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.
Core Information
#core_informationName, 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_profileTypical 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_diagramReference diagram of the technology's internal architecture.
Component Architecture & Topology
Features
#featuresCatalogued product capabilities and what each one does.
Empirical data for features is currently being compiled in the global catalog.
Typical Use Cases
#typical_use_casesScenarios the technology is commonly chosen for.
Empirical data for typical use cases is currently being compiled in the global catalog.
Known Customers
#known_customersPublicly referenced organisations using the technology.
Empirical data for known customers is currently being compiled in the global catalog.
Known Integrations
#known_integrationsOther products and services it is documented to work with.
Empirical data for known integrations is currently being compiled in the global catalog.
Connectors
#connectorsDirectional data connections to other technologies, with direction and maturity.
Empirical data for connectors is currently being compiled in the global catalog.
Reference Architectures
#reference_architecturesPublished architectures where the technology is used or mentioned.
No published reference architecture blueprints currently link to Amazon Redshift.
Security Features
#security_featuresBuilt-in security and access-control capabilities.
Empirical data for security features is currently being compiled in the global catalog.
Known Issues
#known_issuesDocumented limitations, defects and operational pitfalls.
Empirical data for known issues is currently being compiled in the global catalog.
Guidelines
#guidelinesRecommended practices for adopting and operating the technology.
Empirical data for guidelines is currently being compiled in the global catalog.
Standards & Compliance
#standards_and_complianceStandards, certifications and control requirements it maps to.
Empirical data for standards & compliance is currently being compiled in the global catalog.
Sources
#sourcesDocumentation and research references behind the recorded information.
Empirical data for sources is currently being compiled in the global catalog.
Expert Validation
#expert_validationWhether domain experts reviewed and confirmed the content.
Empirical data for expert validation is currently being compiled in the global catalog.