Druid is a columnar OLAP database optimized for real-time analytics on time-series data with sub-second latency, while Elasticsearch is a distributed search and analytics engine built for full-text search and log analysis. Druid excels at numerical aggregations across massive datasets, whereas Elasticsearch prioritizes flexible querying and text search capabilities.
Druid vs Elasticsearch — Side-by-side comparison on A Versus B
Real-time OLAP database for streaming analytics and time-series data
Proprietary distributed search and analytics engine by Elastic with cloud-native architecture.
Primary Use Case. Query Latency (typical aggregations). Full-Text Search Capability. Data Model. Typical Storage Efficiency (compression ratio). Community Size (GitHub stars as of 2026). Setup Complexity
Choose Druid if you need sub-second analytics queries on time-series data at massive scale with pre-aggregated rollups and extreme storage efficiency. Choose Elasticsearch if you prioritize full-text search capabilities, flexible JSON document querying, or need a more accessible solution for log analytics with a larger ecosystem and community support.
Druid: 0.1-0.5 seconds | Elasticsearch: N/A
Druid: 8:1 to 15:1 | Elasticsearch: 4:1 to 8:1
Druid: 500+ nodes tested | Elasticsearch: Unlimited (enterprise only)
Druid: Druid SQL (subset of ANSI) | Elasticsearch: N/A
Druid: Native (Kafka, Kinesis, Pulsar) | Elasticsearch: N/A
Druid: No ACID (eventual consistency) | Elasticsearch: N/A
Druid: 16,000+ stars | Elasticsearch: N/A
Druid: 100-500ms (real-time) | Elasticsearch: N/A
Query Latency (100M rows, simple aggregation)
Druid: 10TB practical limit | Elasticsearch: N/A
Druid: 70% (Druid SQL dialect) | Elasticsearch: N/A
Druid: Native time_floor, granular rollups, datasource-level aggregations | Elasticsearch: N/A
Druid: 1,000,000+ realtime | Elasticsearch: N/A
Druid: ~400 enterprises | Elasticsearch: N/A
Druid: $50,000-500,000 (infrastructure) | Elasticsearch: N/A
Druid: 0.2 (pre-aggregated metrics) | Elasticsearch: N/A
Druid: 500+ TB/day sustainable | Elasticsearch: N/A
Druid: 8/10 (high setup & tuning) | Elasticsearch: N/A
Average Query Latency (Standard Aggregation)
Druid: Druid SQL dialect (proprietary subset) | Elasticsearch: N/A
Druid: Coordinator, Data, Query, Broker (4+ types) | Elasticsearch: N/A
Druid: 0.2-0.5 seconds (real-time) | Elasticsearch: N/A
Druid: 2012 (Metamarkets) | Elasticsearch: N/A
Druid: Limited (no native implementation) | Elasticsearch: Native with advanced analyzers
Druid: ~10-100ms | Elasticsearch: ~100-500ms
Druid: 8/10 (complex) | Elasticsearch: 5/10 (moderate)
Druid: 100+ billion | Elasticsearch: 10-50 billion (performance degradation)
Maximum Concurrent Queries (Standard Node)
Druid: 32+ (distributed) | Elasticsearch: N/A
Druid: Partial (60-70% ANSI SQL) | Elasticsearch: N/A
Druid: Linear scaling with added nodes | Elasticsearch: N/A
Druid: N/A | Elasticsearch: $0.10 - $0.20
Druid: N/A | Elasticsearch: 30+ days (self-hosted)
Druid: N/A | Elasticsearch: 40-80 (self-hosted)
Druid: N/A | Elasticsearch: Unlimited (via client libraries)
Druid: N/A | Elasticsearch: Petabyte-scale (1000+ TB)
Druid: N/A | Elasticsearch: 7 (Lucene/DSL - steep learning curve)
Druid: N/A | Elasticsearch: Self-hosted, SaaS (Elastic Cloud), or Kubernetes
Druid: N/A | Elasticsearch: $0 (self-hosted)
Druid: N/A | Elasticsearch: $0 (unlimited after infrastructure cost)
Druid: N/A | Elasticsearch: 0 (requires custom hardening)
Druid: N/A | Elasticsearch: 3 (anomaly detection, forecasting, outlier detection)
Druid: N/A | Elasticsearch: 12-48 (community forums)
Druid: N/A | Elasticsearch: 1,000+ (tested to 10,000 with advanced tuning)
Druid: N/A | Elasticsearch: Native (analyzers, relevance tuning, fuzzy matching)
Druid: N/A | Elasticsearch: 1-3 days (schemaless indexing)
Druid: N/A | Elasticsearch: SQL via plugin (Elastic SQL), primary is Query DSL
