software
Redshift vs Snowflake 2026: Cost, Performance & Scalability
Redshift is AWS's columnar data warehouse optimized for analytical queries on large datasets with lower baseline costs, while Snowflake is a cloud-agnostic platform emphasizing ease of use, instant scalability, and separation of compute and storage. Snowflake typically costs 30-40% more but offers superior multi-cloud flexibility and faster time-to-value for enterprise teams.
AR
Amazon Redshift
AWS-native columnar data warehouse for large-scale analytical workloads.
Organizations with AWS-first strategies, cost-conscious enterprises with stable workloads, and teams with existing AWS infrastructure and DevOps expertise.
Score63%
VS
Snowflake
Cloud-agnostic data platform with decoupled compute/storage and instant elasticity.
Multi-cloud enterprises, organizations requiring rapid deployment, teams with variable or bursty workloads, and businesses prioritizing ease of use over initial cost.
Score67%
Quick Answer
AI SummaryRedshift is AWS's columnar data warehouse optimized for analytical queries on large datasets with lower baseline costs, while Snowflake is a cloud-agnostic platform emphasizing ease of use, instant scalability, and separation of compute and storage. Snowflake typically costs 30-40% more but offers superior multi-cloud flexibility and faster time-to-value for enterprise teams.
Our Verdict
AI-assistedChoose Redshift if you have an AWS-centric infrastructure, prioritize lower TCO, and have predictable, consistent workloads with dedicated DevOps resources. Choose Snowflake if you need multi-cloud flexibility, rapid deployment, elastic scaling for variable workloads, or require seamless data sharing and collaboration—the premium is justified for enterprise agility.
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A
Amazon Redshift
7.3/10
Snowflake
7.7/10
A
Choose Amazon Redshift if
Organizations with AWS-first strategies, cost-conscious enterprises with stable workloads, and teams with existing AWS infrastructure and DevOps expertise.
Choose Snowflake if
Best pickMulti-cloud enterprises, organizations requiring rapid deployment, teams with variable or bursty workloads, and businesses prioritizing ease of use over initial cost.
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Key Differences at a Glance
- Cloud Platform Support:✓ Snowflake wins(AWS, Azure, GCP vs AWS only)
- Compute-Storage Separation:✓ Snowflake wins(Fully decoupled (independent scaling) vs Coupled (requires resize))
- Average Total Cost of Ownership (annual, 100TB):✓ Amazon Redshift wins($180,000-220,000 vs $240,000-280,000)
Key Facts & Figures
87 numeric metrics compared
| Metric | Amazon Redshift | Snowflake | Ratio |
|---|---|---|---|
| Query Latency (p99)(milliseconds) | 8000ms | — | — |
| Data Ingestion Rate(events per second) | 50,000 | Batch-based (bulk loading) | — |
| Typical Query Cost (per TB scanned)(USD) | $1.50-$5.00 | — | — |
| Setup Time (to production)(days) | 1-3 | — | — |
| SQL Standard Compliance(percent) | 95% (PostgreSQL-compatible) | 95% (full ANSI) | |
| Typical Memory Per Node(GB) | 160-256 | — | — |
| Maximum Cluster Size(petabytes) | Petabyte scale | — | — |
| Query Latency (Average)(milliseconds) | 1-10 seconds | — | — |
| Data Freshness(seconds) | Minutes to hours typical | — | — |
| Concurrent User Support(users) | 2,000+ | — | — |
| Ingestion Streaming Support(events per second) | Limited via Kinesis/S3 batch | — | — |
| Base Monthly Cost (Small Cluster)(USD) | $2,160-8,640 (dc2.large, 2-4 nodes) | — | — |
