software
Druid vs Snowflake 2026: Real-Time OLAP vs Data Warehouse
Druid is a real-time OLAP database optimized for sub-second analytics on streaming data, while Snowflake is a cloud data warehouse designed for batch processing and complex SQL queries on large datasets. Druid excels at time-series and event data analysis, whereas Snowflake is better for enterprise data consolidation and reporting.
AD
Apache Druid
Open-source real-time OLAP database for streaming analytics and time-series data.
Real-time monitoring, IoT analytics, clickstream analysis, financial market data feeds, and organizations that need sub-second response times on high-volume event streams.
Score63%
VS
Snowflake
Cloud-native data warehouse with separation of compute and storage, SQL-first design.
Enterprise data consolidation, BI reporting, data lakes, complex analytical queries, organizations prioritizing minimal ops overhead, and teams requiring ANSI SQL compatibility.
Score63%
Quick Answer
AI SummaryDruid is a real-time OLAP database optimized for sub-second analytics on streaming data, while Snowflake is a cloud data warehouse designed for batch processing and complex SQL queries on large datasets. Druid excels at time-series and event data analysis, whereas Snowflake is better for enterprise data consolidation and reporting.
Our Verdict
AI-assistedChoose Druid if you need real-time analytics on streaming or time-series data with sub-second latency and want control over infrastructure costs. Choose Snowflake if you require a fully managed cloud data warehouse for enterprise SQL analytics, complex joins across large datasets, and minimal operational overhead.
Community feedback
Was this verdict helpful?
Thanks — we'll use this to improve our verdicts.
A
Apache Druid
7.1/10
Snowflake
7.9/10
A
Choose Apache Druid if
Real-time monitoring, IoT analytics, clickstream analysis, financial market data feeds, and organizations that need sub-second response times on high-volume event streams.
Choose Snowflake if
Best pickEnterprise data consolidation, BI reporting, data lakes, complex analytical queries, organizations prioritizing minimal ops overhead, and teams requiring ANSI SQL compatibility.
Track this comparison
Get notified when prices change, new specs ship, or our verdict updates.
Triggers: price change new spec verdict update
No spam. Stop anytime.
Key Differences at a Glance
- Primary Use Case:Real-time OLAP analytics & time-series data vs Cloud data warehouse & batch processing
- Query Latency (P99):✓ Apache Druid wins(100-500ms for typical queries vs 1-5 seconds for typical queries)
- Data Ingestion Rate:✓ Apache Druid wins(1M+ events/second vs 500K+ rows/second (Snowpipe))
Key Facts & Figures
100 numeric metrics compared
| Metric | Apache Druid | Snowflake | Ratio |
|---|---|---|---|
| Query Latency (1B rows, 100 dimensions)(milliseconds) | 50-150ms | — | — |
| Memory Footprint per 1GB Data(MB) | 600-900MB | — | — |
| Maximum Events/Sec per Node(events/sec) | 100K-500K | — | — |
| Typical Cluster Setup Cost(USD/month (3-node)) | $2500-5000 | — | — |
| Enterprise Deployments(thousands) | 500+ (Airbnb, Netflix, etc) | — | — |
| Query Latency (p95 on Real-Time Data)(milliseconds) | 100-500ms | — | — |
| Minimum Cluster Size for 1TB Dataset(nodes) | 3-5 nodes | — | — |
| GitHub Stars (Community Activity)(count) | 15,800 | — | — |
| Storage Compression Ratio(x reduction) | ~10x with roll-ups | — | — |
| Max Ingestion Throughput(events/second) | 500,000 | — | — |
| Query Latency (50th percentile)(milliseconds) | 150 | — | — |
