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Snowflake Alternatives

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Verdict

Snowflake is the best general-purpose data warehouse for teams that need predictable performance across mixed workloads on AWS, Azure, and GCP from one platform. The catch is consumption pricing that punishes inefficient queries; bills routinely grow 35 to 50 percent year over year. Where alternatives win: BigQuery is cheaper for occasional querying with no compute to manage, Redshift fits AWS-heavy stacks tightly, Databricks SQL pairs lakehouse and ML in one platform, MotherDuck makes single-team analytics work on DuckDB economics, and ClickHouse Cloud beats Snowflake for real-time aggregation workloads.

By Subrupt EditorialPublished Reviewed

A typical Snowflake bill grows roughly 35 to 50 percent year over year, mostly because credit consumption tracks how teams write queries, not how much data they actually need. Teams that do not enforce auto-suspend or that misuse warehouse sizing routinely double their bill within six months. Snowflake the product is excellent; Snowflake the line item is the cost most teams want to flatten.

Snowflake's value is the multi-cloud architecture: same SQL, same security model, same platform across AWS, Azure, and GCP. Standard at $2 per credit covers most starter workloads; Enterprise at $3 unlocks 90-day time travel, multi-cluster warehouses, and dynamic data masking. Storage runs roughly $23 per TB per month on-demand, $19 with a contract. The trade-offs sharpen above $50K per year in spend, where alternatives cover similar use cases more cheaply.

Pick by your actual workload shape. Occasional analytics with no compute to manage: BigQuery. AWS-heavy stack with predictable usage: Redshift. Lakehouse plus ML in one platform: Databricks SQL. Solo analyst or small team on data under a few TB: MotherDuck. Real-time aggregation on event streams: ClickHouse Cloud.

Affiliate disclosure: Subrupt earns a commission when you switch to a service through our recommendation links. This never changes the price you pay. We only recommend services where there's a real cost or feature advantage for you, and our picks are based on the data on this page, not on which programs pay the most.

Quick pick by use case

If you only have thirty seconds, find your situation below and skip to that pick.

If your queries are intermittent and you don't want to manage computeGoogle BigQueryBigQuery on-demand bills $6.25 per TB scanned with zero idle cost between queries.If your stack is AWS-heavy and your workload is predictableAmazon RedshiftRedshift Serverless or RA3 provisioned fits AWS-tight integration; reserved instances cut about 50 percent.If you need lakehouse plus ML training in one platformDatabricks SQLDatabricks SQL Pro at $0.55 per DBU shares storage with ML pipelines and Delta tables.If you are a solo analyst or small team and your data fits in a few TBMotherDuckMotherDuck Standard at $25 per user runs DuckDB hybrid local-cloud at sharply lower cost.If you run real-time aggregations on event streamsClickHouse CloudClickHouse Cloud Production from $0.71 per compute hour beats Snowflake on OLAP-heavy aggregations.

At a glance: Snowflake alternatives

Quick comparison across pricing floor, best fit, and switching effort. Tap a row to jump to the full pick.

Our picks for Snowflake alternatives

#1

Google BigQuery

Free tierMedium switching effort

Best for occasional analytics with no compute management

Try Google BigQuery

BigQuery's on-demand model bills $6.25 per TB scanned with zero ongoing cost when nothing runs. For teams whose query volume is intermittent (weekly dashboards, ad-hoc analysis, monthly reports), this beats Snowflake's per-credit-hour model. The 1 TB free monthly query budget is generous; 10 GB free storage covers spec work. Heavy users move to Editions (slot-hour capacity-based pricing) for predictability above a few TB scanned per day.

Strengths

  • +1 TB free queries per month, no card required
  • +Zero compute cost when idle
  • +Native GCP and Looker integration
  • +Editions for predictable capacity pricing

Trade-offs

  • −Cold-cache penalty on first query
  • −Per-TB scanning model can shock users on wide tables
  • −Less mature in-warehouse Python than Snowpark
Free
1 TB queries/mo, 10 GB storage
On-demand
$6.25/TB scanned
Editions Standard
$0.04/slot-hour
Storage
$20/TB/mo active
Migration steps
  1. Sign up for GCP free tier and create a BigQuery project.
  2. Migrate schemas via dbt or BigQuery Migration Service (Snowflake adapter).
  3. Run parallel for 2-4 weeks and compare query cost on your top dashboards.
  4. Cut over once query parity is confirmed; cancel Snowflake credits if applicable.

Not for: BigQuery is the wrong choice when your workload runs continuously with predictable concurrency; Snowflake or Redshift fit better.

#2

Amazon Redshift

Free tierHigh switching effort

Best for AWS-heavy stacks with predictable workload

Try Amazon Redshift

Redshift's value is tight AWS integration: VPC peering, IAM, S3, Glue, and Lake Formation are all native. RA3.xlplus at $3.26 per hour on-demand drops to roughly $1.65 with 1-year reserved. For teams whose data lake already lives in S3 and whose pipeline is Step Functions plus Lambda, Redshift becomes the path of least friction. Serverless (RPU-based) covers spiky workloads without explicit provisioning.