Druid: N/A | Elasticsearch: 32-64GB for equivalent throughput
Druid: N/A | Elasticsearch: $0-$10,000 (self-hosted) or $20,000-$60,000 (managed)
Druid: N/A | Elasticsearch: 45-120 (manual investigation required)
Druid: N/A | Elasticsearch: 1000+ via community/Beats
Druid: N/A | Elasticsearch: Unlimited (storage-dependent)
Druid: N/A | Elasticsearch: 500,000+ EPS per cluster
Druid: N/A | Elasticsearch: Complex Query DSL requiring technical expertise
Druid: N/A | Elasticsearch: 68,000+ stars
Druid: N/A | Elasticsearch: 5-10 minutes
Druid: N/A | Elasticsearch: 65 docs/sec per thread
Druid: N/A | Elasticsearch: $5,000-$50,000
Druid: N/A | Elasticsearch: Via aggregations (requires custom queries)
Monthly Cost (100GB index, 1M queries/month)
Druid: N/A | Elasticsearch: $200-500 self-hosted
Druid: N/A | Elasticsearch: Petabyte-scale (unlimited)
Druid: N/A | Elasticsearch: Requires DevOps expertise
Druid: N/A | Elasticsearch: 9/10 (plugins, analyzers, scripting)
Druid: N/A | Elasticsearch: Community-based or 4+ hours (enterprise)
Druid: N/A | Elasticsearch: 14-28 days (self-hosted)
Druid: N/A | Elasticsearch: $3,000-$8,000
Druid: N/A | Elasticsearch: ~300 integrations
Druid: N/A | Elasticsearch: Unlimited (configurable)
Druid: N/A | Elasticsearch: Advanced EQL with full customization
Druid: N/A | Elasticsearch: 120-240 minutes
Druid: N/A | Elasticsearch: 1+ Billion (across clusters)
Druid: N/A | Elasticsearch: 40+ aggregation types
Druid: N/A | Elasticsearch: Manual configuration required
Druid: N/A | Elasticsearch: ~60,000 stars
Druid: N/A | Elasticsearch: $50,000-150,000
Druid: N/A | Elasticsearch: 30-40 (via Beats)
Druid: N/A | Elasticsearch: $0 (open-source) or $12,000
Druid: N/A | Elasticsearch: Requires third-party integrations
Druid: N/A | Elasticsearch: Full Elasticsearch Query DSL and custom scripts
Druid: N/A | Elasticsearch: 1M+ active developers
Mean Time to Resolution (MTTR) Improvement
Druid: N/A | Elasticsearch: Depends on manual investigation
Druid: N/A | Elasticsearch: 80-200 hours (extensive)
Total Cost of Ownership (3-year, 500GB/month ingestion)
Druid: N/A | Elasticsearch: $120,000 (self-hosted licensing + 2 FTEs infrastructure)
Druid: N/A | Elasticsearch: Logs, metrics (via plugins), custom JSON data
Druid: N/A | Elasticsearch: 100-2000ms (depends on tuning)
Required Infrastructure Team Size (100 users)
Druid: N/A | Elasticsearch: 2-3 (cluster management + optimization)
Druid: N/A | Elasticsearch: 180,000+ (open-source)
Druid: N/A | Elasticsearch: Unlimited (petabyte-scale)
Druid: N/A | Elasticsearch: 60-120 minutes
Druid: N/A | Elasticsearch: 1000+ plugins/integrations
Druid: N/A | Elasticsearch: 30+ languages
Druid: N/A | Elasticsearch: Requires configuration/plugin
Druid: N/A | Elasticsearch: 500,000+ companies worldwide
Typical Query Latency (1B rows, GROUP BY)
Druid: N/A | Elasticsearch: Native, highly optimized (primary feature)
Druid: N/A | Elasticsearch: Via Beats and Logstash (indirect)
Druid: N/A | Elasticsearch: Low-Medium (simpler operations)
Druid: N/A | Elasticsearch: 5+ PB (operational limit)
Druid: N/A | Elasticsearch: SQL plugin available (limited JOIN support)
Druid: N/A | Elasticsearch: 2-4 full-time engineers
Druid: N/A | Elasticsearch: Lucene, KQL, SQL, JavaScript
Druid: N/A | Elasticsearch: Varies by deployment (self-hosted: customer responsibility)
Druid: N/A | Elasticsearch: Yes (SSPL/Elastic License)
Druid: N/A | Elasticsearch: $0 (self-hosted) / $884 (cloud)
Druid: N/A | Elasticsearch: Unlimited (user-configured)
Druid: N/A | Elasticsearch: 40-80 hours for production cluster
Druid: N/A | Elasticsearch: Requires ML plugins or third-party tools
Druid: N/A | Elasticsearch: Query DSL (complex, steep learning curve)
Druid: N/A | Elasticsearch: 45+ via Logstash and Beats
Druid: N/A | Elasticsearch: $10,600-$40,000 (Elastic Cloud)
Annual Licensing Cost (Small Deployment)