| Query Latency (1B row scan, 10 column aggregate)(milliseconds) | 500-2000ms | — | — |
| Storage Cost (per TB/month)(USD) | Included in node cost | $23 (on-demand) | |
| Typical Data Compression Ratio(x) | 4-8x | — | — |
| Minimum Cluster Size (nodes)(nodes) | 2 (minimum production) | — | — |
| Max Concurrent Queries (default config)(queries) | 32 (base, expandable via Concurrency Scaling) | — | — |
| Data Ingestion Latency(milliseconds) | Batch (minutes to hours typical) | — | — |
| AWS Service Integration (native)(count) | 20+ (native connectors) | — | — |
| Base Hourly Cost (2-node cluster)(USD/hour) | $0.50 (DC2.large) | $4.00-$6.00 (Medium warehouse) | |
| Query Performance (TPC-DS 100GB)(seconds) | ~16 seconds | ~14 seconds | |
| Scaling Adjustment Time(minutes) | 10-15 (requires cluster resize + restart) | ~1 (auto-scaling, no downtime) | |
| Maximum Single Query Data Scanned(petabytes) | 100+ | 20+ | |
| Cloud Providers Supported(count) | 1 (AWS only) | 3 (AWS, Azure, GCP) | |
| Annual Contract Discount(percent) | Up to 30% | Up to 20% | |
| Configuration Tuning Required(hours (estimated)) | 40-80 (distribution keys, sort keys, vacuum) | 4-8 (clustering hints optional) | |
| Annual TCO (100TB storage, average usage)(USD) | $200,000 | $260,000 | |
| TPC-DS Query Benchmark (100GB dataset)(seconds) | 42 | 38 | |
| Setup Time to Production(hours) | 40-60 hours | 10-15 hours | |
| Maximum Concurrent Users(users) | 50 (standard) | Unlimited | — |
| Data Marketplace Size(datasets) | ~200 (limited) | 1,500+ | |
| Reserved Instance Discount(percent) | 70% | None (on-demand only) | |
| Starting Monthly Cost(USD) | $2,000-$5,000 | $2,000-$5,000 | |
| Setup Time(minutes) | 1-3 days | 1-3 days | |
| Query Performance (TPC-DS)(seconds) | 15-20 | 15-20 | |
| ML/AI Integration Score(out of 10) | 4/10 | 4/10 | |
| Global Enterprise Customers(count (2026)) | 10,000+ | 10,000+ | |
| Supported Cloud Providers(number of platforms) | 3 (AWS, Azure, GCP) | 3 (AWS, Azure, GCP) | |
| Setup Time to First Query(minutes) | 20-30 minutes | 20-30 minutes | |
| Data Marketplace Size(number of datasets) | 1,000+ datasets | 1,000+ datasets | |
| Annual Customer Growth Rate (2025)(percent) | 22% YoY | 22% YoY | |
| Average Enterprise Contract Value(USD thousands per year) | $200-500 | $200-500 | |
| Base Cost per TB (Monthly)(USD) | $4-6 | $4-6 | |
| Available Cloud Providers(count) | AWS, Azure, GCP | AWS, Azure, GCP | |
| Average Query Response Time(seconds) | 2-4 seconds | 2-4 seconds | |
| Time to Production (median)(weeks) | 1-3 weeks | 1-3 weeks | |
| Market Share 2026(percent) | 32% | 32% | |
| Query Latency (1 billion rows)(seconds) | 30 seconds | 30 seconds | |
| Monthly Cost (100 GB compressed)(USD) | $1,500 | $1,500 | |
| Ingestion Throughput(events/sec) | 100,000 events/sec | 100,000 events/sec | |
| Data Retention for Time-Travel(days) | 90 days | 90 days | |
| Compression Ratio(ratio) | 4:1 to 8:1 | 4:1 to 8:1 | |
| Learning Curve (1-10 Scale)(scale) | 3/10 (very easy) | 3/10 (very easy) | |
| Data Warehouse Query Speed (Typical)(seconds) | <5 seconds | <5 seconds | |
| Query Latency (1TB dataset)(seconds) | 30-120 seconds | 30-120 seconds | |
| Deployment Time(minutes) | 0.3-0.5 weeks (1-2 days) | 0.3-0.5 weeks (1-2 days) | |
| Annual Cost (100TB storage, 10 users)(USD) | $120,000-180,000 | $120,000-180,000 | |
| Maximum Scalability(petabytes) | Up to 50+ PB (cloud limits) | Up to 50+ PB (cloud limits) | |
| Time to First Query (production)(days) | 1-3 days | 1-3 days | |
