
Nothing to size or suspend, first TiB of queries free each month, official Snowflake SQL translator.
The rest of your stack runs on AWSRedshift ServerlessPer-second billing, $300 trial credit good for 90 days.
Your company runs on Power BI and Microsoft 365Microsoft FabricFlat capacity pricing, Power BI built in, free capacity trial.
You also do Spark and machine learningDatabricks SQLSQL, notebooks and models on one platform, 14-day free trial.
Your real-time dashboards read billions of eventsClickHouse CloudVery fast column store, $300 in credits for 30 days.
Your data fits in a few hundred GBMotherDuckDuckDB in the cloud, free Lite plan.
Snowflake alternatives, one by one
Each card covers why you'd move to the tool, who it fits, who it doesn't, its catch, how to migrate from Snowflake, and what it costs. Ratings and prices match our data warehouse ranking. Snowflake scores 4.3 out of 5 there, just behind BigQuery, so leaving isn't obvious. It's a math problem.
BigQuery: when you never want to size a warehouse again
Rating 4.4Why move to BigQuery. There's no warehouse size and no auto-suspend to tune. You run a query, Google runs it, you pay for bytes scanned: $6.25 per TiB, with the first TiB free every month. If you're tired of babysitting warehouses that never go to sleep, this is the biggest change you can make.
Who it fits. Teams already on Google Cloud, and teams whose queries come in waves (a morning report, a few ad hoc analyses).
Who it doesn't. Teams whose dashboards scan full tables all day. Scanned bytes drive the bill, so they'll end up on reserved slots (Enterprise, $0.06 per slot-hour in the US).
The catch. Cost depends on how your tables are laid out, and partitioning and clustering don't carry over from Snowflake. You configure them by hand, table by table.
How to migrate. Google publishes a Snowflake migration guide: an assessment of your account, SQL translators from Snowflake to GoogleSQL (Google tells you to review every translated query), and a data validation tool. The guide flags one concrete gotcha: Snowflake lets you build a role hierarchy, IAM doesn't (it relies on a resource hierarchy), so plan to remap permissions.
- Queries
- $6.25 per TiB scanned, 1 TiB free a month
- Storage
- about $0.023 per GiB-month
- Migration
- official SQL translator
- Catch
- cost tracks bytes scanned
Redshift Serverless: when everything else is on AWS
Rating 3.9Why move to Redshift. If your apps, your S3 data and your tooling already live on AWS, Redshift Serverless keeps it all on one bill. Like Snowflake, it bills per second with a 60-second minimum and stops when nobody queries.
Who it fits. AWS teams with a few TB who'd rather keep spend inside their existing AWS agreement.
Who it doesn't. Teams that want zero tuning. Redshift asks for more care on table design than Snowflake does.
The catch. The minimum base is 4 RPUs, so it starts at $1.50 an hour ($0.375 per RPU-hour in US East). On the same workload as a Snowflake X-Small running 176 hours a month, that's 4 × $0.375 × 176 = $264, against $352 on Snowflake Standard in US East. That math only holds if your load fits in the 4 RPU base.
How to migrate. Unloading Parquet to an S3 bucket in the same region costs nothing on the Snowflake side. AWS gives you a $300 credit that expires after 90 days, which is enough for a real pilot.
- Compute
- $0.375 per RPU-hour (US East)
- Minimum
- 4 RPUs, $1.50 an hour
- Trial
- $300 credit for 90 days
- Catch
- table design needs care
Microsoft Fabric: when the company lives in Power BI
Rating 3.7Why move to Fabric. Fabric puts the warehouse, pipelines and Power BI under one fixed-price capacity. No credits running away: an F2 capacity runs about $262.80 a month left on 24/7 in East US (our math), and a one- or three-year reservation saves about 41%.
Who it fits. Companies already on Microsoft 365 and Power BI that want one contract and a flat bill.
Who it doesn't. Teams on AWS or Google Cloud, or products serving dashboards to thousands of outside customers.
The catch. Below F64, everyone who views a report needs a Power BI Pro license. From F64 up, they don't. A small capacity looks cheap on the Fabric invoice and less cheap on the total.
