How does Snowflake compute pricing compare to BigQuery and Redshift?

Direct Answer

There is no universal winner — the answer depends on workload shape, team SQL discipline, and which cloud you already live in. At small scale with bursty ad-hoc analyst queries, BigQuery on-demand wins because you pay $0 when no one queries (you only pay storage). At predictable, always-on warehouse workloads with multi-year visibility, Snowflake credits + a capacity contract win — the per-second billing on suspended warehouses plus 30-50% multi-year discounts beat list-price comparisons.

At AWS-native shops with tight Lake Formation / S3 / IAM integration, Redshift Serverless wins on data-gravity — egress alone often kills the Snowflake/BigQuery alternative. The gotchas: BigQuery on-demand can explode if a junior analyst writes SELECT * against a partitioned 50TB table; Snowflake credit consumption is opaque until you instrument warehouse-level monitoring; Redshift's RA3 vs.

Serverless vs. Legacy DC2 SKU sprawl confuses procurement. *List price approximations below — actual contract pricing varies by region, edition, commit tier, and negotiation.*

The Three Pricing Models Explained

Snowflake (credit-based)

• Compute = credits/hour × warehouse size (XS=1, S=2, M=4, L=8, XL=16, ... 4XL=128, 6XL=512), billed per-second after a 60-second minimum
• Credit price varies by edition: Standard (~$2/credit on AWS US East), Enterprise (~$3), Business Critical (~$4), VPS (negotiated)
• Multiplier by cloud region — Azure and GCP regions sometimes price 5-15% higher
• Storage billed separately (~$23/TB/month on-demand, ~$40/TB/month for capacity-purchased Time Travel + Fail-safe)
• Capacity contracts unlock 10-50% off list when you pre-purchase credits (1yr, 2yr, 3yr tiers)

BigQuery (two pricing modes)

• On-demand: ~$6.25/TB scanned (US multi-region, list) — no compute SKU at all, you pay per byte read
• Editions (capacity slots): Standard (~$0.04/slot-hr), Enterprise (~$0.06), Enterprise Plus (~$0.10) — autoscale + 1yr / 3yr commits give 20-40% off
• Storage: ~$0.02/GB/month active, ~$0.01/GB/month for partitions untouched 90+ days (auto-tier)
• Streaming inserts ~$0.01/200MB; Storage Write API is cheaper and now the default for high-throughput ingest

Redshift (two SKUs)

• RA3 nodes (provisioned): ra3.xlplus ~$1.086/hr, ra3.4xlarge ~$3.26/hr, ra3.16xlarge ~$13.04/hr (US East, list) — separates compute from managed storage (~$24/TB/mo)
• Redshift Serverless: billed per RPU-second (~$0.375/RPU-hour list in US East), 60-second minimum, 8 RPU floor — autoscales for variable workloads
• Reserved Instances on RA3 give 1yr (~30% off) or 3yr (~60% off) — Serverless does not have RIs, but commits are now negotiable per AWS reInvent 2025
• Concurrency Scaling credits — first hour/day free, then ~$1/hr per cluster

Apples-to-Apples Comparison Math

*All figures are list-price approximations for US-East regions, May 2026. Actual contract pricing varies.*

Workload 1: 5 analysts, ~50 ad-hoc queries/day, ~500GB scanned/day, 2TB stored

• Snowflake: XS warehouse ~2 hrs/day × $2 + storage ~$50/mo ≈ $170/mo
• BigQuery on-demand: ~15TB/mo scanned × $6.25 + storage $40 ≈ $135/mo
• Redshift Serverless: 8 RPU × ~3 hrs/day × $0.375 ≈ $280/mo
• *Winner: BigQuery on-demand*

Workload 2: Mid-market BI dashboard, 24/7 light read, 10TB stored

• Snowflake: S warehouse on auto-suspend, ~6 credit-hrs/day × $2 ≈ $580/mo
• BigQuery Enterprise: 100 slot baseline ~$2,900/mo (or on-demand: ~$1,500 if scans stay disciplined)
• Redshift: 1× ra3.xlplus reserved 1yr ≈ $540/mo
• *Winner: Redshift RA3 (or Snowflake if multi-cloud)*

