AWS Lake Formation — Technology Profile & Architecture

Core Information

#core_information

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

Overview & Role

Builds, secures and governs data lakes on Amazon S3.

Domain Classification & Tags

Analytics

Performance Profile

#performance_profile

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

Read Performance Profile

Throughput: Highly variable, depends on underlying services (e.g., Athena, Redshift Spectrum, EMR) and data volume. Can range from hundreds of MB/s to several GB/s for large analytical queries.

Payload Size: Highly variable, depends on query results. Can range from KB (metadata) to TB (full table scans). Typical analytical queries might process GBs of data.

Processing Latency: Highly variable, depends on underlying services and query complexity. Can range from sub-second (metadata access, small queries) to minutes or hours (complex analytical queries over large datasets).

Write Performance Profile

Throughput: Highly variable, depends on underlying services (e.g., Glue, EMR) and data volume. Can range from MB/s to GB/s for batch ingestion.

Payload Size: Highly variable, depends on data ingestion patterns. Can range from KB (small updates) to TB (large batch loads).

Processing Latency: Highly variable, depends on underlying services and write operation. Can range from seconds (small file uploads, metadata updates) to minutes or hours (large batch ETL jobs).

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 AWS Lake Formation.

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.