How to migrate. Unload Parquet to Azure storage in your region, then load it into OneLake. Review every query and every role on the way. Use the free capacity trial on a real report before you size anything; billing is per minute.
- F2 capacity
- about $262.80 a month (East US)
- Reservation
- saves about 41%
- Trial
- free capacity trial
- Catch
- Power BI Pro needed below F64
Databricks SQL: when data science is a big part of the job
Rating 4.1Why move to Databricks. If your team already runs Python, Spark and ML next to Snowflake, Databricks brings SQL, notebooks and model training into one platform. One tool instead of two.
Who it fits. Data teams mixing engineering, data science and BI, with data measured in terabytes.
Who it doesn't. A small team doing mostly SQL and dashboards. Databricks will feel heavier than Snowflake for little gain.
The catch. Outside Serverless you get two bills: Databricks DBUs plus your cloud's VMs. On Azure Databricks Premium (France Central, the region in our ranking), a DBU-hour costs $0.22 on SQL Classic, $0.72 on SQL Pro and $0.91 on Serverless. Our guide to switching from Databricks covers the reverse trip, because teams move in both directions.
How to migrate. Unload tables to Parquet in your own storage, then load them as Delta tables. Review every query: no SQL dialect copies over unchanged. Start with the 14-day free trial on a single data domain.
- SQL Classic
- $0.22 per DBU-hour
- Serverless
- $0.91 per DBU-hour
- Trial
- 14 days
- Catch
- cloud VMs billed on top
ClickHouse Cloud: when dashboards have to answer instantly
Rating 4.0Why move to ClickHouse. It's a column store built to aggregate billions of rows in under a second. ClickHouse makes a specific claim: a Snowflake warehouse handles 8 concurrent queries by default, while a ClickHouse node takes up to 1,000 (the vendor's number). For customer-facing analytics, that gap shows.
Who it fits. SaaS products showing analytics to their users, and teams tracking events in real time (logs, clicks, sensors).
Who it doesn't. A classic BI team with lots of complex joins across business tables. ClickHouse makes you rethink the data model.
The catch. On Enterprise, a compute unit (8 GiB RAM, 2 vCPU) costs $0.39030 an hour in AWS us-east-1. A unit isn't the same as a Snowflake X-Small, so don't compare hourly prices without a pilot. The first months often cost more than planned while the team learns the engine.
How to migrate. ClickHouse publishes a Snowflake migration guide built around a Parquet unload to object storage. Run the pilot on part of your data with the $300 in credits it gives for 30 days, no credit card required.
- Compute
- $0.39030 per unit-hour (Enterprise, us-east-1)
- Trial
- $300 for 30 days, no card
- Concurrency
- up to 1,000 queries per node (vendor)
- Catch
- data model needs rethinking
MotherDuck: when your data is smaller than your bill
Rating 3.9Why move to MotherDuck. Plenty of companies pay for a distributed warehouse to hold 100 or 300 GB. MotherDuck runs DuckDB in the cloud on a single node, billed per second. Lite is free (3 users, 10 GB, 10 compute hours a month), and Business is $250 a month per organization plus usage. A Hacker News commenter summed up the pitch: "DuckDB has the performance of Snowflake for a fraction of the cost." That holds at small sizes, not at every size.
Who it fits. Startups and small companies with a few hundred GB and a small data team.
Who it doesn't. Tens of TB, or spikes of hundreds of concurrent users.
The catch. You pick the region when you create the organization and can't change it later. Storage is $0.04 per GB-month, which is more per TB than Snowflake.
How to migrate. Unload to Parquet, then load the files. On the SQL side, Snowflake uppercases identifiers and DuckDB lowercases them; VARIANT becomes JSON, ARRAY becomes LIST, OBJECT becomes STRUCT, and there are no TRANSIENT tables. A tool like SQLGlot converts most of the syntax, but expect about a quarter of your transformations to need hand fixes.