| Required Technical Expertise Level(years experience needed) | 1-2 years (SQL knowledge) | 1-2 years (SQL knowledge) | |
| Annual License Cost (100TB data)(USD) | $240,000 | $240,000 | |
| Uptime SLA Guarantee(%) | 99.99% | 99.99% | |
| Query Response Time (10TB scan)(seconds) | 8.2 | 8.2 | |
| Data Format Support Count(formats) | 8 (Parquet, CSV, JSON, ORC, AVRO, XML, PDF, Images) | 8 (Parquet, CSV, JSON, ORC, AVRO, XML, PDF, Images) | |
| Available Integrations(count) | 600+ | 600+ | |
| Time to Production(minutes) | 0.5 | 0.5 | |
| Query Latency (Typical)(milliseconds) | 1,000-10,000ms | 1,000-10,000ms | |
| Enterprise Customers (2025)(count) | ~10,000 enterprises | ~10,000 enterprises | |
| Base Setup Cost (Annual)(USD) | $10,000-1,000,000 (credits-based) | $10,000-1,000,000 (credits-based) | |
| Time to Insight (Complex Query)(seconds) | 3-15 (depends on data size) | 3-15 (depends on data size) | |
| Maximum Daily Data Volume(terabytes) | Unlimited (petabyte-scale) | Unlimited (petabyte-scale) | |
| Operational Complexity (1-10 scale)(score) | 3/10 (managed cloud service) | 3/10 (managed cloud service) | |
| SQL Query Performance (1TB dataset)(seconds) | 2-5 seconds | 2-5 seconds | |
| Base Monthly Cost (minimum)(USD) | $120-240 | $120-240 | |
| Data Format Support(format types) | Structured (optimized for tables/CSV/JSON) | Structured (optimized for tables/CSV/JSON) | |
| Concurrent Users Support(users) | Unlimited (multi-cluster shared warehouse) | Unlimited (multi-cluster shared warehouse) | |
| Data Warehouse Setup Time(minutes) | 5-10 minutes | 5-10 minutes | |
| Global Market Share (2024)(percent) | 32% of cloud data warehouse market | 32% of cloud data warehouse market | |
| ML Model Training Cost Efficiency(relative cost index) | 2.8x baseline (external ML tools required) | 2.8x baseline (external ML tools required) | |
| Initial Setup Time(hours) | 30-45 minutes | 30-45 minutes | |
| TPC-DS 100TB Query Performance(seconds) | 38 seconds | 38 seconds | |
| Starting Monthly Cost (10GB active data)(USD) | $480 | $480 | |
| SQL Query Performance (TPC-DS Benchmark)(seconds) | 28 | 28 | |
| BI Tool Native Connectors(count) | 150+ | 150+ | |
| Maximum Concurrent Queries Per Warehouse(queries) | 8-128 (warehouse-dependent) | 8-128 (warehouse-dependent) | |
| Customer Satisfaction Rating (G2 2025)(percent) | 85% | 85% | |
| Setup Complexity (1-10 scale)(scale) | 4 | 4 |
Sourced from publicly available data ·
Key Differences
7 attributes compared head-to-head
AR
1Amazon RedshiftSnowflake leads
Amazon Redshift
Attribute
Snowflake
- AWS onlyCloud Platform SupportAWS, Azure, GCP(winner)
- Coupled (requires resize)Compute-Storage SeparationFully decoupled (independent scaling)(winner)
- $180,000-220,000(winner)Average Total Cost of Ownership (annual, 100TB)$240,000-280,000
- 42 seconds averageQuery Performance (TPC-DS benchmark, 100GB)38 seconds average(winner)
- Moderate (requires tuning)Setup & Configuration ComplexityMinimal (auto-configured)(winner)
- Up to 50 simultaneouslyConcurrent Users Support (Standard tier)Unlimited (elastic scaling)(winner)
- Basic (limited ecosystem)Data Sharing CapabilitiesAdvanced (Snowflake Marketplace)(winner)
- Cloud Platform Support
Amazon Redshift
AWS only
Snowflake
AWS, Azure, GCP(winner)
- Compute-Storage Separation
Amazon Redshift
Coupled (requires resize)
Snowflake
Fully decoupled (independent scaling)(winner)
- Average Total Cost of Ownership (annual, 100TB)
Amazon Redshift
$180,000-220,000(winner)
Snowflake
$240,000-280,000
- Query Performance (TPC-DS benchmark, 100GB)
Amazon Redshift
42 seconds average
Snowflake
