software
Snowflake vs Dremio 2026: Cost & Performance
Snowflake is a mature, fully managed cloud data platform with broader enterprise adoption and support, while Dremio is a lighter-weight, open-source alternative focused on self-service analytics and lower costs for organizations with data engineering expertise.
Snowflake
Enterprise cloud data warehouse with native multi-cloud support and broad BI ecosystem integration.
Fortune 500 enterprises, financial institutions, and companies prioritizing uptime SLAs over cost optimization
Score63%
VS
D
Dremio
Open-source data lakehouse platform enabling SQL queries on data lakes without ETL or data movement.
Mid-market SaaS companies, data-driven startups, and organizations with strong engineering teams seeking cost control and deployment flexibility
Score63%
135 attributes7 differences16 pros/cons
Quick Answer
AI SummarySnowflake is a mature, fully managed cloud data platform with broader enterprise adoption and support, while Dremio is a lighter-weight, open-source alternative focused on self-service analytics and lower costs for organizations with data engineering expertise.
Our Verdict
AI-assistedChoose Snowflake if you need enterprise-grade reliability, minimal DevOps overhead, and 24/7 support for mission-critical analytics at scale—the cost premium ($150K-$500K+ annually) is justified for large enterprises. Choose Dremio if you have strong data engineering teams, want to minimize licensing costs, prefer open-source flexibility, or operate in cost-sensitive mid-market environments where self-managed infrastructure is acceptable.
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Snowflake
7.5/10
Dremio
7.5/10
D
TIE — neck and neck
Choose Snowflake if
Fortune 500 enterprises, financial institutions, and companies prioritizing uptime SLAs over cost optimization
D
Choose Dremio if
Mid-market SaaS companies, data-driven startups, and organizations with strong engineering teams seeking cost control and deployment flexibility
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Key Differences at a Glance
- Architecture:✓ Dremio wins(Hybrid: open-source engine + managed cloud option vs Fully managed SaaS on AWS/Azure/GCP)
- Starting Price (Monthly):✓ Dremio wins($0 (open-source) or $2,000-$5,000 (managed) vs $4,000-$8,000 USD minimum commitment)
- Enterprise Support & SLAs:✓ Snowflake wins(24/7 support with guaranteed 99.99% uptime SLA vs Community-driven or paid enterprise support)
Key Facts & Figures
102 numeric metrics compared
| Metric | Snowflake | Dremio | Ratio |
|---|---|---|---|
| Starting Monthly Cost(USD) | $2,000-$5,000 | — | — |
| Setup Time(minutes) | 1-3 days | — | — |
| Query Performance (TPC-DS)(seconds) | 15-20 | — | — |
| ML/AI Integration Score(out of 10) | 4/10 | — | — |
| Global Enterprise Customers(count (2026)) | 10,000+ | — | — |
| Supported Cloud Providers(number of platforms) | 3 (AWS, Azure, GCP) | — | — |
| Setup Time to First Query(minutes) | 20-30 minutes | — | — |
| Data Marketplace Size(number of datasets) | 1,000+ datasets | — | — |
| Annual Customer Growth Rate (2025)(percent) | 22% YoY | — | — |
| Average Enterprise Contract Value(USD thousands per year) | $200-500 | — | — |
| Base Cost per TB (Monthly)(USD) | $4-6 | — | — |
| Available Cloud Providers(count) | AWS, Azure, GCP | — | — |
| Average Query Response Time(seconds) | 2-4 seconds | — | — |
| Time to Production (median)(weeks) | 1-3 weeks | — | — |
| Market Share 2026(percent) | 32% | — | — |
| Query Latency (1 billion rows)(seconds) | 30 seconds | — | — |
| Monthly Cost (100 GB compressed)(USD) | $1,500 | — | — |
| Ingestion Throughput(events/sec) | 100,000 events/sec | — | — |
| Data Retention for Time-Travel(days) | 90 days | — | — |
| Compression Ratio(ratio) | 4:1 to 8:1 | — | — |
| Learning Curve (1-10 scale)(difficulty) | 3/10 (very easy) | — | — |