- Lite
- free (10 GB, 10 compute hours)
- Business
- $250 a month + usage
- Trial
- 7 days, no card
- Catch
- single node
Six alternatives on the same workload
The table shows each tool's billing unit and entry price, then what changes coming from Snowflake. Keep one reference point: a Snowflake X-Small running 8 hours a day, 22 days a month, burns 176 credits. That's $352 on Standard and $528 on Enterprise in AWS US East.
| Billing and entry price | What changes coming from Snowflake | |
|---|---|---|
| SnowflakeWhere you start | Per-second credits, 60 s minimum; $2.00 a credit on Standard (US East); storage $23 per TB-month | Easy to run, hard to forecast |
| Google BigQueryNothing to tune | $6.25 per TiB scanned, first TiB free each month | No warehouses to suspend; partitioning to redo |
| Redshift ServerlessAWS shops | $0.375 per RPU-hour (US East), 4 RPU minimum | Everything on AWS; table design needs care |
| Microsoft FabricMicrosoft shops | F2 about $262.80 a month always on (East US, our math) | Flat bill; Power BI Pro licenses below F64 |
| Databricks SQLSQL plus ML | $0.22 to $0.91 per DBU-hour + VMs outside Serverless | One platform for SQL and data science; two bills |
| ClickHouse CloudReal time | $0.39030 per unit-hour (Enterprise, us-east-1) | Much faster dashboards; data model to rethink |
| MotherDuckSmall data | Lite free; Business $250 a month + usage | Far cheaper; single node |
Pre-tax prices in US dollars as published by vendors in 2026 and matched to our data warehouse ranking. A ClickHouse unit, a Redshift RPU and a Snowflake credit don't buy the same power: only a pilot on your own volume gives you a real number.
Leaving Snowflake in eight steps
The idea: work back from the contract end date, tune first so you know your real baseline, then run the new platform next to Snowflake until the numbers match. Expect a few weeks for a small SQL team and several months for hundreds of models and tasks.
Pull out the contract
FirstWrite down the term end, the auto-renewal notice period, your remaining credit balance, and any rollover clause. Unused prepaid credits are usually forfeited at term end, so aim to shut down on that date and burn the balance during the parallel run.
If you need to renew to cover the transition, push for a shorter commitment instead of an automatic renewal.
- Time
- one hour
- Output
- a target shutdown date
Tune for a week before you compare
Week 1Set a short auto-suspend on every warehouse, add resource monitors (credit caps that alert or suspend), and drop oversized warehouses to X-Small. Lean on the result cache for dashboards that rerun the same query.
Now you have your real baseline. Sometimes it's low enough to stay. If not, compare alternatives against that number, not the inflated one.
- Time
- one week
- Output
- tuned monthly cost
Take inventory
Week 2Query ACCOUNT_USAGE to see which warehouses burn credits and ACCESS_HISTORY to see which tables people actually read. List data shares, Snowpipe, scheduled tasks, stored procedures and roles too.
Tables nobody has read in months don't migrate. Archive them.
- Time
- two to three days
- Output
- tables and tasks ranked by cost
Pick the target by cloud and workload
Week 2Go back to the "you're leaving because" table above. The cloud your apps already run on matters more than a few cents an hour: it saves transfer fees and a new vendor agreement.
If you rely on secure data sharing with partners, check they can read from you elsewhere. That's often what keeps teams on Snowflake.
- Time
- two days
- Output
- one target, one pilot
Unload to Parquet in the same region
Week 3Use COPY INTO to a bucket in the same region and the same cloud as your Snowflake account: that transfer is free. Another region or another cloud gets billed.
Cast TIMESTAMP_TZ and TIMESTAMP_LTZ columns to TIMESTAMP_NTZ before unloading, and raise the file size: the 16 MB default is too small for most engines, so aim for 250 MB to 1 GB. Time Travel doesn't come with you, so export any history you need.
- Cost
- free within the same region
- Risk
- timestamp time zones
Translate SQL and permissions
Weeks 3 to 5Run your queries and models through a translator (BigQuery's, or SQLGlot), then review them one by one. The same traps come back: identifier case, functions the target doesn't have, semi-structured types.
Then map Snowflake roles to the target's permission model, by group rather than by person.
- Time
- the longest step
- Risk
- a sensitive table open to everyone
Run both side by side
One billing cycleRun both platforms for at least one full billing cycle. Compare row counts and monthly totals on your key tables, then repoint BI from the least critical reports to the most critical.
This stretch means two bills, which makes it the right time to burn your remaining credits.