38 seconds average(winner)
- Setup & Configuration Complexity
Amazon Redshift
Moderate (requires tuning)
Snowflake
Minimal (auto-configured)(winner)
- Concurrent Users Support (Standard tier)
Amazon Redshift
Up to 50 simultaneously
Snowflake
Unlimited (elastic scaling)(winner)
- Data Sharing Capabilities
Amazon Redshift
Basic (limited ecosystem)
Snowflake
Advanced (Snowflake Marketplace)(winner)
Full Comparison
| Attribute | Amazon Redshift | Snowflake |
|---|---|---|
| Query Latency (p99)(milliseconds) | 8000ms | — |
| Data Ingestion Rate(events per second) | 50,000 | Batch-based (bulk loading) |
| Query Latency (Average)(milliseconds) | 1-10 seconds | — |
| Query Latency (1B row scan, 10 column aggregate)(milliseconds) | 500-2000ms | — |
| Query Performance (TPC-DS 100GB)(seconds) | ~16 seconds | ~14 seconds(winner) |
Show 17 more attributesTPC-DS Query Benchmark (100GB dataset)(seconds) 42 38 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 — 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(minutes) 0.3-0.5 weeks (1-2 days) — Query Response Time (10TB scan)(seconds) 8.2 — Query Latency (Typical)(milliseconds) 1,000-10,000ms — 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 — SQL Query Performance (TPC-DS Benchmark)(seconds) 28 — Maximum Concurrent Queries Per Warehouse(queries) 8-128 (warehouse-dependent) — | ||
| Typical Query Cost (per TB scanned)(USD) | $1.50-$5.00 | — |
| Base Monthly Cost (Small Cluster)(USD) | $2,160-8,640 (dc2.large, 2-4 nodes) | — |
| Annual TCO (100TB storage, average usage)(USD) | $200,000(winner) | $260,000 |
| Annual Cost (100TB storage, 10 users)(USD) | $120,000-180,000 | — |
| Setup Time (to production)(days) | 1-3 | — |
| Scaling Adjustment Time(minutes) | 10-15 (requires cluster resize + restart) | ~1 (auto-scaling, no downtime)(winner) |
| Configuration Tuning Required(hours (estimated)) | 40-80 (distribution keys, sort keys, vacuum) | 4-8 (clustering hints optional)(winner) |
| Operational Complexity (1-10 scale)(score) | 3/10 (managed cloud service) | — |
| Supported Data Retention(duration) | Unlimited historical storage | — |
| SQL Standard Compliance(percent) | 95% (PostgreSQL-compatible) | 95% (full ANSI) |
| Typical Memory Per Node(GB) | 160-256 | — |
| Maximum Cluster Size(petabytes) | Petabyte scale | — |
| Maximum Concurrent Users(users) | 50 (standard) | Unlimited |
| Maximum Scalability(petabytes) | Up to 50+ PB (cloud limits) | — |
| Maximum Daily Data Volume(terabytes) | Unlimited (petabyte-scale) | — |
| Concurrent Users Support(users) | Unlimited (multi-cluster shared warehouse) | — |
| Data Freshness(seconds) | Minutes to hours typical | — |
| Ingestion Streaming Support(events per second) | Limited via Kinesis/S3 batch | — |
| Concurrent User Support(users) | 2,000+ | — |
| License Type | AWS Proprietary Managed Service | — |
| Deployment Flexibility | AWS only | — |
| Minimum Cluster Size (nodes)(nodes) | 2 (minimum production) | — |
| Cloud Platform Support | AWS only | AWS, Azure, GCP |
| Supported Cloud Providers(number of platforms) | 3 (AWS, Azure, GCP) | — |
| Available Cloud Providers(count) | AWS, Azure, GCP | — |
| Storage Cost (per TB/month)(USD) | Included in node cost(winner) | $23 (on-demand) |
| Base Hourly Cost (2-node cluster)(USD/hour) | $0.50 (DC2.large)(winner) | $4.00-$6.00 (Medium warehouse) |
| Annual Contract Discount(percent) | Up to 30%(winner) | Up to 20% |
| Reserved Instance Discount(percent) | 70%(winner) | None (on-demand only) |
| Starting Monthly Cost(USD) | $2,000-$5,000 | — |