| Data Compression Ratio (metrics)(ratio) | 10:1 | — | — |
| GitHub Stars(stars) | 15,200 | — | — |
| Minimum Cluster Node Count(nodes) | 3 | — | — |
| Third-Party Integrations(integrations) | 300+ | — | — |
| Memory Overhead (1M events)(MB per node) | 120 | — | — |
| Query Latency (p99)(milliseconds) | 500ms | — | — |
| Data Ingestion Rate(GB/sec) | 1,000,000 | Batch-based (bulk loading) | — |
| Typical Query Cost (per TB scanned)(USD) | $0.10-$0.50 | — | — |
| Setup Time (to production)(days) | 14-30 | — | — |
| SQL Standard Compliance(percent) | ~60% ANSI SQL | 95% (full ANSI) | |
| Typical Memory Per Node(GB) | 16-64 | — | — |
| P99 Query Latency(milliseconds) | 5-50ms | — | — |
| Median Query Latency(milliseconds) | 10-100ms | — | — |
| Data Ingestion Latency(seconds) | 1-5 seconds (streaming) | — | — |
| Maximum Dataset Size Supported(petabytes) | Petabyte+ (with cluster scaling) | — | — |
| Query Latency (P99 percentile)(milliseconds) | 250ms | 2500ms | |
| Maximum Ingestion Rate(events/second) | 1,000,000+ | 500,000 | |
| Storage Cost(USD per TB per month) | $5 (self-hosted avg) | $50 | |
| Concurrent Query Capacity(concurrent users) | 300 | 1000+ | |
| Time to First Query(minutes) | 45 (self-hosted setup) | 5 (account creation) | |
| Minimum Cluster Size(nodes) | 3 (recommended) | 1 (virtual warehouse) | |
| 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)(difficulty) | 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(months) | 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(percent) | 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)(complexity 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)(%) | 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(minutes) | 30-45 minutes | 30-45 minutes | |
| TPC-DS 100TB Query Performance(seconds) | 38 seconds | 38 seconds | |
| Base Hourly Cost (2-node cluster)(USD/hour) | $4.00-$6.00 (Medium warehouse) | $4.00-$6.00 (Medium warehouse) | |
| Storage Cost (per TB/month)(USD) | $23 (on-demand) | $23 (on-demand) | |
| Query Performance (TPC-DS 100GB)(seconds) | ~14 seconds | ~14 seconds | |
| Scaling Adjustment Time(minutes) | ~1 (auto-scaling, no downtime) | ~1 (auto-scaling, no downtime) | |
| Maximum Single Query Data Scanned(petabytes) | 20+ | 20+ | |
| Cloud Providers Supported(count) | 3 (AWS, Azure, GCP) | 3 (AWS, Azure, GCP) | |
| Annual Contract Discount(percent) | Up to 20% | Up to 20% | |
| Configuration Tuning Required(hours (estimated)) | 4-8 (clustering hints optional) | 4-8 (clustering hints optional) | |
| 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)(score) | 4 | 4 | |
| Annual TCO (100TB storage, average usage)(USD) | $260,000 | $260,000 | |
| TPC-DS Query Benchmark (100GB dataset)(seconds) | 38 | 38 | |
| Setup Time to Production(minutes) | 10-15 hours | 10-15 hours | |
| Data Marketplace Size(datasets) | 1,500+ | 1,500+ | |
| Reserved Instance Discount(percent) | None (on-demand only) | None (on-demand only) |
Sourced from publicly available data ·
Key Differences
7 attributes compared head-to-head
AD
4Apache DruidApache Druid leads1 tie
Apache Druid
Attribute
Snowflake
- Real-time OLAP analytics & time-series dataPrimary Use CaseCloud data warehouse & batch processing
- 100-500ms for typical queries(winner)Query Latency (P99)1-5 seconds for typical queries
- 1M+ events/second(winner)Data Ingestion Rate500K+ rows/second (Snowpipe)
- Self-hosted or cloud (open-source available)(winner)Deployment ModelCloud-only (SaaS)