Strengths

  • +Tightest AWS integration of any warehouse
  • +Reserved instances cut on-demand cost about 50 percent
  • +Serverless option covers spiky workloads
  • +Federated queries against S3, RDS, and Aurora

Trade-offs

  • −Less polished outside AWS than Snowflake's multi-cloud
  • −Concurrency scaling adds variable cost surprises
  • −Semi-structured handling less mature than Snowflake VARIANT
Free trial
750 hrs/mo for 2 months
RA3.xlplus
$3.26/hr on-demand
RA3.4xlarge
$13.04/hr per node
Serverless
$0.375/RPU-hour
Migration steps
  1. Provision a Redshift cluster sized to expected workload.
  2. Use AWS Schema Conversion Tool or dbt for SQL portability.
  3. Stage data via S3 and COPY (or Snowpipe-equivalent unload).
  4. Run parallel for 4 weeks; compare cost and p95 latency before cutover.

Not for: Avoid Redshift when your stack is multi-cloud or non-AWS; Snowflake's portability becomes the deciding factor.

#3

Databricks SQL

Free tierHigh switching effort

Best for lakehouse plus ML training in one platform

Try Databricks SQL

Databricks SQL is the SQL surface on top of Databricks' Lakehouse: Delta tables, Photon execution engine, and shared storage with notebooks doing ML training. SQL Pro at $0.55 per DBU plus underlying cloud compute is comparable to Snowflake on a normalized basis but unlocks one platform for both BI queries and ML pipelines. For teams whose use case mixes analytics and data science, the consolidation is meaningful.

Strengths

  • +One platform for SQL and ML training
  • +Photon execution and Delta tables included
  • +Sub-10s startup on Serverless
  • +Unity Catalog for cross-workspace governance

Trade-offs

  • −DBU plus underlying compute is harder to model than Snowflake credits
  • −BI-only teams pay for ML capability they don't use
  • −Steeper learning curve outside the lakehouse pattern
Free trial
$400 credits, 14 days
SQL Classic
$0.22/DBU
SQL Pro
$0.55/DBU
Serverless
$0.70/DBU
Migration steps
  1. Provision a Databricks workspace on your cloud of choice.
  2. Migrate Snowflake tables via the JDBC connector or Spark COPY INTO.
  3. Move dashboards and Looker connections to Databricks SQL endpoints.
  4. Cut over once query latency and bill projection match production needs.

Not for: Databricks SQL is the wrong pick for BI-only teams that will not use the ML side; Snowflake or BigQuery fit better.

#4

MotherDuck

Free tierLow switching effort

Best for solo analysts or small teams on DuckDB economics

Try MotherDuck

MotherDuck is DuckDB-native cloud with hybrid execution: queries run partly on your laptop, partly in the cloud, automatically. Free covers 10 GB storage and 10 compute hours; Standard at $25 per user per month covers 100 GB and 100 hours. For data under a few TB and teams under 10 people, MotherDuck is dramatically cheaper than Snowflake at similar latency for most queries. The differentiator is real: DuckDB's SQL engine plus zero cluster overhead.

Strengths

  • +$25 per user (vs Snowflake's per-second consumption)
  • +DuckDB-native, hybrid local-cloud execution
  • +Free tier covers solo analysis at 10 GB
  • +Zero infrastructure to manage

Trade-offs

  • −Wrong shape above 5 TB of active data
  • −Smaller integration ecosystem than Snowflake
  • −Newer platform, governance features still maturing
Free
10 GB + 10 compute hrs/mo
Standard
$25/user/mo, 100 GB + 100 hrs
Business
Custom
Enterprise
On-prem hybrid
Migration steps
  1. Sign up for MotherDuck free.
  2. Connect via DuckDB CLI or the VSCode extension.
  3. Import Snowflake tables via parquet export to S3 or GCS.
  4. Validate query performance on your typical workload, then cancel Snowflake.

Not for: MotherDuck is the wrong choice for teams managing more than 5 TB of active data; Snowflake or BigQuery sized better there.

Paid plans from $25.00/mo

#5

ClickHouse Cloud

Free tierHigh switching effort

Best for real-time aggregation on event streams

Try ClickHouse Cloud

ClickHouse Cloud is the managed version of ClickHouse, the OLAP database known for sub-second aggregations on multi-TB data. Production from $0.71 per compute unit-hour plus $1 per GB storage; per-query cost on aggregation-heavy workloads (counting events, percentile calculations, time-series rollups) runs sharply lower than Snowflake's. For teams whose workload is dashboards over event streams (product analytics, observability, ad-tech), ClickHouse fits a shape Snowflake handles less efficiently.