Show 8 more attributesBase 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 — Annual License Cost (100TB data)(USD) $240,000 — Base Setup Cost (Annual)(USD) $10,000-1,000,000 (credits-based) — Base Monthly Cost (minimum)(USD) $120-240 — Starting Monthly Cost (10GB active data)(USD) $480 — | ||
| Typical Data Compression Ratio(x) | 4-8x | — |
| Max Concurrent Queries (default config)(queries) | 32 (base, expandable via Concurrency Scaling) | — |
| Data Ingestion Latency(milliseconds) | Batch (minutes to hours typical) | — |
| AWS Service Integration (native)(count) | 20+ (native connectors) | — |
| Data Marketplace Size(datasets) | ~200 (limited) | 1,500+(winner) |
| Available Integrations(count) | 600+ | — |
| GitHub Stars (as of 2026)(stars) | Not open-source (proprietary) | — |
| Maximum Single Query Data Scanned(petabytes) | 100+(winner) | 20+ |
| Cloud Providers Supported(count) | 1 (AWS only) | 3 (AWS, Azure, GCP)(winner) |
| Setup Time to First Query(minutes) | 20-30 minutes | — |
| Setup Time to Production(hours) | 40-60 hours | 10-15 hours(winner) |
| Time to Production (median)(weeks) | 1-3 weeks | — |
| Time to First Query (production)(days) | 1-3 days | — |
| Compute-Storage Decoupling | Coupled (scale together) | Independent scaling |
| Compute-Storage Decoupling | Complete separation | — |
| Deployment Options | SaaS only (AWS/Azure/GCP) | — |
| Setup Time(minutes) | 1-3 days | — |
| Customer Satisfaction Rating (G2 2025)(percent) | 85% | — |
| ML/AI Integration Score(out of 10) | 4/10 | — |
| Native ML Framework Integration | Cortex AI (basic) | — |
| Global Enterprise Customers(count (2026)) | 10,000+ | — |
| Market Share 2026(percent) | 32% | — |
| Global Market Share (2024)(percent) | 32% of cloud data warehouse market | — |
| Supported Data Formats(types) | Structured (Parquet, CSV, JSON) | — |
| Data Format Support(format types) | Structured (optimized for tables/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) | — |
Show 1 more attributeNative ML/AI Capabilities Limited (external integration required) — | ||
| Multi-Language Support(languages) | SQL primarily | — |
| Data Marketplace Size(number of datasets) | 1,000+ datasets | — |
| Annual Customer Growth Rate (2025)(percent) | 22% YoY | — |
| Setup Time(minutes) | 15 minutes | — |
| Time to Production(minutes) | 0.5 | — |
| Data Warehouse Setup Time(minutes) | 5-10 minutes | — |
| Setup Complexity (1-10 scale)(scale) | 4 | — |
| Compression Ratio(ratio) | 4:1 to 8:1 | — |
| Licensing Model | Consumption-based (compute + storage) | — |
| Learning Curve (1-10 Scale)(scale) | 3/10 (very easy) | — |
| Supported Query Languages(count) | SQL, Python, Java, JavaScript, Scala | — |
| Required Technical Expertise Level(years experience needed) | 1-2 years (SQL knowledge) | — |
| Real-time Analytics Capability | Yes (sub-second latency) | — |
| Uptime SLA Guarantee(%) | 99.99% | — |
| Enterprise Customers (2025)(count) | ~10,000 enterprises | — |
| ML Model Training Cost Efficiency(relative cost index) | 2.8x baseline (external ML tools required) | — |
| Initial Setup Time(hours) | 30-45 minutes | — |
| Data Format Lock-in Risk | High (proprietary format) | — |
| BI Tool Native Connectors(count) | 150+ | — |
AAmazon Redshift
SnowflakeQuery Latency (p99)(milliseconds)
8000ms
—
Data Ingestion Rate(events per second)
50,000
Batch-based (bulk loading)
Query Latency (Average)(milliseconds)
1-10 seconds
—
Query Latency (1B row scan, 10 column aggregate)(milliseconds)
500-2000ms
—
Query Performance (TPC-DS 100GB)(seconds)
~16 seconds
~14 seconds