- $3-8 (self-hosted infrastructure)(winner)Storage Cost (per TB/month)$40-60 (on-demand pricing)
- Native Druid SQL + proprietary extensionsSQL Dialect SupportANSI SQL compliant(winner)
- 100-500 concurrent queriesConcurrent Users at Scale1000+ concurrent queries(winner)
- Primary Use Case
Apache Druid
Real-time OLAP analytics & time-series data
Snowflake
Cloud data warehouse & batch processing
- Query Latency (P99)
Apache Druid
100-500ms for typical queries(winner)
Snowflake
1-5 seconds for typical queries
- Data Ingestion Rate
Apache Druid
1M+ events/second(winner)
Snowflake
500K+ rows/second (Snowpipe)
- Deployment Model
Apache Druid
Self-hosted or cloud (open-source available)(winner)
Snowflake
Cloud-only (SaaS)
- Storage Cost (per TB/month)
Apache Druid
$3-8 (self-hosted infrastructure)(winner)
Snowflake
$40-60 (on-demand pricing)
- SQL Dialect Support
Apache Druid
Native Druid SQL + proprietary extensions
Snowflake
ANSI SQL compliant(winner)
- Concurrent Users at Scale
Apache Druid
100-500 concurrent queries
Snowflake
1000+ concurrent queries(winner)
Full Comparison
| Attribute | Apache Druid | Snowflake |
|---|---|---|
| Query Latency (1B rows, 100 dimensions)(milliseconds) | 50-150ms | — |
| Query Latency (p95 on Real-Time Data)(milliseconds) | 100-500ms | — |
| Storage Compression Ratio(x reduction) | ~10x with roll-ups | — |
| Max Ingestion Throughput(events/second) | 500,000 | — |
| Query Latency (50th percentile)(milliseconds) | 150 | — |
Show 23 more attributesQuery Latency (p99)(milliseconds) 500ms — Data Ingestion Rate(GB/sec) 1,000,000 Batch-based (bulk loading) P99 Query Latency(milliseconds) 5-50ms — Median Query Latency(milliseconds) 10-100ms — Data Ingestion Latency(seconds) 1-5 seconds (streaming) — Query Latency (P99 percentile)(milliseconds) 250ms 2500ms 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 — 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 — 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 — | ||
| Memory Footprint per 1GB Data(MB) | 600-900MB | — |
| Typical Memory Per Node(GB) | 16-64 | — |
| Maximum Events/Sec per Node(events/sec) | 100K-500K | — |
| Typical Cluster Setup Cost(USD/month (3-node)) | $2500-5000 | — |
| Licensing Model | Consumption-based (compute + storage) | — |
| Multi-table JOIN Support(capability level) | Limited (requires denormalization) | — |
| SQL Compatibility(percentage) | Custom JSON/Druid QL | — |
| Typical Use Case Flexibility | Real-time metrics (specialized) | — |
| JOIN Operation Support | Limited (basic) | — |
| Full-Text Search Capability | Basic (limited analyzers) | — |
| SQL Standard Compliance(percent) | ~60% ANSI SQL | 95% (full ANSI)(winner) |
Show 6 more attributesData 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) — Native ML/AI Capabilities Limited (external integration required) — | ||
| Enterprise Deployments(thousands) | 500+ (Airbnb, Netflix, etc) | — |
| Global Enterprise Customers(count (2026)) | 10,000+ | — |
| Market Share 2026(percent) | 32% | — |
| Global Market Share (2024)(%) | 32% of cloud data warehouse market | — |
| Minimum Cluster Size for 1TB Dataset(nodes) | 3-5 nodes | — |
| Deployment Options | Self-hosted, cloud, hybrid, open-source | Cloud-only (SaaS) |
| Minimum Cluster Size(nodes) | 3 (recommended) | 1 (virtual warehouse)(winner) |
| Supported Cloud Providers(number of platforms) | 3 (AWS, Azure, GCP) | — |
| Available Cloud Providers(count) | AWS, Azure, GCP | — |
Show 1 more attributeCloud Platform Support AWS, Azure, GCP — | ||
| Native SQL Support | Druid SQL (Full) | — |
