Druid is a real-time OLAP database optimized for sub-second analytics on streaming data, while Redshift is a data warehouse designed for batch processing of large analytical queries. Druid excels at time-series and event data with millisecond latency, whereas Redshift offers superior query performance on petabyte-scale datasets through columnar compression.
Druid vs Amazon Redshift — Side-by-side comparison on A Versus B
Real-time OLAP database optimized for time-series analytics and streaming ingestion.
AWS-native MPP data warehouse optimized for large-scale batch analytics and predictable workloads.
Query Latency. Primary Use Case. Data Ingestion Rate. Typical Cluster Cost (Monthly). Data Retention Model. Ease of Setup. SQL Dialect Support
Choose Druid if you need real-time dashboards, live event streaming analytics, or sub-second query latency on time-series data—it's built for speed on incoming data. Choose Redshift if you're running a traditional data warehouse with complex analytical queries on historical data, need AWS ecosystem integration, or prefer a fully managed solution with minimal operational overhead.
Apache Druid: 50-150ms | Amazon Redshift: N/A
Apache Druid: 600-900MB | Amazon Redshift: N/A
Apache Druid: 100K-500K | Amazon Redshift: N/A
Apache Druid: $2500-5000 | Amazon Redshift: N/A
Apache Druid: Limited (requires denormalization) | Amazon Redshift: N/A
Apache Druid: Custom JSON/Druid QL | Amazon Redshift: N/A
Apache Druid: 500+ (Airbnb, Netflix, etc) | Amazon Redshift: N/A
Apache Druid: 100-500ms | Amazon Redshift: N/A
Apache Druid: 3-5 nodes | Amazon Redshift: N/A
Apache Druid: Druid SQL (Full) | Amazon Redshift: N/A
Apache Druid: 15,800 | Amazon Redshift: N/A
Apache Druid: Real-time metrics (specialized) | Amazon Redshift: N/A
Apache Druid: Limited (basic) | Amazon Redshift: N/A
Apache Druid: 500,000 | Amazon Redshift: N/A
Apache Druid: 150 | Amazon Redshift: N/A
Apache Druid: 10:1 | Amazon Redshift: N/A
Apache Druid: Basic (limited analyzers) | Amazon Redshift: N/A
Apache Druid: 15,200 | Amazon Redshift: N/A
Apache Druid: 300+ | Amazon Redshift: N/A
Apache Druid: 120 | Amazon Redshift: N/A
Apache Druid: 500ms | Amazon Redshift: 8000ms
Apache Druid: 1,000,000 | Amazon Redshift: 0.5-2
Apache Druid: Unlimited (distributed) | Amazon Redshift: Petabyte scale
Apache Druid: $0.10-$0.50 | Amazon Redshift: $1.50-$5.00
Apache Druid: 14-30 | Amazon Redshift: 1-3
Apache Druid: Time-window based (7 days to 3 years typical) | Amazon Redshift: Unlimited historical storage
Apache Druid: ~60% ANSI SQL | Amazon Redshift: 95% (PostgreSQL-compatible)
Apache Druid: 16-64 | Amazon Redshift: 160-256
Apache Druid: 10-100ms | Amazon Redshift: N/A
Apache Druid: 1-5 seconds (streaming) | Amazon Redshift: Batch (minutes to hours typical)
Apache Druid: Included in storage/infrastructure | Amazon Redshift: N/A
Apache Druid: Petabyte+ (with cluster scaling) | Amazon Redshift: N/A