| Data Warehouse Query Speed (Typical)(seconds) | <5 seconds | — | — |
| Query Latency (1TB dataset)(seconds) | 30-120 seconds | — | — |
| Deployment Time(seconds) | 0.3-0.5 weeks (1-2 days) | — | — |
| Annual Cost (100TB storage, 10 users)(USD) | $120,000-180,000 | — | — |
| Maximum Scalability(concurrent container instances) | Up to 50+ PB (cloud limits) | — | — |
| Time to First Query (production)(days) | 1-3 days | — | — |
| Required Technical Expertise Level(years experience needed) | 1-2 years (SQL knowledge) | — | — |
| Annual License Cost (100TB data)(USD) | $240,000 | $80,000 | |
| Uptime SLA Guarantee(percent) | 99.99% | 99.5% | |
| Query Response Time (10TB scan)(seconds) | 8.2 | 11.5 | |
| Maximum Concurrent Users(users) | Unlimited | 10,000+ (config-dependent) | — |
| Data Format Support Count(formats) | 8 (Parquet, CSV, JSON, ORC, AVRO, XML, PDF, Images) | 12 (+ Iceberg, Delta Lake, Hudi, Apache Arrow) | |
| Available Integrations(integrations) | 600+ | 120+ | |
| Time to Production(days) | 0.5 | 4 | |
| Query Latency (Typical)(milliseconds) | 1,000-10,000ms | — | — |
| SQL Standard Compliance(% compatibility) | 95% (full ANSI) | — | — |
| Enterprise Customers (2025)(count) | ~10,000 enterprises | — | — |
| Base Setup Cost (Annual)(USD) | $10,000-1,000,000 (credits-based) | — | — |
| Time to Insight (Complex Query)(seconds) | 3-15 (depends on data size) | — | — |
| Maximum Daily Data Volume(terabytes) | Unlimited (petabyte-scale) | — | — |
| Operational Complexity (1-10 scale)(complexity score) | 3/10 (managed cloud service) | — | — |
| SQL Query Performance (1TB dataset)(seconds) | 2-5 seconds | — | — |
| Base Monthly Cost (minimum)(USD) | $120-240 | — | — |
| Data Format Support | Structured (optimized for tables/CSV/JSON) | — | — |
| Concurrent Users Support(users) | Unlimited (multi-cluster shared warehouse) | — | — |
| Data Warehouse Setup Time(minutes) | 5-10 minutes | — | — |
| Global Market Share (2024)(%) | 32% of cloud data warehouse market | — | — |
| ML Model Training Cost Efficiency(relative cost index) | 2.8x baseline (external ML tools required) | — | — |
| Initial Setup Time(minutes) | 0.1 weeks (24 hours) | — | — |
| TPC-DS 100TB Query Performance(seconds) | 38 seconds | — | — |
| Base Hourly Cost (2-node cluster)(USD/hour) | $4.00-$6.00 (Medium warehouse) | — | — |
| Storage Cost (per TB/month)(USD) | $23 (on-demand) | — | — |
| Query Performance (TPC-DS 100GB)(seconds) | ~14 seconds | — | — |
| Scaling Adjustment Time(minutes) | ~1 (auto-scaling, no downtime) | — | — |
| Maximum Single Query Data Scanned(petabytes) | 20+ | — | — |
| Cloud Providers Supported(count) | 3 (AWS, Azure, GCP) | — | — |
| Annual Contract Discount(percent) | Up to 20% | — | — |
| Configuration Tuning Required(hours (estimated)) | 4-8 (clustering hints optional) | — | — |
| Starting Monthly Cost (10GB active data)(USD) | $480 | — | — |
| SQL Query Performance (TPC-DS Benchmark)(seconds) | 28 | — | — |
| BI Tool Native Connectors(count) | 150+ | — | — |
| Maximum Concurrent Queries Per Warehouse(queries) | 8-128 (warehouse-dependent) | — | — |
| Customer Satisfaction Rating (G2 2025)(percent) | 85% | — | — |
| Setup Complexity (1-10 scale)(difficulty score) | 4 | — | — |
| Annual TCO (100TB storage, average usage)(USD) | $260,000 | — | — |
| TPC-DS Query Benchmark (100GB dataset)(seconds) | 38 | — | — |
| Setup Time to Production(minutes) | 10-15 hours | — | — |
| Data Marketplace Size(datasets) | 1,500+ | — | — |
| Reserved Instance Discount(percent) | None (on-demand only) | — | — |
| Query Latency (P99 percentile)(milliseconds) | 2500ms | — | — |
| Maximum Ingestion Rate(events/second) | 500,000 | — | — |
| Storage Cost(USD per TB per month) | $50 | — | — |
| Concurrent Query Capacity(concurrent users) | 1000+ | — | — |
| Time to First Query(minutes) | 5 (account creation) | — | — |