Workload 3: Streaming ETL, 500GB/day ingest, hourly transforms, 30TB stored

• Snowflake: M warehouse 8 hrs/day × $2 × 4 credits/hr ≈ $2,200/mo + storage $700
• BigQuery: Storage Write API + 200 slots ≈ $5,800/mo + storage $600
• Redshift Serverless: 32 RPU × 8 hrs × $0.375 × 30 ≈ $2,880/mo
• *Winner: Snowflake (per-second billing on suspended warehouse helps)*

Workload 4: Enterprise ML feature engineering, 50TB scanned/wk, 200TB stored

• Snowflake: L warehouse w/ Snowpark ~$18,000/mo + storage ~$4,600
• BigQuery: Enterprise Plus 500 slots reserved ~$36,000/mo + storage $4,000
• Redshift: ra3.4xlarge × 4 nodes reserved 3yr ~$5,600/mo + RMS $4,800
• *Winner: Redshift RA3 reserved (if AWS-native)*

Workload 5: AI inference + LLM-generated SQL, 1M queries/mo via Cortex/Gemini/Bedrock

• Snowflake Cortex: charged in credits, varies wildly by model — Llama 3.1 70b ~$1.21/1M tokens out; expect $8K-25K/mo at this volume
• BigQuery ML + Gemini integration: ~$0.0025/1K tokens for Gemini 1.5 Flash, generally $3K-12K/mo
• Redshift ML (SageMaker passthrough): ~$5K-15K/mo + SageMaker endpoint costs separately
• *Winner: BigQuery (Gemini pricing is currently most aggressive)*

Hidden Costs That Bite

Snowflake gotchas

• Cloud Services compute (metadata ops) — free up to 10% of warehouse spend, then billed
• Materialized View auto-refresh consumes credits silently
• Marketplace listings can be billed in credits — Snowflake Cortex AI functions especially
• Time Travel + Fail-safe storage stacks on top of base storage (90 days × big tables = real money)
• Cross-region/cross-cloud replication: you pay egress *and* destination storage *and* replication credits
• Search Optimization Service: opt-in but easy to forget — adds 5-15% to credit bill on enabled tables

BigQuery gotchas

• Slot reservation idle time still bills — reservations are not auto-suspending like Snowflake warehouses
• Streaming inserts cost extra over batch loads; many teams forget to migrate to Storage Write API
• Materialized Views re-compute costs hit your slot capacity (or on-demand bytes)
• Data egress to non-Google clouds: $0.08-0.12/GB — kills multi-cloud architectures
• Long-term storage tier kicks in at 90 days untouched but a single SELECT bumps it back to active pricing
• BI Engine reservations are separate from query slots — easy to double-pay

Redshift gotchas

• RA3 Managed Storage (RMS) is cheap (~$24/TB) but cross-AZ traffic for replicas isn't free
• Concurrency Scaling beyond the free hour can quietly 2-3x bills during reporting peaks
• Serverless 8 RPU floor means even tiny workloads cost ~$60/mo minimum if always-on
• Spectrum queries against S3 charge $5/TB scanned — separate from Redshift compute
• DataShare consumer-side compute is billed to consumer; producers often surprised when partners complain
• Backups beyond the free retention period bill at S3 standard rates

Negotiation Levers In 2026

Snowflake (post-Sridhar Ramaswamy era, more aggressive on price)

• Multi-year capacity commits: 25-40% off list at $1M+/yr; 40-55% at $5M+
• Multi-cloud commit (AWS + Azure or AWS + GCP): adds 5-10% additional discount
• Migration credits if coming from BigQuery/Redshift — Snowflake will fund a POC
• Cortex AI commit carve-out: negotiate AI credits as separate line item with usage-based true-up
• Procurement signal: mention Databricks evaluation in writing — discounts move 10-15%

BigQuery / Google Cloud

• Committed Use Discounts on Editions: 20% (1yr) / 40% (3yr) standard
• Enterprise Agreement gets you another 5-10% if bundled with GCP infra spend
• Gemini token commit: Google is buying market share — ask for AI credits parity vs. OpenAI
• Multi-region storage discount: data sovereignty asks (EU, India) move pricing
• Procurement signal: mention Snowflake-on-GCP — Google sales will discount to keep workload native