Show 17 more attributes
TPC-DS Query Benchmark (100GB dataset)(seconds)
42
38
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
—
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(minutes)
0.3-0.5 weeks (1-2 days)
—
Query Response Time (10TB scan)(seconds)
8.2
—
Query Latency (Typical)(milliseconds)
1,000-10,000ms
—
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
—
SQL Query Performance (TPC-DS Benchmark)(seconds)
28
—
Maximum Concurrent Queries Per Warehouse(queries)
8-128 (warehouse-dependent)
—
Typical Query Cost (per TB scanned)(USD)
$1.50-$5.00
—
Base Monthly Cost (Small Cluster)(USD)
$2,160-8,640 (dc2.large, 2-4 nodes)
—
Annual TCO (100TB storage, average usage)(USD)
$200,000
$260,000
Annual Cost (100TB storage, 10 users)(USD)
$120,000-180,000
—
Setup Time (to production)(days)
1-3
—
Scaling Adjustment Time(minutes)
10-15 (requires cluster resize + restart)
~1 (auto-scaling, no downtime)
Configuration Tuning Required(hours (estimated))
40-80 (distribution keys, sort keys, vacuum)
4-8 (clustering hints optional)
Operational Complexity (1-10 scale)(score)
3/10 (managed cloud service)
—
Supported Data Retention(duration)
Unlimited historical storage
—
SQL Standard Compliance(percent)
95% (PostgreSQL-compatible)
95% (full ANSI)
Typical Memory Per Node(GB)
160-256
—
Maximum Cluster Size(petabytes)
Petabyte scale
—
Maximum Concurrent Users(users)
50 (standard)
Unlimited
Maximum Scalability(petabytes)
Up to 50+ PB (cloud limits)
—
Maximum Daily Data Volume(terabytes)
Unlimited (petabyte-scale)
—
Concurrent Users Support(users)
Unlimited (multi-cluster shared warehouse)
—
Data Freshness(seconds)
Minutes to hours typical
—
Ingestion Streaming Support(events per second)
Limited via Kinesis/S3 batch
—
Concurrent User Support(users)
2,000+
—
License Type
AWS Proprietary Managed Service
—
Deployment Flexibility
AWS only
—
Minimum Cluster Size (nodes)(nodes)
2 (minimum production)
—
Cloud Platform Support
AWS only
AWS, Azure, GCP
Supported Cloud Providers(number of platforms)
3 (AWS, Azure, GCP)
—
Available Cloud Providers(count)
AWS, Azure, GCP
—
Storage Cost (per TB/month)(USD)
Included in node cost
$23 (on-demand)
Base Hourly Cost (2-node cluster)(USD/hour)
$0.50 (DC2.large)
$4.00-$6.00 (Medium warehouse)
Annual Contract Discount(percent)
Up to 30%
Up to 20%
Reserved Instance Discount(percent)
70%
None (on-demand only)
Starting Monthly Cost(USD)
$2,000-$5,000
—
Show 8 more attributes
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
—
Annual License Cost (100TB data)(USD)
$240,000
—
Base Setup Cost (Annual)(USD)
$10,000-1,000,000 (credits-based)
—
Base Monthly Cost (minimum)(USD)
$120-240
—
Starting Monthly Cost (10GB active data)(USD)
$480
—
Typical Data Compression Ratio(x)
4-8x
—
Max Concurrent Queries (default config)(queries)
32 (base, expandable via Concurrency Scaling)
—
Data Ingestion Latency(milliseconds)
Batch (minutes to hours typical)
—
AWS Service Integration (native)(count)
20+ (native connectors)
—
Data Marketplace Size(datasets)
~200 (limited)
1,500+
Available Integrations(count)
600+
—
GitHub Stars (as of 2026)(stars)
Not open-source (proprietary)
—
Maximum Single Query Data Scanned(petabytes)
100+
20+
Cloud Providers Supported(count)
1 (AWS only)
3 (AWS, Azure, GCP)
Setup Time to First Query(minutes)
20-30 minutes
—
Setup Time to Production(hours)
40-60 hours
10-15 hours
Time to Production (median)(weeks)
1-3 weeks
—
Time to First Query (production)(days)
1-3 days
—
Compute-Storage Decoupling
Coupled (scale together)
Independent scaling
Compute-Storage Decoupling
Complete separation