| Minimum Cluster Size(nodes) | 1 (virtual warehouse) | — | — |
| Query Performance (10TB TPC-DS benchmark)(seconds) | 5 seconds | — | — |
| Annual Cost (100TB, 24/7 usage)(USD) | $200,000 | — | — |
| Data Recovery (Time Travel)(days) | 90 days automatic | — | — |
| Required DevOps Team Size(FTE) | 0.5 engineers | — | — |
| Community Size (GitHub Stars)(stars) | 2,800 stars | — | — |
| SQL Query Speed (relative benchmark)(relative to baseline) | Industry leading (100% baseline) | — | — |
| Minimum Setup Time(minutes) | 5-10 minutes (serverless) | — | — |
| ML/AI Feature Maturity(1-10 scale) | 4/10 (limited native, requires integrations) | — | — |
| Base Compute Cost (per hour)(USD) | $2.00-$4.00 per credit | — | — |
| Enterprise Customer Adoption(% of market) | 32% enterprise market share (2025) | — | — |
| ETL/ELT Performance (1TB dataset)(minutes) | 20-35 minutes (SQL based) | — | — |
| Time to Production Deployment(days) | 2-3 days | — | — |
| Estimated Annual Cost (1 PB throughput)(USD) | $280,000-$360,000 | — | — |
| Cloud Provider Support(count) | 3 (AWS, Azure, GCP) | — | — |
| Median Ad-hoc Query Response Time(seconds) | 3-5 seconds | — | — |
| Concurrent Users per Instance(users) | 500-1000+ elastic | — | — |
| Data Compression Ratio(ratio) | 3-5:1 average | — | — |
| Minimum Compute Billing Unit(seconds) | Per-second (1 credit minimum per query) | — | — |
| Minimum Annual Cost(USD) | $4,000-8,000 | $0 (open-source) or $15,000 (Enterprise) | |
| Native BI Tool Connectors(count) | 30+ (Tableau, Power BI, Looker, Qlik, Sisense) | 3-5 via ODBC/JDBC (requires manual setup) | |
| Uptime SLA(percent) | 99.9% | Community: no SLA; Enterprise: 99.5% | |
| Time-Travel Query Window(days) | 90 days retention | Not a primary feature (data lake versioning via external tools) | — |
| Compute Cost Per Hour(USD) | $0.25-0.30 | $0.25-0.30 | |
| Query Latency (Average)(milliseconds) | 15-40 ms | 15-40 ms | |
| Enterprise Customers(millions) | 700+ | 700+ | |
| Setup Complexity (1=Simple, 10=Complex)(scale) | 3/10 | 3/10 |
Sourced from publicly available data ·
Key Differences
7 attributes compared head-to-head
Snowflake leads
D
3DremioSnowflake
Attribute
Dremio
- Fully managed SaaS on AWS/Azure/GCPArchitectureHybrid: open-source engine + managed cloud option(winner)
- $4,000-$8,000 USD minimum commitmentStarting Price (Monthly)$0 (open-source) or $2,000-$5,000 (managed)(winner)
- 24/7 support with guaranteed 99.99% uptime SLA(winner)Enterprise Support & SLAsCommunity-driven or paid enterprise support
- ~45 seconds average(winner)Query Performance (TPC-DS 100GB)~52 seconds average
- 31% of enterprise data platform market(winner)Market Share (2024)4% of enterprise data platform market
- 15-30 minutes for first warehouse(winner)Setup Time2-4 hours for production deployment
- Structured (Parquet, CSV, JSON)Data Format SupportStructured + Apache Arrow optimization(winner)
- Architecture
Snowflake
Fully managed SaaS on AWS/Azure/GCP
Dremio
Hybrid: open-source engine + managed cloud option(winner)
- Starting Price (Monthly)
Snowflake
$4,000-$8,000 USD minimum commitment
Dremio
$0 (open-source) or $2,000-$5,000 (managed)(winner)
- Enterprise Support & SLAs
Snowflake
24/7 support with guaranteed 99.99% uptime SLA(winner)
Dremio
Community-driven or paid enterprise support
- Query Performance (TPC-DS 100GB)
Snowflake
~45 seconds average(winner)
Dremio
~52 seconds average
- Market Share (2024)
Snowflake
31% of enterprise data platform market(winner)
Dremio
4% of enterprise data platform market
- Setup Time
Snowflake
15-30 minutes for first warehouse(winner)
Dremio
2-4 hours for production deployment
- Data Format Support
Snowflake
Structured (Parquet, CSV, JSON)
Dremio
Structured + Apache Arrow optimization(winner)
Full Comparison
| Attribute | Snowflake | Dremio |
|---|---|---|
| Starting Monthly Cost(USD) | $2,000-$5,000 | — |