| GitHub Stars (Community Activity)(count) | 15,800 | — |
| GitHub Stars(stars) | 15,200 | — |
| Data Compression Ratio (metrics)(ratio) | 10:1 | — |
| Compression Ratio(ratio) | 4:1 to 8:1 | — |
| Minimum Cluster Node Count(nodes) | 3 | — |
| Setup Time (to production)(days) | 14-30 | — |
| Operational Management Overhead(text) | High (cluster tuning, scaling, monitoring) | — |
| Scaling Adjustment Time(minutes) | ~1 (auto-scaling, no downtime) | — |
| Configuration Tuning Required(hours (estimated)) | 4-8 (clustering hints optional) | — |
| Third-Party Integrations(integrations) | 300+ | — |
| Available Integrations(count) | 600+ | — |
| Data Marketplace Size(datasets) | 1,500+ | — |
| Memory Overhead (1M events)(MB per node) | 120 | — |
| Maximum Cluster Size(petabytes) | Unlimited (distributed) | — |
| Maximum Dataset Size Supported(petabytes) | Petabyte+ (with cluster scaling) | — |
| Concurrent Query Capacity(concurrent users) | 300 | 1000+(winner) |
| Maximum Scalability(petabytes) | Up to 50+ PB (cloud limits) | — |
| Maximum Concurrent Users(users) | Unlimited | — |
Show 2 more attributesMaximum Daily Data Volume(terabytes) Unlimited (petabyte-scale) — Concurrent Users Support(users) Unlimited (multi-cluster shared warehouse) — | ||
| Typical Query Cost (per TB scanned)(USD) | $0.10-$0.50 | — |
| Query Cost (On-Demand)(USD per TB scanned) | Included in storage/infrastructure | — |
| Annual Cost (100TB storage, 10 users)(USD) | $120,000-180,000 | — |
| Annual TCO (100TB storage, average usage)(USD) | $260,000 | — |
| Supported Data Retention(duration) | Time-window based (7 days to 3 years typical) | — |
| Maximum Ingestion Rate(events/second) | 1,000,000+(winner) | 500,000 |
| Storage Cost(USD per TB per month) | $5 (self-hosted avg)(winner) | $50 |
| 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 | — |
Show 9 more attributesMonthly 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 — Base Hourly Cost (2-node cluster)(USD/hour) $4.00-$6.00 (Medium warehouse) — Storage Cost (per TB/month)(USD) $23 (on-demand) — Annual Contract Discount(percent) Up to 20% — Starting Monthly Cost (10GB active data)(USD) $480 — Reserved Instance Discount(percent) None (on-demand only) — | ||
| SQL Compliance | Proprietary Druid SQL with extensions | ANSI SQL compliant |
| Time to First Query(minutes) | 45 (self-hosted setup) | 5 (account creation)(winner) |
| Setup Time(minutes) | 1-3 days | — |
| Initial Setup Time(minutes) | 30-45 minutes | — |
| Customer Satisfaction Rating (G2 2025)(percent) | 85% | — |
| ML/AI Integration Score(out of 10) | 4/10 | — |
| Native ML Framework Integration | Cortex AI (basic) | — |
| Supported Data Formats(types) | Structured (Parquet, CSV, JSON) | — |
| Data Format Support(format types) | Structured (optimized for tables/CSV/JSON) | — |
| Multi-Language Support(languages) | SQL primarily | — |
| Setup Time to First Query(minutes) | 20-30 minutes | — |
| Setup Time(minutes) | 15 minutes | — |
| Time to Production(minutes) | 0.5 | — |
| Cloud Providers Supported(count) | 3 (AWS, Azure, GCP) | — |
| Setup Complexity (1-10 scale)(score) | 4 | — |
Show 1 more attributeSetup Time to Production(minutes) 10-15 hours — | ||
| Data Marketplace Size(number of datasets) | 1,000+ datasets | — |
| Annual Customer Growth Rate (2025)(percent) | 22% YoY | — |
| Compute-Storage Decoupling | Complete separation | — |
| Compute-Storage Decoupling | Independent scaling | — |
| Time to Production (median)(weeks) | 1-3 weeks | — |