Strengths

  • +Sub-second aggregations on multi-TB data
  • +Lower per-query cost than Snowflake on aggregation-heavy workloads
  • +Auto-pause development tier reduces dev costs
  • +Open core: ClickHouse OSS is Apache 2 licensed

Trade-offs

  • −Smaller SQL feature set than Snowflake (MERGE syntax differs)
  • −Smaller third-party tool ecosystem
  • −Less mature governance than Unity Catalog or Snowflake roles
Free trial
$300 credits, 30 days
Development
$0.21/CU-hour
Production
$0.71/CU-hour
Storage
$1/GB/mo
Migration steps
  1. Sign up for ClickHouse Cloud trial.
  2. Import Snowflake tables via S3 export and ClickHouse INSERT FROM S3.
  3. Rewrite aggregation queries; ClickHouse SQL diverges from ANSI in places.
  4. Run parallel and benchmark; cut over once dashboards match latency targets.

Not for: ClickHouse Cloud is the wrong choice for general-purpose analytics with diverse query shapes; Snowflake or BigQuery cover broader workloads better.

When to stay with Snowflake

Stay with Snowflake if your platform investment is multi-cloud, your team relies on Snowpark for in-warehouse Python, or you have applications consuming Snowflake views via marketplace integrations. The picks below pull toward different workload shapes, single-cloud commitment, or open-source alignment.

5 Alternatives to Snowflake

Google BigQueryFree tier

From $0/mo (free tier)

Switch to Google BigQuery
Amazon RedshiftFree tier

From $0/mo (free trial)

Switch to Amazon Redshift
Databricks SQLFree tier

From $0/mo (free trial)

Switch to Databricks SQL
MotherDuckFree tier

From $25.00/mo

Switch to MotherDuck
ClickHouse CloudFree tier

From $0/mo (free trial)

Switch to ClickHouse Cloud

Continue your research

Google BigQuery alternativesAmazon Redshift alternativesDatabricks SQL alternativesMotherDuck alternativesClickHouse Cloud alternatives

How we picked

Data-warehouse alternatives split along three vectors: pricing model (per-credit vs per-TB-scanned vs per-DBU vs per-engine-hour), workload shape (mixed BI vs OLAP-heavy vs lakehouse), and cloud commitment (multi-cloud vs single-cloud vs open). Picks below address each combination.

Pricing is taken from each vendor's site on the review date at us-east-1 list price. We score on total cost of ownership for a representative workload (1 TB working set, 10 active users, 30 minutes of query time per day). Reserved capacity discounts can halve costs on Redshift, Snowflake, and BigQuery Editions; we flag those where they change the answer.

Update history1 update
  • Initial published version with 5 picks.

Frequently asked questions about Snowflake alternatives

How does Snowflake's credit pricing actually compare to per-hour pricing on competitors?

One Snowflake credit equals one hour of an X-Small warehouse, scaling up by powers of 2 (Small = 2 credits/hr, Medium = 4, etc.). At Standard's $2/credit, an X-Small running an hour costs $2; Medium running an hour is $8. BigQuery on-demand bills only when queries run, so an idle warehouse costs nothing. Redshift RA3.xlplus is $3.26/hr regardless of utilization. The fairest comparison is total cost over a representative day, not per-unit pricing.

Can I migrate from Snowflake to BigQuery without rewriting all my SQL?

Most ANSI SQL ports cleanly. Snowflake-specific syntax (QUALIFY, ASOF JOIN, MATCH_RECOGNIZE, FLATTEN with VARIANT) needs rework. dbt portable models migrate with minimal change. Stored procedures in Snowflake JavaScript or SQL UDFs need full rewrite. The BigQuery Migration Service automates 80 to 90 percent of typical workloads but leaves the snowflake-specific 10 percent for manual review.

Is MotherDuck production-ready or still beta?

MotherDuck reached general availability in mid-2024. The DuckDB engine itself has been production-stable for 5+ years. The cloud platform is newer; teams using MotherDuck for production reporting do so with smaller data sizes (under 1 TB working set) and rely on DuckDB's local execution as a fallback. For mission-critical workloads above 1 TB, MotherDuck is improving but Snowflake or BigQuery have longer track records.

Does Apache Iceberg change the warehouse decision?

Yes for some teams. Iceberg lets you keep table data in your own S3, GCS, or ADLS and have multiple compute engines query it (Snowflake, BigQuery, Databricks, ClickHouse, Trino). If you adopt Iceberg, the warehouse becomes a compute layer rather than a storage lock-in, and switching warehouses gets cheaper. Snowflake supports Iceberg tables natively as of 2024; BigQuery via BigLake; Databricks via Unity Catalog.

How do I cut my Snowflake bill before deciding to switch?

Three quick wins: (1) enforce auto-suspend at 60 seconds (default is often too generous), (2) right-size warehouses (most teams over-provision; Medium handles workloads X-Small can do), (3) review the top-10 queries by credit cost monthly and refactor or materialize them. Most teams see 25 to 40 percent cost reduction from these alone, which often makes the switch question moot.

SE

About the author: Subrupt Editorial

The team behind subrupt.com. We track subscriptions, surface cheaper alternatives, and publish comparisons where the score formula is on the page so you can recompute it yourself. We do not claim 30,000 hours of testing. What we claim is live pricing from our database, a transparent composite score, and honest savings math against a category baseline.

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