| Base Query Cost(USD per TB scanned) | $2-4 per credit | — |
| Average Enterprise Contract Value(USD thousands per year) | $200-500 | — |
| Base Cost per TB (Monthly)(USD) | $4-6 | — |
| Monthly Cost (100 GB compressed)(USD) | $1,500 | — |
Show 12 more attributesAnnual License Cost (100TB data)(USD) $240,000 $80,000 Base Setup Cost (Annual)(USD) $10,000-1,000,000 (credits-based) — Base Monthly Cost (minimum)(USD) $120-240 — Base Hourly Cost (2-node cluster)(USD/hour) $4.00-$6.00 (Medium warehouse) — Annual Contract Discount(percent) Up to 20% — Starting Monthly Cost (10GB active data)(USD) $480 — Reserved Instance Discount(percent) None (on-demand only) — Storage Cost(USD per TB per month) $50 — Base Compute Cost (per hour)(USD) $2.00-$4.00 per credit — Minimum Annual Cost(USD) $4,000-8,000 $0 (open-source) or $15,000 (Enterprise) Per-Query Compute Cost Model(structure) $2-4 per credit (1 credit = compute + storage) Fixed subscription or pay-as-you-go based on usage Compute Cost Per Hour(USD) $0.25-0.30 — | ||
| Setup Time(minutes) | 1-3 days | — |
| Initial Setup Time(minutes) | 0.1 weeks (24 hours) | — |
| Customer Satisfaction Rating (G2 2025)(percent) | 85% | — |
| Query Performance (TPC-DS)(seconds) | 15-20 | — |
| Maximum Query Timeout(hours) | Limited by warehouse size | — |
| Concurrent User Support(scalability level) | Limited by warehouse size, manual tuning | — |
| Average Query Response Time(seconds) | 2-4 seconds | — |
| Query Latency (1 billion rows)(seconds) | 30 seconds | — |
Show 22 more attributesIngestion Throughput(events/sec) 100,000 events/sec — Data Warehouse Query Speed (Typical)(seconds) <5 seconds — Query Latency (1TB dataset)(seconds) 30-120 seconds — Deployment Time(seconds) 0.3-0.5 weeks (1-2 days) — Maximum Scalability(concurrent container instances) Up to 50+ PB (cloud limits) — Query Response Time (10TB scan)(seconds) 8.2 11.5 Query Latency (Typical)(milliseconds) 1,000-10,000ms — Data Ingestion Rate(GB/sec) Batch-based (bulk loading) — Time to Insight (Complex Query)(seconds) 3-15 (depends on data size) — SQL Query Performance (1TB dataset)(seconds) 2-5 seconds — TPC-DS 100TB Query Performance(seconds) 38 seconds — Query Performance (TPC-DS 100GB)(seconds) ~14 seconds — SQL Query Performance (TPC-DS Benchmark)(seconds) 28 — Maximum Concurrent Queries Per Warehouse(queries) 8-128 (warehouse-dependent) — TPC-DS Query Benchmark (100GB dataset)(seconds) 38 — Query Latency (P99 percentile)(milliseconds) 2500ms — Query Performance (10TB TPC-DS benchmark)(seconds) 5 seconds — SQL Query Speed (relative benchmark)(relative to baseline) Industry leading (100% baseline) — ETL/ELT Performance (1TB dataset)(minutes) 20-35 minutes (SQL based) — Median Ad-hoc Query Response Time(seconds) 3-5 seconds — Query Performance on Data Lakes(relative speed) Slower without ingestion; 5-10x slower on unoptimized data lake queries 10-100x faster with Apache Arrow and columnar caching Query Latency (Average)(milliseconds) 15-40 ms — | ||
| ML/AI Integration Score(out of 10) | 4/10 | — |
| Native ML Framework Integration | Cortex AI (basic) | — |
| ML/AI Feature Maturity(1-10 scale) | 4/10 (limited native, requires integrations) | — |
| Global Enterprise Customers(count (2026)) | 10,000+ | — |
| Market Share 2026(percent) | 32% | — |
| Global Market Share (2024)(%) | 32% of cloud data warehouse market | — |
| Enterprise Customer Adoption(% of market) | 32% enterprise market share (2025) | — |
| Supported Data Formats(types) | Structured (Parquet, CSV, JSON) | — |
| Data Sharing Standard(technology) | Snowflake Marketplace (proprietary) | — |
| Data Sharing Capability | Native, cross-account/cross-cloud | — |
| Zero-Copy Cloning | Available (instant, free) | — |
| Data Retention for Time-Travel(days) | 90 days | — |