| Time to First Query (production)(days) | 1-3 days | — |
| Learning Curve (1-10 scale)(difficulty) | 3/10 (very easy) | — |
| Deployment Time(months) | 0.3-0.5 weeks (1-2 days) | — |
| 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(percent) | 99.99% | — |
| 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 | — |
| ML Model Training Cost Efficiency(relative cost index) | 2.8x baseline (external ML tools required) | — |
| Maximum Single Query Data Scanned(petabytes) | 20+ | — |
| Data Format Lock-in Risk | High (proprietary format) | — |
| BI Tool Native Connectors(count) | 150+ | — |
AApache Druid
SnowflakeQuery Latency (1B rows, 100 dimensions)(milliseconds)
50-150ms
—
Query Latency (p95 on Real-Time Data)(milliseconds)
100-500ms
—
Storage Compression Ratio(x reduction)
~10x with roll-ups
—
Max Ingestion Throughput(events/second)
500,000
—
Query Latency (50th percentile)(milliseconds)
150
—
Show 23 more attributes
Query Latency (p99)(milliseconds)
500ms
—
Data Ingestion Rate(GB/sec)
1,000,000
Batch-based (bulk loading)
P99 Query Latency(milliseconds)
5-50ms
—
Median Query Latency(milliseconds)
10-100ms
—
Data Ingestion Latency(seconds)
1-5 seconds (streaming)
—
Query Latency (P99 percentile)(milliseconds)
250ms
2500ms
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
—
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
—
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
—
Memory Footprint per 1GB Data(MB)
600-900MB
—
Typical Memory Per Node(GB)
16-64
—
Maximum Events/Sec per Node(events/sec)
100K-500K
—
Typical Cluster Setup Cost(USD/month (3-node))
$2500-5000
—
Licensing Model
Consumption-based (compute + storage)
—
Multi-table JOIN Support(capability level)
Limited (requires denormalization)
—
SQL Compatibility(percentage)
Custom JSON/Druid QL
—
Typical Use Case Flexibility
Real-time metrics (specialized)
—
JOIN Operation Support
Limited (basic)
—
Full-Text Search Capability
Basic (limited analyzers)
—
SQL Standard Compliance(percent)
~60% ANSI SQL
95% (full ANSI)
Show 6 more attributes
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)
—
Native ML/AI Capabilities
Limited (external integration required)
—
Enterprise Deployments(thousands)
500+ (Airbnb, Netflix, etc)
—
Global Enterprise Customers(count (2026))
10,000+
—
Market Share 2026(percent)
32%
—
Global Market Share (2024)(%)
32% of cloud data warehouse market
—
Minimum Cluster Size for 1TB Dataset(nodes)
3-5 nodes
—
Deployment Options
Self-hosted, cloud, hybrid, open-source
Cloud-only (SaaS)
Minimum Cluster Size(nodes)
3 (recommended)
1 (virtual warehouse)
Supported Cloud Providers(number of platforms)
3 (AWS, Azure, GCP)
—
Available Cloud Providers(count)
AWS, Azure, GCP
—
Show 1 more attribute
Cloud Platform Support
AWS, Azure, GCP
—
Native SQL Support
Druid SQL (Full)
—
GitHub Stars (Community Activity)(count)
15,800
—
GitHub Stars(stars)
15,200
—
Data Compression Ratio (metrics)(ratio)
10:1
—
Compression Ratio(ratio)
4:1 to 8:1
—
Minimum Cluster Node Count(nodes)
3
—
Setup Time (to production)(days)
14-30
—
Operational Management Overhead(text)
High (cluster tuning, scaling, monitoring)
—
Scaling Adjustment Time(minutes)
~1 (auto-scaling, no downtime)
—
Configuration Tuning Required(hours (estimated))
4-8 (clustering hints optional)
—
Third-Party Integrations(integrations)
300+
—
Available Integrations(count)
600+
—
Data Marketplace Size(datasets)
1,500+
—
Memory Overhead (1M events)(MB per node)
120
—
Maximum Cluster Size(petabytes)
Unlimited (distributed)
—
Maximum Dataset Size Supported(petabytes)