—
Deployment Options
SaaS only (AWS/Azure/GCP)
—
Setup Time(minutes)
1-3 days
—
Customer Satisfaction Rating (G2 2025)(percent)
85%
—
ML/AI Integration Score(out of 10)
4/10
—
Native ML Framework Integration
Cortex AI (basic)
—
Global Enterprise Customers(count (2026))
10,000+
—
Market Share 2026(percent)
32%
—
Global Market Share (2024)(percent)
32% of cloud data warehouse market
—
Supported Data Formats(types)
Structured (Parquet, CSV, JSON)
—
Data Format Support(format types)
Structured (optimized for tables/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)
—
Show 1 more attribute
Native ML/AI Capabilities
Limited (external integration required)
—
Multi-Language Support(languages)
SQL primarily
—
Data Marketplace Size(number of datasets)
1,000+ datasets
—
Annual Customer Growth Rate (2025)(percent)
22% YoY
—
Setup Time(minutes)
15 minutes
—
Time to Production(minutes)
0.5
—
Data Warehouse Setup Time(minutes)
5-10 minutes
—
Setup Complexity (1-10 scale)(scale)
4
—
Compression Ratio(ratio)
4:1 to 8:1
—
Licensing Model
Consumption-based (compute + storage)
—
Learning Curve (1-10 Scale)(scale)
3/10 (very easy)
—
Supported Query Languages(count)
SQL, Python, Java, JavaScript, Scala
—
Required Technical Expertise Level(years experience needed)
1-2 years (SQL knowledge)
—
Real-time Analytics Capability
Yes (sub-second latency)
—
Uptime SLA Guarantee(%)
99.99%
—
Enterprise Customers (2025)(count)
~10,000 enterprises
—
ML Model Training Cost Efficiency(relative cost index)
2.8x baseline (external ML tools required)
—
Initial Setup Time(hours)
30-45 minutes
—
Data Format Lock-in Risk
High (proprietary format)
—
BI Tool Native Connectors(count)
150+
—
Pros & Cons
11 pros·6 cons across both
AR
AR
Amazon Redshift
+5-3
Pros
- 25-35% lower total cost of ownership compared to competitors
- Excellent performance on complex analytical queries (42-second TPC-DS benchmark)
- Deep AWS ecosystem integration (S3, Lambda, QuickSight, IAM)
- Mature platform with 12+ years of production deployments
- Reserved instance pricing offers up to 70% savings vs. on-demand
Cons
- Locked into AWS; multi-cloud strategies require architectural changes
- Compute and storage must be scaled together, leading to resource inefficiency during variable workloads
- Requires significant tuning and schema optimization for optimal performance
Snowflake
+6-3
Pros
- Fully independent compute and storage scaling eliminates resource waste
- Multi-cloud deployment (AWS, Azure, GCP) enables vendor lock-in prevention
- Minimal setup with automatic optimization; 75% faster time-to-productivity vs. Redshift
- Unlimited concurrent users through elastic clustering
- Snowflake Marketplace enables secure data collaboration with 1,500+ datasets available
- Native support for semi-structured data (JSON, Parquet, Avro)
Cons
- 30-40% higher baseline costs than Redshift (approximately $240K-280K annual for 100TB)
- Compute-centric pricing model means costs surge during intensive analysis periods
- Smaller ecosystem compared to AWS; fewer pre-built integrations
Frequently Asked Questions
5 questions
Redshift is 25-35% cheaper on average. For a 100TB data warehouse with typical usage, Redshift costs ~$200K annually vs. Snowflake's ~$260K. However, Snowflake's elastic scaling can be more cost-effective for highly variable workloads, as you pay only for compute actually used, whereas Redshift charges for provisioned capacity regardless of utilization.
Resources & Learn More
Curated sources to dive deeper
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