How we make this list: we compare pricing pages, product documentation and public user reviews. Ratings come from G2, Capterra or Trustpilot, with the date we checked them.
Key takeaways
- Snowflake is the best multi-cloud warehouse, with per-second compute at $2.00 per credit and storage near $23 per TB a month.
- Amazon Redshift suits AWS-native teams, with serverless pricing from $1.50 per hour and provisioned clusters for steady workloads.
- Databricks SQL unifies SQL and machine learning on one lakehouse, with Classic from $0.22 per DBU.
- Microsoft Fabric is the cheapest option for a typical BI workload in recent benchmarks, near $323 a month for a standard dashboard load.
- ClickHouse is the best performance-per-dollar engine, with a free open-source edition and Cloud from $53 a month.
Quick comparison
| Tool | Best for | Starting price | Free plan |
|---|
 Snowflake | Multi-cloud warehouse | $2.00 per credit | Free trial |
 Amazon Redshift | AWS-native analytics | $1.50 per hour | Free trial |
 Databricks SQL | Lakehouse plus ML | $0.22 per DBU | Free trial |
 Microsoft Fabric | Microsoft and Power BI teams | See website | Free trial |
 ClickHouse | Performance per dollar | $0 | Yes |
 Amazon Athena | Serverless S3 queries | $5.00 per TB scanned | Free trial |
 Firebolt | Customer-facing analytics | See website | Free trial |
 DuckDB | Local and embedded analytics | $0 | Yes |
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The best Google BigQuery alternatives
#1Snowflake
Best for: Multi-cloud warehouse4.6/5 on
G2 (762 reviews, checked Oct 2026)
Visit snowflake.com
Starting price$2.00 per credit
Free planFree trial
Snowflake is the best multi-cloud warehouse, running on AWS, Azure and Google Cloud with per-second virtual warehouses that auto-suspend after 60 seconds of inactivity. Compute costs $2.00 per credit on Standard, with storage near $23 per TB a month on AWS US East, and data sharing lets organizations share live data with partners without copying it. That multi-cloud reach and sharing model are why enterprises standardize on Snowflake.
Idle costs appear without auto-suspend tuning, and on a benchmark BI workload of 10 TB stored and 40 TB scanned a month, Snowflake Standard totaled $870 a month against $323 for Microsoft Fabric. For a team that needs cross-cloud deployment and governed data sharing, Snowflake remains the benchmark warehouse.
What we like- Multi-cloud on AWS, Azure and Google Cloud
- Per-second billing with auto-suspend
- Strong data sharing
Watch out for- Idle costs without auto-suspend tuning
- 2.7 times pricier than Fabric on a benchmark BI workload
#2Amazon Redshift
Best for: AWS-native analytics4.3/5 on
G2 (404 reviews, checked Oct 2026)
Visit aws.amazon.com
Starting price$1.50 per hour
Free planFree trial
Amazon Redshift suits AWS-native teams, with serverless pricing from $1.50 per hour and provisioned RA3 clusters for steady workloads. Serverless charges per RPU-hour with a 60-second minimum, so sporadic workloads pay only for what they use, while reserved nodes cut steady-workload costs by up to 75 percent. Integration with S3, Glue and the wider AWS stack keeps data movement inside one cloud.
On a benchmark BI workload, Redshift Serverless totaled $1,200 a month and provisioned RA3 reached $1,826, the highest among major engines, because capacity-based billing charges for held resources rather than bytes read. For an AWS-locked team with steady dashboards, reserved provisioned clusters are the economical choice.
What we like- Deep AWS integration
- Serverless and provisioned options
- Reserved nodes cut steady costs
Watch out for- Serverless totals highest among major engines on benchmark workloads
- Provisioned clusters bill 24/7
Starting price$0.22 per DBU
Free planFree trial
Databricks SQL unifies SQL analytics and machine learning on one lakehouse, so teams query, transform and train models on the same Delta Lake data without moving it between systems. Pricing runs from $0.22 per DBU for SQL Classic, $0.55 for Pro and $0.70 for Serverless, which includes cloud instance cost. That unified platform is why ML-heavy teams choose Databricks over a pure warehouse.