Petabyte+ (with cluster scaling)
—
Concurrent Query Capacity(concurrent users)
300
1000+
Maximum Scalability(petabytes)
Up to 50+ PB (cloud limits)
—
Maximum Concurrent Users(users)
Unlimited
—
Show 2 more attributes
Maximum Daily Data Volume(terabytes)
Unlimited (petabyte-scale)
—
Concurrent Users Support(users)
Unlimited (multi-cluster shared warehouse)
—
Typical Query Cost (per TB scanned)(USD)
$0.10-$0.50
—
Query Cost (On-Demand)(USD per TB scanned)
Included in storage/infrastructure
—
Annual Cost (100TB storage, 10 users)(USD)
$120,000-180,000
—
Annual TCO (100TB storage, average usage)(USD)
$260,000
—
Supported Data Retention(duration)
Time-window based (7 days to 3 years typical)
—
Maximum Ingestion Rate(events/second)
1,000,000+
500,000
Storage Cost(USD per TB per month)
$5 (self-hosted avg)
$50
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
—
Show 9 more attributes
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
—
Base Hourly Cost (2-node cluster)(USD/hour)
$4.00-$6.00 (Medium warehouse)
—
Storage Cost (per TB/month)(USD)
$23 (on-demand)
—
Annual Contract Discount(percent)
Up to 20%
—
Starting Monthly Cost (10GB active data)(USD)
$480
—
Reserved Instance Discount(percent)
None (on-demand only)
—
SQL Compliance
Proprietary Druid SQL with extensions
ANSI SQL compliant
Time to First Query(minutes)
45 (self-hosted setup)
5 (account creation)
Setup Time(minutes)
1-3 days
—
Initial Setup Time(minutes)
30-45 minutes
—
Customer Satisfaction Rating (G2 2025)(percent)
85%
—
ML/AI Integration Score(out of 10)
4/10
—
Native ML Framework Integration
Cortex AI (basic)
—
Supported Data Formats(types)
Structured (Parquet, CSV, JSON)
—
Data Format Support(format types)
Structured (optimized for tables/CSV/JSON)
—
Multi-Language Support(languages)
SQL primarily
—
Setup Time to First Query(minutes)
20-30 minutes
—
Setup Time(minutes)
15 minutes
—
Time to Production(minutes)
0.5
—
Cloud Providers Supported(count)
3 (AWS, Azure, GCP)
—
Setup Complexity (1-10 scale)(score)
4
—
Show 1 more attribute
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
—
Compute-Storage Decoupling
Complete separation
—
Compute-Storage Decoupling
Independent scaling
—
Time to Production (median)(weeks)
1-3 weeks
—
Time to First Query (production)(days)
1-3 days
—
Learning Curve (1-10 scale)(difficulty)
3/10 (very easy)
—
Deployment Time(months)
0.3-0.5 weeks (1-2 days)
—
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(percent)
99.99%
—
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
—
ML Model Training Cost Efficiency(relative cost index)
2.8x baseline (external ML tools required)
—
Maximum Single Query Data Scanned(petabytes)
20+
—
Data Format Lock-in Risk
High (proprietary format)
—
BI Tool Native Connectors(count)
150+
—
Pros & Cons
10 pros·6 cons across both
AD
AD
Apache Druid
+5-3
Pros
- Sub-second query latency (P99: 100-500ms) for real-time dashboards
- Ingests 1M+ events/second with built-in support for streaming (Kafka, AWS Kinesis)
- Open-source with self-hosting option reduces long-term infrastructure costs by 70-80%
- Native time-series aggregations and windowing functions optimized for event data
- Horizontal scalability with no single point of failure across clusters
Cons
- Steeper learning curve with proprietary Druid SQL syntax and configuration complexity
- Limited support for complex joins and transactions compared to traditional databases
- Smaller ecosystem and community compared to established data warehouses
Snowflake
+5-3
Pros