Redshift / AWS

• 3yr Reserved Instance on RA3: ~60% off list, no upfront option available
• Enterprise Discount Program (EDP) — bundled S3, EC2, Redshift commit gets 15-25% across the board
• Serverless commit announced at reInvent 2025: now negotiable per-RPU pricing for $500K+/yr commits
• Free DMS migration + Professional Services credits if migrating from competitor warehouse
• Procurement signal: mention Iceberg + open-table strategy — AWS will negotiate to keep you in Redshift vs. Open-source Trino/Athena

The AI Workload Question

• Snowflake Cortex prices LLM inference in credits — convenient billing but opaque; Llama 3.1 70b runs ~$1.21/1M output tokens, fine-tunes priced in credit-hours. Embedding functions cheap, generative LLM calls expensive at scale.
• BigQuery + Gemini integration is currently the cheapest path for high-volume LLM enrichment — Gemini 1.5 Flash at ~$0.30/1M output tokens beats Cortex by ~3-4x for equivalent quality on summarization/classification.
• Redshift ML outsources to SageMaker — you pay SageMaker endpoint costs (instance-hour pricing) plus Redshift compute for the SQL wrapper. Worst $/inference of the three for ad-hoc generative work but best for batch scoring at predictable volume.
• The overcharge today: Snowflake Cortex is the most expensive per-token for top-tier models (GPT-4-class), justified by zero data movement. If your AI workload is 60%+ of platform spend, BigQuery + Gemini or Redshift + Bedrock will beat Snowflake on raw economics — but factor in egress and security review costs.
• Vector search: Snowflake (native Cortex Search), BigQuery (Vector Search GA 2025), Redshift (pgvector via Aurora integration) — Snowflake currently has the simplest TCO story for embedding-heavy RAG workloads kept inside the warehouse.

Pricing Comparison Table

*All figures list-price approximations May 2026; actual contract pricing varies 30-60% with commits.*

Decision Tree

FAQ

Which warehouse wins for a small team with bursty ad-hoc analyst queries? BigQuery on-demand wins at small scale because you pay $0 when no one queries and only pay storage. In Workload 1 (5 analysts, ~50 queries/day, ~500GB scanned/day), BigQuery on-demand came in around $135/mo versus Snowflake's ~$170/mo and Redshift Serverless' ~$280/mo.

How is Snowflake compute priced and what does a credit cost? Snowflake bills credits per hour times warehouse size (XS=1 up to 6XL=512), per-second after a 60-second minimum. Credit price varies by edition: roughly $2/credit for Standard on AWS US East, ~$3 for Enterprise, and ~$4 for Business Critical, with capacity contracts unlocking 10-50% off list.

What is the danger with BigQuery on-demand pricing? BigQuery on-demand can explode if a junior analyst writes SELECT * against a partitioned 50TB table, since you pay roughly $6.25/TB scanned. It bills per byte read with no compute SKU, so undisciplined scans drive cost directly.

When does Redshift win on data-gravity? At AWS-native shops with tight Lake Formation, S3, and IAM integration, Redshift Serverless wins on data-gravity because egress alone often kills the Snowflake or BigQuery alternative. The gotcha is RA3 vs. Serverless vs. Legacy DC2 SKU sprawl that confuses procurement.

What hidden Snowflake costs catch teams off guard? Cloud Services compute is free only up to 10% of warehouse spend, Materialized View auto-refresh consumes credits silently, and Time Travel plus Fail-safe storage stacks on top of base storage. Search Optimization Service is opt-in but easy to forget and can add 5-15% to the credit bill on enabled tables.

Bottom Line

Stop comparing list prices — they lie. The real pricing question is (a) how predictable is your workload, (b) which cloud holds your data gravity, and (c) how disciplined is your SQL? BigQuery on-demand wins for small disciplined teams; Snowflake wins for predictable multi-cloud enterprises willing to commit; Redshift wins for AWS-native shops with reserved-instance budgets.

AI workload mix is the new wildcard — if 50%+ of your spend is going to LLM inference by 2027, BigQuery + Gemini currently has the most aggressive token economics, but lock-in considerations matter. Always model 3-year TCO including egress, storage tiers, and one major workload-pattern change.

*(see also: q1567, q1568, q1577)*