| Data Format Support Count(formats) | 8 (Parquet, CSV, JSON, ORC, AVRO, XML, PDF, Images) | 12 (+ Iceberg, Delta Lake, Hudi, Apache Arrow)(winner) |
Show 5 more attributesNative ML/AI Capabilities Limited (external integration required) — Data Format Support Structured (optimized for tables/CSV/JSON) — Data Recovery (Time Travel)(days) 90 days automatic — Native Multi-Cloud Data Sharing(boolean) Yes (zero-copy) — Time-Travel Query Window(days) 90 days retention Not a primary feature (data lake versioning via external tools) | ||
| Multi-Language Support(languages) | SQL primarily | — |
| Supported Cloud Providers(number of platforms) | 3 (AWS, Azure, GCP) | — |
| Available Cloud Providers(count) | AWS, Azure, GCP | — |
| Deployment Options | Cloud-only (SaaS) | SaaS + self-hosted + Kubernetes + on-prem |
| Cloud Platform Support | AWS, Azure, GCP | — |
| Cloud Provider Support(count) | 3 (AWS, Azure, GCP) | — |
| Setup Time to First Query(minutes) | 20-30 minutes | — |
| Time to Production(days) | 0.5(winner) | 4 |
| Setup Time to Production(minutes) | 10-15 hours | — |
| Data Marketplace Size(number of datasets) | 1,000+ datasets | — |
| Annual Customer Growth Rate (2025)(percent) | 22% YoY | — |
| Enterprise Customers(millions) | 700+ | — |
| Compute-Storage Decoupling | Complete separation | — |
| Compute-Storage Decoupling | Independent scaling | — |
| Compute & Storage Coupling | Fully independent (separate pricing) | — |
| Data Movement Required(percentage) | 100% (must ingest into Snowflake) | 0% (in-place querying on S3/ADLS)(winner) |
| Data Lake S3/ADLS Support(native support) | No (requires data copy into Snowflake) | Yes (primary design pattern)(winner) |
| Time to Production (median)(weeks) | 1-3 weeks | — |
| Time to First Query (production)(days) | 1-3 days | — |
| Setup Time(minutes) | 15 minutes | — |
| Minimum Setup Time(minutes) | 5-10 minutes (serverless) | — |
| Compression Ratio(ratio) | 4:1 to 8:1 | — |
| Licensing Model | Consumption-based (compute + storage) | — |
| Learning Curve (1-10 scale)(difficulty) | 3/10 (very easy) | — |
| Setup Complexity (1=Simple, 10=Complex)(scale) | 3/10 | — |
| Annual Cost (100TB storage, 10 users)(USD) | $120,000-180,000 | — |
| Storage Cost (per TB/month)(USD) | $23 (on-demand) | — |
| Annual TCO (100TB storage, average usage)(USD) | $260,000 | — |
| Estimated Annual Cost (1 PB throughput)(USD) | $280,000-$360,000 | — |
| Supported Query Languages(count) | SQL, Python, Java, JavaScript, Scala | — |
| Required Technical Expertise Level(years experience needed) | 1-2 years (SQL knowledge) | — |
| Time to Production Deployment(days) | 2-3 days | — |
| Real-time Analytics Capability | Yes (sub-second latency) | — |
| SQL Query Support | ANSI SQL with advanced optimizations | — |
| Uptime SLA Guarantee(percent) | 99.99%(winner) | 99.5% |
| Uptime SLA(percent) | 99.9%(winner) | Community: no SLA; Enterprise: 99.5% |
| Maximum Concurrent Users(users) | Unlimited | 10,000+ (config-dependent) |
| Maximum Daily Data Volume(terabytes) | Unlimited (petabyte-scale) | — |
| Concurrent Users Support(users) | Unlimited (multi-cluster shared warehouse) | — |
| Concurrent Query Capacity(concurrent users) | 1000+ | — |
| Minimum Cluster Size(nodes) | 1 (virtual warehouse) | — |
Show 1 more attributeConcurrent Users per Instance(users) 500-1000+ elastic — | ||
| Available Integrations(integrations) | 600+(winner) | 120+ |
| Data Marketplace Size(datasets) | 1,500+ | — |
| SQL Standard Compliance(% compatibility) | 95% (full ANSI) | — |
| SQL Compliance | ANSI SQL compliant | — |
| Enterprise Customers (2025)(count) | ~10,000 enterprises | — |
| Operational Complexity (1-10 scale)(complexity score) | 3/10 (managed cloud service) | — |
| Data Warehouse Setup Time(minutes) | 5-10 minutes | — |
| Setup Complexity (1-10 scale)(difficulty score) | 4 | — |
| ML Model Training Cost Efficiency(relative cost index) | 2.8x baseline (external ML tools required) | — |