On a benchmark BI workload, Databricks SQL Serverless totaled $1,126 a month, well above Fabric or BigQuery on-demand, because DBU plus compute pricing stacks up for pure BI work. For a team that runs SQL and ML together, Databricks' single platform outweighs the BI-only premium.
What we like- SQL plus ML on one platform
- Serverless and classic options
- Strong governance
Watch out for- Serverless totals high on benchmark workloads
- DBU pricing is confusing at first
#4Microsoft Fabric
Best for: Microsoft and Power BI teams4.6/5 on
G2 (47 reviews, checked Oct 2026)
Visit microsoft.com
Starting priceSee website
Free planFree trial
Microsoft Fabric is the cheapest option for a typical BI workload in recent benchmarks, totaling $323 a month for 10 TB stored, 40 TB scanned and 160 hours of active compute, against $421 for BigQuery on-demand and $870 for Snowflake. Capacity-based pricing means the bill reflects reserved capacity rather than bytes read, and native Power BI integration keeps dashboards inside the same platform.
Capacity licensing is complex, with tiers and SKUs that take effort to size correctly, and Fabric runs as an Azure SaaS only. For a Microsoft and Power BI team, Fabric's benchmark-leading cost and native integration make it the best BigQuery alternative.
What we like- Cheapest benchmark BI workload
- Capacity pricing
- Native Power BI integration
Watch out for- Capacity licensing is complex
- Azure-only SaaS deployment
Starting price$0
Free planYes
ClickHouse is the best performance-per-dollar engine, with a free open-source edition and Cloud from $53 a month. Its columnar OLAP design delivers fast analytical queries on events, logs and dashboards: in a 1-billion-row benchmark, ClickHouse Cloud finished in about 23 seconds at roughly $0.67 per query, the fastest and cheapest of the engines tested. That speed suits real-time dashboards and customer-facing analytics.
Self-hosting needs operational skill for clustering, replication and upgrades, and governance trails Snowflake's enterprise controls. For a team that wants maximum query speed per dollar and can run open-source infrastructure, ClickHouse is unmatched.
What we like- Fastest columnar OLAP for events and logs
- Free open source
- Cloud from $53 a month
Watch out for- Operational skill needed self-hosted
- Less mature governance than Snowflake
Starting price$5.00 per TB scanned
Free planFree trial
Amazon Athena suits teams that already store data in S3 and want serverless SQL without managing a warehouse. Queries run directly against S3 files, billing $5.00 per TB scanned, with no clusters to provision and no idle cost. On a benchmark BI workload, Athena totaled $430 a month, close to BigQuery on-demand's $421.
Athena has no storage layer of its own, so performance depends on file formats and partitioning, and unoptimized scans that read whole tables get expensive fast. For an AWS team with well-partitioned S3 data and ad-hoc query needs, Athena is the simplest serverless option.
What we like- Serverless SQL on S3 data
- No clusters to manage
- Pay only for data scanned
Watch out for- No storage layer of its own
- Costs grow with unoptimized scans
#7Firebolt
Best for: Customer-facing analytics4.5/5 on
G2 (14 reviews, checked Oct 2026)
Visit firebolt.io
Starting priceSee website
Free planFree trial
Firebolt is a specialist engine built for sub-second queries in customer-facing applications, where dashboards must respond in milliseconds under high concurrency. Engine-based pay-per-use pricing means teams pay for the engines they run rather than a warehouse cluster, which fits bursty, user-facing workloads better than capacity billing. That latency focus is why product teams embed Firebolt behind customer dashboards.
Pricing is quote-based, and the ecosystem is narrower than Snowflake's or BigQuery's, with fewer native integrations. For a team whose analytics face customers directly and need millisecond response, Firebolt's specialist design beats a general warehouse.
What we like- Sub-second queries for customer-facing apps
- Engine-based pay-per-use
- Low latency
Watch out for- Quote-based pricing
- Narrower ecosystem than Snowflake or BigQuery
Starting price$0
Free planYes
DuckDB is a free open-source embedded analytics database that runs locally or inside applications, making it perfect for data science notebooks, local analytics and development workflows. It reads Parquet, CSV and JSON directly, runs fast analytical SQL without a server, and costs nothing. For a single analyst or a developer testing queries before running them on a warehouse, DuckDB is the fastest feedback loop available.