Apache Druid: Self-hosted, cloud, hybrid, open-source | Amazon Redshift: N/A
Apache Druid: High (cluster tuning, scaling, monitoring) | Amazon Redshift: N/A
Apache Druid: 250ms | Amazon Redshift: N/A
Apache Druid: 1,000,000+ | Amazon Redshift: N/A
Apache Druid: $5 (self-hosted avg) | Amazon Redshift: N/A
Apache Druid: 300 | Amazon Redshift: N/A
Apache Druid: Proprietary Druid SQL with extensions | Amazon Redshift: N/A
Apache Druid: 45 (self-hosted setup) | Amazon Redshift: N/A
Apache Druid: 3 (recommended) | Amazon Redshift: N/A
Apache Druid: 1M+ | Amazon Redshift: N/A
Apache Druid: 50K-100K | Amazon Redshift: N/A
Apache Druid: 10:1 to 20:1 | Amazon Redshift: N/A
Apache Druid: 12+ (Coordinator, Broker, Historical, MiddleManager, Overlord, Router) | Amazon Redshift: N/A
Apache Druid: 1M-10M practical limit | Amazon Redshift: N/A
Apache Druid: 100-500MB segments | Amazon Redshift: N/A
Apache Druid: 2-3 months | Amazon Redshift: N/A
Apache Druid: N/A | Amazon Redshift: 1-10 seconds
Apache Druid: N/A | Amazon Redshift: Minutes to hours typical
Apache Druid: N/A | Amazon Redshift: 2,000+
Apache Druid: N/A | Amazon Redshift: AWS Proprietary Managed Service
Apache Druid: N/A | Amazon Redshift: AWS only
Apache Druid: N/A | Amazon Redshift: Limited via Kinesis/S3 batch
Apache Druid: N/A | Amazon Redshift: $2,160-8,640 (dc2.large, 2-4 nodes)
Query Latency (1B row scan, 10 column aggregate)
Apache Druid: N/A | Amazon Redshift: 500-2000ms
Apache Druid: N/A | Amazon Redshift: Included in node cost
Apache Druid: N/A | Amazon Redshift: 4-8x
Apache Druid: N/A | Amazon Redshift: 2 (minimum production)
Apache Druid: N/A | Amazon Redshift: 32 (base, expandable via Concurrency Scaling)
Apache Druid: N/A | Amazon Redshift: 20+ (native connectors)
Apache Druid: N/A | Amazon Redshift: Not open-source (proprietary)
Apache Druid: N/A | Amazon Redshift: $0.50 (DC2.large)
Apache Druid: N/A | Amazon Redshift: ~16 seconds
Apache Druid: N/A | Amazon Redshift: 10-15 (requires cluster resize + restart)
Apache Druid: N/A | Amazon Redshift: 100+
Apache Druid: N/A | Amazon Redshift: 1 (AWS only)
Apache Druid: N/A | Amazon Redshift: Up to 30%
Apache Druid: N/A | Amazon Redshift: 40-80 (distribution keys, sort keys, vacuum)
Annual TCO (100TB storage, average usage)
Apache Druid: N/A | Amazon Redshift: $200,000
Apache Druid: N/A | Amazon Redshift: 40-60 hours
Apache Druid: N/A | Amazon Redshift: 50 (standard)
Apache Druid: N/A | Amazon Redshift: Coupled (scale together)
Apache Druid: N/A | Amazon Redshift: ~200 (limited)
Apache Druid: N/A | Amazon Redshift: 70%
Average Query Latency (1 Billion Row Scan)
Apache Druid: N/A | Amazon Redshift: 350ms
Apache Druid: N/A | Amazon Redshift: $2.25
Apache Druid: N/A | Amazon Redshift: 10,000+
Apache Druid: N/A | Amazon Redshift: 99.99%
Apache Druid: N/A | Amazon Redshift: 12+ (S3, Glue, Lambda, Athena, QuickSight, IAM, EventBridge, etc.)