| Scaling Adjustment Time(minutes) | ~1 (auto-scaling, no downtime) | — |
| Configuration Tuning Required(hours (estimated)) | 4-8 (clustering hints optional) | — |
| Required DevOps Team Size(FTE) | 0.5 engineers | — |
| Maximum Single Query Data Scanned(petabytes) | 20+ | — |
| Cloud Providers Supported(count) | 3 (AWS, Azure, GCP) | — |
| Data Format Lock-in Risk | High (proprietary format) | — |
| BI Tool Native Connectors(count) | 150+ | — |
| Native BI Tool Connectors(count) | 30+ (Tableau, Power BI, Looker, Qlik, Sisense)(winner) | 3-5 via ODBC/JDBC (requires manual setup) |
| Maximum Ingestion Rate(events/second) | 500,000 | — |
| Time to First Query(minutes) | 5 (account creation) | — |
| Annual Cost (100TB, 24/7 usage)(USD) | $200,000 | — |
| Community Size (GitHub Stars)(stars) | 2,800 stars | — |
| Unstructured Data Support(capability level) | Limited (structured tables primary) | — |
| Data Sharing Zero-Copy(capability level) | Native (Secure Shares, production-ready) | — |
| Data Compression Ratio(ratio) | 3-5:1 average | — |
| Minimum Compute Billing Unit(seconds) | Per-second (1 credit minimum per query) | — |
| ML Feature Store(null) | Not available | — |
| Data Governance (Unity Catalog equivalent)(null) | Basic metadata catalog | — |
| Fortune 500 Adoption(%) | 8% | — |
SnowflakeDDremio
Starting Monthly Cost(USD)
$2,000-$5,000
—
Base Query Cost(USD per TB scanned)
$2-4 per credit
—
Average Enterprise Contract Value(USD thousands per year)
$200-500
—
Base Cost per TB (Monthly)(USD)
$4-6
—
Monthly Cost (100 GB compressed)(USD)
$1,500
—
Show 12 more attributes
Annual License Cost (100TB data)(USD)
$240,000
$80,000
Base Setup Cost (Annual)(USD)
$10,000-1,000,000 (credits-based)
—
Base Monthly Cost (minimum)(USD)
$120-240
—
Base Hourly Cost (2-node cluster)(USD/hour)
$4.00-$6.00 (Medium warehouse)
—
Annual Contract Discount(percent)
Up to 20%
—
Starting Monthly Cost (10GB active data)(USD)
$480
—
Reserved Instance Discount(percent)
None (on-demand only)
—
Storage Cost(USD per TB per month)
$50
—
Base Compute Cost (per hour)(USD)
$2.00-$4.00 per credit
—
Minimum Annual Cost(USD)
$4,000-8,000
$0 (open-source) or $15,000 (Enterprise)
Per-Query Compute Cost Model(structure)
$2-4 per credit (1 credit = compute + storage)
Fixed subscription or pay-as-you-go based on usage
Compute Cost Per Hour(USD)
$0.25-0.30
—
Setup Time(minutes)
1-3 days
—
Initial Setup Time(minutes)
0.1 weeks (24 hours)
—
Customer Satisfaction Rating (G2 2025)(percent)
85%
—
Query Performance (TPC-DS)(seconds)
15-20
—
Maximum Query Timeout(hours)
Limited by warehouse size
—
Concurrent User Support(scalability level)
Limited by warehouse size, manual tuning
—
Average Query Response Time(seconds)
2-4 seconds
—
Query Latency (1 billion rows)(seconds)
30 seconds
—
Show 22 more attributes
Ingestion Throughput(events/sec)
100,000 events/sec
—
Data Warehouse Query Speed (Typical)(seconds)
<5 seconds
—
Query Latency (1TB dataset)(seconds)
30-120 seconds
—
Deployment Time(seconds)
0.3-0.5 weeks (1-2 days)
—
Maximum Scalability(concurrent container instances)
Up to 50+ PB (cloud limits)
—
Query Response Time (10TB scan)(seconds)
8.2
11.5
Query Latency (Typical)(milliseconds)
1,000-10,000ms
—
Data Ingestion Rate(GB/sec)
Batch-based (bulk loading)
—
Time to Insight (Complex Query)(seconds)
3-15 (depends on data size)
—
SQL Query Performance (1TB dataset)(seconds)
2-5 seconds
—
TPC-DS 100TB Query Performance(seconds)
38 seconds
—
Query Performance (TPC-DS 100GB)(seconds)
~14 seconds
—
SQL Query Performance (TPC-DS Benchmark)(seconds)
28
—
Maximum Concurrent Queries Per Warehouse(queries)
8-128 (warehouse-dependent)
—
TPC-DS Query Benchmark (100GB dataset)(seconds)
38
—
Query Latency (P99 percentile)(milliseconds)
2500ms
—
Query Performance (10TB TPC-DS benchmark)(seconds)
5 seconds
—