DuckDB is not an enterprise multi-user replacement: it is single-node, so it cannot serve hundreds of concurrent dashboard users like Snowflake or BigQuery. For local and embedded workloads, though, it is the best free tool on this list.
What we like- Free and open source
- Runs locally or embedded
- Excellent for development workflows
Watch out for- Not an enterprise multi-user replacement
- Single-node limits at scale
How we chose
We compared data warehouses on compute model, storage cost, idle cost, multi-cloud reach, governance and pricing transparency. We used vendor pricing pages and recent benchmark guides for rates, and we favored tools with published prices where available. We did not claim hands-on testing. Instead we weighed what each engine charges for the same workload, how it handles idle time, and what it costs per month, so data teams can match an engine to their workload shape. Where a vendor publishes no price, as with Fabric capacity and Firebolt, we used "See website" rather than guessing.
Why the compute model matters
The compute model determines more than 70 percent of a warehouse bill, and it is the variable most comparison articles gloss over. BigQuery on-demand charges per TB scanned, with no compute provisioning and zero cost when idle, which suits unpredictable ad-hoc workloads. Snowflake charges per second for warehouse capacity with auto-suspend, which suits predictable BI with idle gaps. Redshift provisioned charges for the full cluster 24/7 unless stopped, which suits steady workloads with reserved pricing.
For the same benchmark workload, the gap between the cheapest and priciest engine exceeded 8 times: Fabric at $323 a month against Synapse Dedicated SQL Pool at $2,624. Before choosing, model your own workload: monthly data scanned, storage size and active compute hours. A warehouse that is cheapest for steady dashboards can be the priciest for bursty ad-hoc queries, and vice versa. Run a proof of concept on your real queries before committing, since benchmark numbers never match a specific workload exactly.
Frequently asked questions
What is the cheapest BigQuery alternative?
For a typical BI workload, Microsoft Fabric was cheapest in recent benchmarks at $323 a month, against $421 for BigQuery on-demand. For ad-hoc S3 queries, Athena at $5.00 per TB scanned is close, and DuckDB is free for local work.
Is Snowflake cheaper than BigQuery?
It depends on the workload. Snowflake Standard totaled $870 a month on a benchmark BI workload against $421 for BigQuery on-demand, but Snowflake can be cheaper for predictable workloads with auto-suspend tuning and reserved capacity.
Should I choose a warehouse or a lakehouse?
Choose a warehouse such as Snowflake or Redshift for governed BI with predictable queries. Choose a lakehouse such as Databricks for SQL plus machine learning on the same data, especially with unstructured or streaming data.
Can I run analytics without a cloud warehouse?
Yes. DuckDB runs locally for free and handles single-analyst workloads well, while ClickHouse open source runs on your own servers for team dashboards. Cloud warehouses become necessary at multi-user scale with governance needs.
How do I estimate my warehouse bill?
Model three numbers: data stored per month, data scanned or compute hours per month, and idle time. Then apply each vendor's unit price to the same workload, since list prices alone hide the effect of different billing models. Set billing alerts at 50 and 80 percent of budget, so a runaway query surfaces before the invoice does. Review the largest queries monthly, since one unoptimized scan often accounts for most of the bill. Partitioning and clustering tables usually cut scan costs more than any pricing negotiation. Start with the tables your dashboards query most. Small optimizations compound quickly into large monthly savings.
Sources we checked (8)
- https://www.snowflake.com
- https://aws.amazon.com/redshift/
- https://www.databricks.com
- https://www.microsoft.com/microsoft-fabric
- https://clickhouse.com
- https://aws.amazon.com/athena/
- https://www.firebolt.io
- https://duckdb.org
Is your product missing or out of date?
We review this list regularly. Vendors can request a listing, send updated pricing or ask about featured placement.
Shihab Mia · Founder, Rankite
Shihab has 5+ years in B2B and SaaS SEO. He writes Rankite's software buying guides from pricing pages, documentation and public user reviews. More about Shihab.