- Time
- at least a month
- Output
- zero gaps in the numbers
Freeze, unload one last time, shut down
At term endFreeze writes in Snowflake, run the final unload, check totals one last time. Suspend and drop warehouses, stop Snowpipe and tasks, revoke service users.
Keep that final Parquet unload in your own storage. It's your archive, and any engine can read it.
- Time
- one day
- Output
- account closed at term end
Is your tool missing from this page? Email us: hello@hackceleration.com
What makes a Snowflake exit go wrong
Failed exits rarely come down to the warehouse you picked. They come from six mistakes that show up again and again in team write-ups and migration guides.
Leaving mid-term
Walking away in the middle of a prepaid term means paying for credits nobody will use. Time the cutover to the contract end.
Comparing the untuned bill
A Medium warehouse that never sleeps costs four times a well-tuned X-Small. Compare the tuned baseline, or you'll swap tools to fix a settings problem that follows you anyway.
Unloading across regions
A COPY INTO to a bucket in another region or cloud gets billed. Create the bucket next to the account first, then move files with the target's own tools.
Forgetting what doesn't move
Time Travel, secure data sharing and the marketplace don't have a direct equivalent everywhere. List them before you choose.
Trusting the SQL translator
Even Google tells you to review every translated query. Compare results on real data, not just syntax.
Cutting over too early
Without a full parallel cycle, a wrong month-end close lands at the worst time. Keep Snowflake until totals match.
- Term end, notice period and credit balance written down
- Auto-suspend and resource monitors in place
- Tuned monthly cost measured
- Warehouses and tables ranked by cost (ACCOUNT_USAGE, ACCESS_HISTORY)
- Data shares and Time Travel needs listed
- Target picked by cloud and workload
- Parquet unloaded in the same region, timestamps as NTZ
- SQL translated and reviewed, roles remapped
- One full parallel cycle, totals compared
- Warehouses, Snowpipe and tasks stopped at term end
Snowflake alternatives: common questions
What is the cheapest alternative to Snowflake?
For small data, MotherDuck: Lite is free up to 10 GB and 10 compute hours a month, and Business starts at $250 a month plus usage. For bursty queries, BigQuery's first TiB scanned each month is free. On AWS, Redshift Serverless starts at $1.50 an hour. The cheapest one depends on your workload, so run a pilot before you sign.
Is there an open source alternative to Snowflake?
Yes. DuckDB and ClickHouse are open source, and Firebolt publishes Firebolt Core, a free version you host yourself. The trade-off is that you run the servers. MotherDuck and ClickHouse Cloud sell managed versions if you don't want that job.
Snowflake vs Databricks: which costs less?
It depends on the work. For SQL and BI, Snowflake is usually easier to keep under control: an X-Small burns 1 credit an hour ($2.00 on Standard in US East) and suspends itself. For heavy Spark and ML, Databricks is often the better fit. Our guide to switching from Databricks covers the other direction.
What is the Microsoft alternative to Snowflake?
Microsoft Fabric. It replaces Azure Synapse in Microsoft's lineup and bundles the warehouse with Power BI under one capacity. An F2 runs about $262.80 a month always on in East US. Remember the Power BI Pro licenses for report viewers below F64.
What happens to unused Snowflake credits if I leave?
They're usually forfeited at the end of the term. You can sometimes negotiate a rollover, most often in exchange for renewing at the same amount or more. That's why you time the exit to the term end and burn the balance during the parallel run.
How long does a Snowflake migration take?
A few weeks for a small team doing mostly SQL, several months for hundreds of models and tasks. The parallel run alone should cover at least one full billing cycle. SQL translation and role mapping are the slowest parts.
How do I export data from Snowflake without egress fees?
Use
COPY INTOto write Parquet to a bucket in the same region and cloud as your account; Snowflake doesn't charge for that transfer. Cross-region or cross-cloud unloads are billed. Cast time-zone timestamps toTIMESTAMP_NTZfirst.Should I leave Snowflake or cut the bill first?
Cut the bill first. A short auto-suspend, resource monitors and X-Small warehouses fix a lot of invoices. If the tuned cost is still too high, or the company is changing clouds, leaving makes sense. If ingestion or BI is moving too, our guides to switching from Fivetran, switching from Power BI and switching from Looker Studio cover those moves.
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