- Fully managed SaaS with zero infrastructure maintenance and automatic scaling
- ANSI SQL compliant with native support for complex joins, CTEs, and window functions
- Separation of compute and storage allows 1000+ concurrent users without performance degradation
- Time-travel and zero-copy cloning features for data recovery and testing
- Native support for semi-structured data (JSON, Parquet) without ETL transformation
Cons
- Query latency of 1-5 seconds makes it unsuitable for real-time interactive dashboards
- Storage costs of $40-60/TB/month significantly higher than self-hosted alternatives
- Vendor lock-in: all data and queries remain within Snowflake ecosystem
Frequently Asked Questions
5 questions
Druid is significantly better for real-time dashboards. It achieves P99 query latency of 100-500ms, enabling truly interactive visualizations that update in near real-time. Snowflake's 1-5 second latency introduces noticeable delays that degrade user experience for live monitoring. Druid was purpose-built for this use case with streaming ingestion and OLAP-optimized storage.
Resources & Learn More
Curated sources to dive deeper
Where to Buy
As an affiliate, we may earn a commission from qualifying purchases at no extra cost to you. Learn more about our affiliate disclosure
Wikipedia
Related Comparisons
12 more to explore
Druid vs BigQuery
softwareSnowflake vs ClickHouse
softwareSnowflake vs Azure
softwareDruid vs Pinot
softwareDruid vs Elasticsearch
softwareDruid vs Amazon Redshift
softwareHadoop vs Snowflake
softwareDruid vs Snowflake
softwareDruid vs BigQuery
softwareSnowflake vs Dremio
softwareSnowflake vs Databricks
softwareBigQuery vs Snowflake
software
Related Articles
5 articles
- technology
Best Streaming Services in 2026: Top Picks for Every Budget & Interest
Navigating the crowded streaming landscape in 2026 can be overwhelming. We've tested and ranked the best streaming services that offer the most value, from Netflix's massive library to budget-friendly options like Tubi, helping you cut cable and find your perfect entertainment solution.
Read article - technology
Best Live TV Streaming Services & Plans for Spring 2026: Complete Buyer's Guide
Tired of overpaying for cable? Discover the best live TV streaming services and plans for Spring 2026, including YouTube TV's new genre-based packages starting at $55/month. Our comprehensive guide breaks down pricing, channels, and features to help you cut the cord.
Read article - technology
Philo in 2026: Streaming TV Service Review, Pricing & Reddit Community Insights
Explore Philo's evolution heading into 2026, including pricing tiers, channel lineup, and how it compares to competitors like Sling TV. Discover what the r/PhiloTV Reddit community thinks about the service's current offerings and future prospects.
Read article - technology
Best US Fighter Jets 2026: Top American Combat Aircraft Ranked
Discover the most advanced US fighter jets dominating the skies in 2026. From the legendary F-22 Raptor to the versatile F-35 Lightning II, we rank America's best combat aircraft based on performance, stealth, and air superiority capabilities.
Read article - technology
Philo in 2026: Pricing, Lineup & How It Compares to Sling TV
As we head into 2026, Philo continues to position itself as an affordable streaming alternative for cable TV lovers. Discover what Philo offers, how its pricing stacks up against competitors like Sling TV, and what the Reddit community thinks about its future.
Read article
Explore More
Related comparisons and categories
AI generated