Analytics Evaluated
Amazon Redshift logo

Amazon Redshift

Amazon Redshift is a fully managed, petabyte-scale cloud data warehouse service. It is designed for analytical workloads, allowing users to run complex analytical queries against large datasets using standard SQL. Redshift is optimized for high-performance analytics and integrates with various AWS services for data ingestion, processing, and visualization.

Category / Domain Analytics
I/O Performance Empirical Profile

Core Information

#core_information

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

Overview & Role

Amazon Redshift is a fully managed, petabyte-scale cloud data warehouse service. It is designed for analytical workloads, allowing users to run complex analytical queries against large datasets using standard SQL. Redshift is optimized for high-performance analytics and integrates with various AWS services for data ingestion, processing, and visualization.

Domain Classification & Tags

Performance Profile

#performance_profile

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

Read Performance Profile

Throughput: Varies greatly, from hundreds to tens of thousands of queries/hour, or hundreds of MB/s to several GB/s for data scanning

Payload Size: Typically large datasets, ranging from MBs to TBs per query

Processing Latency: Sub-second for simple queries on small datasets, to minutes or hours for complex analytical queries on large datasets

Write Performance Profile

Throughput: Hundreds of MB/s to several GB/s for bulk loading (e.g., COPY command), thousands of rows/second for individual inserts

Payload Size: Typically large datasets for bulk loading (MBs to TBs), individual rows for inserts

Processing Latency: Seconds to minutes for bulk loading, tens to hundreds of milliseconds for individual inserts

Architecture Diagram

#architecture_diagram

Reference diagram of the technology's internal architecture.

Component Architecture & Topology

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 Amazon Redshift.

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.