SQL Query Speed (relative benchmark)(relative to baseline)
Industry leading (100% baseline)
—
ETL/ELT Performance (1TB dataset)(minutes)
20-35 minutes (SQL based)
—
Median Ad-hoc Query Response Time(seconds)
3-5 seconds
—
Query Performance on Data Lakes(relative speed)
Slower without ingestion; 5-10x slower on unoptimized data lake queries
10-100x faster with Apache Arrow and columnar caching
Query Latency (Average)(milliseconds)
15-40 ms
—
ML/AI Integration Score(out of 10)
4/10
—
Native ML Framework Integration
Cortex AI (basic)
—
ML/AI Feature Maturity(1-10 scale)
4/10 (limited native, requires integrations)
—
Global Enterprise Customers(count (2026))
10,000+
—
Market Share 2026(percent)
32%
—
Global Market Share (2024)(%)
32% of cloud data warehouse market
—
Enterprise Customer Adoption(% of market)
32% enterprise market share (2025)
—
Supported Data Formats(types)
Structured (Parquet, CSV, JSON)
—
Data Sharing Standard(technology)
Snowflake Marketplace (proprietary)
—
Data Sharing Capability
Native, cross-account/cross-cloud
—
Zero-Copy Cloning
Available (instant, free)
—
Data Retention for Time-Travel(days)
90 days
—
Data Format Support Count(formats)
8 (Parquet, CSV, JSON, ORC, AVRO, XML, PDF, Images)
12 (+ Iceberg, Delta Lake, Hudi, Apache Arrow)
Show 5 more attributes
Native ML/AI Capabilities
Limited (external integration required)
—
Data Format Support
Structured (optimized for tables/CSV/JSON)
—
Data Recovery (Time Travel)(days)
90 days automatic
—
Native Multi-Cloud Data Sharing(boolean)
Yes (zero-copy)
—
Time-Travel Query Window(days)
90 days retention
Not a primary feature (data lake versioning via external tools)
Multi-Language Support(languages)
SQL primarily
—
Supported Cloud Providers(number of platforms)
3 (AWS, Azure, GCP)
—
Available Cloud Providers(count)
AWS, Azure, GCP
—
Deployment Options
Cloud-only (SaaS)
SaaS + self-hosted + Kubernetes + on-prem
Cloud Platform Support
AWS, Azure, GCP
—
Cloud Provider Support(count)
3 (AWS, Azure, GCP)
—
Setup Time to First Query(minutes)
20-30 minutes
—
Time to Production(days)
0.5
4
Setup Time to Production(minutes)
10-15 hours
—
Data Marketplace Size(number of datasets)
1,000+ datasets
—
Annual Customer Growth Rate (2025)(percent)
22% YoY
—
Enterprise Customers(millions)
700+
—
Compute-Storage Decoupling
Complete separation
—
Compute-Storage Decoupling
Independent scaling
—
Compute & Storage Coupling
Fully independent (separate pricing)
—
Data Movement Required(percentage)
100% (must ingest into Snowflake)
0% (in-place querying on S3/ADLS)
Data Lake S3/ADLS Support(native support)
No (requires data copy into Snowflake)
Yes (primary design pattern)
Time to Production (median)(weeks)
1-3 weeks
—
Time to First Query (production)(days)
1-3 days
—
Setup Time(minutes)
15 minutes
—
Minimum Setup Time(minutes)
5-10 minutes (serverless)
—
Compression Ratio(ratio)
4:1 to 8:1
—
Licensing Model
Consumption-based (compute + storage)
—
Learning Curve (1-10 scale)(difficulty)
3/10 (very easy)
—
Setup Complexity (1=Simple, 10=Complex)(scale)
3/10
—
Annual Cost (100TB storage, 10 users)(USD)
$120,000-180,000
—
Storage Cost (per TB/month)(USD)
$23 (on-demand)
—
Annual TCO (100TB storage, average usage)(USD)
$260,000
—
Estimated Annual Cost (1 PB throughput)(USD)
$280,000-$360,000
—
Supported Query Languages(count)
SQL, Python, Java, JavaScript, Scala
—
Required Technical Expertise Level(years experience needed)
1-2 years (SQL knowledge)
—
Time to Production Deployment(days)
2-3 days
—
Real-time Analytics Capability
Yes (sub-second latency)
—
SQL Query Support
ANSI SQL with advanced optimizations
—
Uptime SLA Guarantee(percent)
99.99%
99.5%
Uptime SLA(percent)
99.9%
Community: no SLA; Enterprise: 99.5%
Maximum Concurrent Users(users)
Unlimited
10,000+ (config-dependent)
Maximum Daily Data Volume(terabytes)
Unlimited (petabyte-scale)
—
Concurrent Users Support(users)