Druid: N/A | Elasticsearch: $0 (self-managed)
Druid: N/A | Elasticsearch: 67,000+ stars
Druid: N/A | Elasticsearch: Via plugin (not native)
Druid: N/A | Elasticsearch: Proprietary SSPL/Elastic License (features restricted)
Druid: N/A | Elasticsearch: $1.95/hour minimum ($429/month)
Druid: N/A | Elasticsearch: Free (open source core)
Druid: N/A | Elasticsearch: ~50,000 documents/second
Druid: N/A | Elasticsearch: ~45ms average across distributions
Druid: N/A | Elasticsearch: 1000+ verified integrations
Druid: N/A | Elasticsearch: 23+ years in market
How to choose between Druid and Elasticsearch
Druid vs Elasticsearch — Structured Comparison Data
Machine-readable comparison dataset for Druid vs Elasticsearch. Contains 171 attribute comparisons, 5 FAQ pairs.
Druid vs Elasticsearch — Attribute Category Vocabulary
Taxonomy of attribute categories used to classify comparison data for Druid vs Elasticsearch.
When should I use Druid over Elasticsearch?
Use Druid when you need sub-second analytics on massive time-series datasets (100B+ rows), require extreme storage compression, perform frequent numerical aggregations, or need real-time metric pre-computation via rollups. Druid's columnar architecture excels at OLAP workloads with predictable query patterns.
When should I use Elasticsearch over Druid?
Use Elasticsearch for full-text search, log analysis, flexible ad-hoc querying, security analytics, or when you need a lower barrier to entry. Elasticsearch is better for text-heavy workloads, evolving schemas, and applications where search relevance scoring matters more than raw aggregation speed.
Can Druid and Elasticsearch be used together?
Yes. Many organizations use Elasticsearch for log indexing and search, then export/replicate aggregated metrics to Druid for long-term time-series analytics. This leverages Elasticsearch's search strength for recent logs and Druid's efficiency for historical metric analysis.
What's the cost difference between Druid and Elasticsearch?
Both are open-source and free to self-host. Druid requires more operational expertise (higher DevOps costs), while Elasticsearch has lower setup costs but higher storage/compute at scale. Cloud-hosted versions (Elastic Cloud vs. Imply) typically cost $500-5000+/month depending on data volume.
How do query patterns differ between Druid and Elasticsearch?
Druid optimizes for known, repeated aggregations (COUNT, SUM, GROUP BY) via pre-computation, making these extremely fast. Elasticsearch excels at varied, ad-hoc queries with complex boolean logic and text matching. Druid penalizes unpredictable unique-value queries, while Elasticsearch handles them gracefully at the cost of latency.
How to Choose Between Druid and Elasticsearch
Primary Use Case: Druid has Real-time OLAP analytics on time-series data, while Elasticsearch has Full-text search and log/event analytics.
Consider: Query Latency (typical aggregations)
Query Latency (typical aggregations): Druid has 50-500ms for billion-row datasets, while Elasticsearch has 100-2000ms depending on query complexity.
Full-Text Search Capability: Druid has Limited/not native, while Elasticsearch has Native with advanced analyzers and stemming.
Data Model: Druid has Columnar storage with rollup pre-aggregation, while Elasticsearch has Document-based JSON with inverted indexing.
Consider: Typical Storage Efficiency (compression ratio)
Typical Storage Efficiency (compression ratio): Druid has 8:1 to 15:1 (highly compressible numeric data), while Elasticsearch has 4:1 to 8:1 (document storage overhead).
Consider: Community Size (GitHub stars as of 2026)
Community Size (GitHub stars as of 2026): Druid has ~14,000 stars, while Elasticsearch has ~67,000 stars.
Setup Complexity: Druid has High - requires careful segment management and deep configuration, while Elasticsearch has Medium - relatively straightforward single-node setup, harder at scale.