Apache Druid: N/A | Amazon Redshift: 500ms-5000ms
Apache Druid: N/A | Amazon Redshift: $0.25-$0.50
Apache Druid: N/A | Amazon Redshift: 3-7 days
Apache Druid: N/A | Amazon Redshift: 300-3600 seconds
Apache Druid: N/A | Amazon Redshift: 6:1 to 15:1
Maximum Concurrent Queries (Standard Node)
Apache Druid: N/A | Amazon Redshift: 15-25
Apache Druid: N/A | Amazon Redshift: Full PostgreSQL compatible (95%+ ANSI SQL)
Apache Druid: N/A | Amazon Redshift: Linear scaling with node count limits
Apache Druid: N/A | Amazon Redshift: 21-28 days
Apache Druid: N/A | Amazon Redshift: $180,000-$240,000
Apache Druid: N/A | Amazon Redshift: 120-240 seconds
Apache Druid: N/A | Amazon Redshift: 50-100 typical
Apache Druid: N/A | Amazon Redshift: 10:1 average
Apache Druid: N/A | Amazon Redshift: No (requires replication)
Apache Druid: N/A | Amazon Redshift: Per-second (reserved/on-demand)
How to choose between Apache Druid and Amazon Redshift
Druid vs Amazon Redshift — Structured Comparison Data
Machine-readable comparison dataset for Druid vs Amazon Redshift. Contains 100 attribute comparisons, 5 FAQ pairs.
Druid vs Amazon Redshift — Attribute Category Vocabulary
Taxonomy of attribute categories used to classify comparison data for Druid vs Amazon Redshift.
When should I use Druid instead of Redshift?
Use Druid when you need real-time analytics with sub-second latency on streaming data (clickstreams, user events, sensor data, financial ticks). Redshift is better if you're running traditional data warehouse queries on historical data without real-time requirements. Druid's strength is speed on incoming data; Redshift's strength is analyzing massive historical datasets.
What's the cost difference between Druid and Redshift?
Druid is often cheaper for high-throughput streaming (pay per ingestion/query), typically $3K-$15K/month for mid-sized clusters. Redshift costs depend on node type ($2K-$20K+/month), but includes AWS managed services. For bursty or unpredictable workloads, Redshift concurrency scaling adds costs; Druid's pay-as-you-go is more predictable for streaming scenarios.
Can Druid and Redshift be used together?
Yes—many organizations use both. Druid handles real-time dashboards and live analytics (hot data), while Redshift handles deeper historical analysis and long-term archival queries. Data can flow from Druid to Redshift for cold-storage analytics via tools like Apache Kafka or AWS S3.
Which requires less operational overhead?
Redshift requires significantly less operational effort—it's fully managed by AWS with automatic scaling, backups, and patching. Druid requires hands-on cluster management, Zookeeper coordination, and tuning expertise. For teams without dedicated data engineering resources, Redshift is the better choice.
How do query latencies compare for interactive dashboards?
Druid delivers 50-500ms latency suitable for live dashboards (feels instant to users). Redshift typically returns queries in 1-10 seconds, acceptable for batch reporting but noticeable lag in interactive exploration. If sub-second responsiveness is critical, Druid is the only choice.
How to Choose Between Apache Druid and Amazon Redshift
Query Latency: Apache Druid has 50-500ms (sub-second), while Amazon Redshift has 1-10 seconds (batch optimized).
Primary Use Case: Apache Druid has Real-time OLAP and time-series analytics, while Amazon Redshift has Large-scale data warehouse and batch analytics.
Data Ingestion Rate: Apache Druid has Up to 1M events/second, while Amazon Redshift has Batch-oriented (slower streaming).
Consider: Typical Cluster Cost (Monthly)
Typical Cluster Cost (Monthly): Apache Druid has $3,000-$15,000 for mid-size, while Amazon Redshift has $2,000-$20,000+ depending on node type.
Data Retention Model: Apache Druid has Time-based rolling windows (hot/cold data), while Amazon Redshift has Persistent all-data storage.
Ease of Setup: Apache Druid has Complex (requires Zookeeper, deep tuning), while Amazon Redshift has Simple (AWS-managed, minimal config).
SQL Dialect Support: Apache Druid has Druid SQL (proprietary variant), while Amazon Redshift has PostgreSQL-compatible SQL.