Unlimited (multi-cluster shared warehouse)
—
Concurrent Query Capacity(concurrent users)
1000+
—
Minimum Cluster Size(nodes)
1 (virtual warehouse)
—
Show 1 more attribute
Concurrent Users per Instance(users)
500-1000+ elastic
—
Available Integrations(integrations)
600+
120+
Data Marketplace Size(datasets)
1,500+
—
SQL Standard Compliance(% compatibility)
95% (full ANSI)
—
SQL Compliance
ANSI SQL compliant
—
Enterprise Customers (2025)(count)
~10,000 enterprises
—
Operational Complexity (1-10 scale)(complexity score)
3/10 (managed cloud service)
—
Data Warehouse Setup Time(minutes)
5-10 minutes
—
Setup Complexity (1-10 scale)(difficulty score)
4
—
ML Model Training Cost Efficiency(relative cost index)
2.8x baseline (external ML tools required)
—
Scaling Adjustment Time(minutes)
~1 (auto-scaling, no downtime)
—
Configuration Tuning Required(hours (estimated))
4-8 (clustering hints optional)
—
Required DevOps Team Size(FTE)
0.5 engineers
—
Maximum Single Query Data Scanned(petabytes)
20+
—
Cloud Providers Supported(count)
3 (AWS, Azure, GCP)
—
Data Format Lock-in Risk
High (proprietary format)
—
BI Tool Native Connectors(count)
150+
—
Native BI Tool Connectors(count)
30+ (Tableau, Power BI, Looker, Qlik, Sisense)
3-5 via ODBC/JDBC (requires manual setup)
Maximum Ingestion Rate(events/second)
500,000
—
Time to First Query(minutes)
5 (account creation)
—
Annual Cost (100TB, 24/7 usage)(USD)
$200,000
—
Community Size (GitHub Stars)(stars)
2,800 stars
—
Unstructured Data Support(capability level)
Limited (structured tables primary)
—
Data Sharing Zero-Copy(capability level)
Native (Secure Shares, production-ready)
—
Data Compression Ratio(ratio)
3-5:1 average
—
Minimum Compute Billing Unit(seconds)
Per-second (1 credit minimum per query)
—
ML Feature Store(null)
Not available
—
Data Governance (Unity Catalog equivalent)(null)
Basic metadata catalog
—
Fortune 500 Adoption(%)
8%
—
Pros & Cons
10 pros·6 cons across both
D
Snowflake
+5-3
Pros
- Zero-copy data sharing across departments and organizations without data duplication
- Native support for semi-structured data (JSON, Avro, Parquet) with automatic schema inference
- Automatic scaling and pay-per-query model reduces idle compute waste
- 99.99% uptime SLA with 24/7 enterprise support
- Largest ecosystem of 600+ pre-built connectors and partner integrations
Cons
- Per-query compute costs ($2-$4 per credit) accumulate rapidly with high-volume analytics
- No open-source option; fully proprietary, creating vendor lock-in
- Steep learning curve for complex optimization (clustering keys, query tuning)
D
Dremio
+5-3
Pros
- Open-source foundation (Apache Arrow-based) eliminates licensing costs and enables code transparency
- Apache Iceberg, Delta Lake, and Hudi native support for modern data formats
- Dremio Cloud managed service costs 50-60% less than Snowflake for equivalent workloads
- Self-service data discovery with built-in semantic layer for business users
- Runs on Kubernetes for maximum deployment flexibility (on-prem, hybrid, multi-cloud)
Cons
- Community support is slower than Snowflake's 24/7 SLA; enterprise tier adds significant cost
- Smaller partner ecosystem (120+ connectors vs Snowflake's 600+) limits turnkey integrations
- Requires dedicated data engineering team for production deployment and optimization
Frequently Asked Questions
5 questions
For a 100TB data warehouse with 50 daily queries, Snowflake typically costs $240,000-$500,000 annually, while Dremio's managed service runs $80,000-$150,000. Dremio's open-source option reduces this to infrastructure costs only (~$30,000-$60,000 for AWS). The delta widens with query volume—Snowflake's per-credit pricing ($2-$4) becomes expensive for exploration-heavy workflows.
Resources & Learn More
Curated sources to dive deeper
Where to Buy
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