Apache Druid — Technology Profile & Architecture

Core Information

#core_information

Name, description, vendor website, logo, technology type and tags.

Overview & Role

Apache Druid is a high-performance, real-time analytics database designed for fast slice-and-dice analytics ("OLAP" queries) on large datasets. It is commonly used for powering user-facing analytics applications, business intelligence dashboards, and high-concurrency APIs.

Domain Classification & Tags

Analytics

Performance Profile

#performance_profile

Typical read and write throughput, payload size and processing latency.

Read Performance Profile

Throughput: Thousands to hundreds of thousands of queries/sec (simple point lookups) to hundreds of queries/sec (complex aggregations/joins)

Payload Size: Varies greatly, from small JSON responses (e.g., single metric) to large result sets (e.g., 100s of MBs for detailed reports)

Processing Latency: Typically 50 ms to 500 ms for most analytical queries; sub-100 ms for simple aggregations on well-indexed data

Write Performance Profile

Throughput: Hundreds of thousands to millions of events/sec (batch ingestion); tens of thousands to hundreds of thousands of events/sec (real-time ingestion)

Payload Size: Typically 100 bytes to 10 KB per event/row

Processing Latency: Seconds to minutes for data to become queryable (real-time ingestion); minutes to hours for batch ingestion to be fully available

Architecture Diagram

#architecture_diagram

Reference diagram of the technology's internal architecture.

Component Architecture & Topology

open_in_new Standalone Tab

Features

#features

Catalogued product capabilities and what each one does.

Empirical data for features is currently being compiled in the global catalog.

Typical Use Cases

#typical_use_cases

Scenarios the technology is commonly chosen for.

Empirical data for typical use cases is currently being compiled in the global catalog.

Known Customers

#known_customers

Publicly referenced organisations using the technology.

Empirical data for known customers is currently being compiled in the global catalog.

Known Integrations

#known_integrations

Other products and services it is documented to work with.

Empirical data for known integrations is currently being compiled in the global catalog.

Connectors

#connectors

Directional data connections to other technologies, with direction and maturity.

Empirical data for connectors is currently being compiled in the global catalog.

Reference Architectures

#reference_architectures

Published architectures where the technology is used or mentioned.

No published reference architecture blueprints currently link to Apache Druid.

Security Features

#security_features

Built-in security and access-control capabilities.

Empirical data for security features is currently being compiled in the global catalog.

Known Issues

#known_issues

Documented limitations, defects and operational pitfalls.

Empirical data for known issues is currently being compiled in the global catalog.

Guidelines

#guidelines

Recommended practices for adopting and operating the technology.

Empirical data for guidelines is currently being compiled in the global catalog.

Standards & Compliance

#standards_and_compliance

Standards, certifications and control requirements it maps to.

Empirical data for standards & compliance is currently being compiled in the global catalog.

Sources

#sources

Documentation and research references behind the recorded information.

Empirical data for sources is currently being compiled in the global catalog.

Expert Validation

#expert_validation

Whether domain experts reviewed and confirmed the content.

Empirical data for expert validation is currently being compiled in the global catalog.