Amazon Kinesis Data Streams
Amazon Kinesis Data Streams (KDS) is a massively scalable and durable real-time data streaming service. It enables you to continuously capture gigabytes of data per second from hundreds of thousands of sources, such as website clickstreams, database event streams, financial transactions, social media feeds, and IoT device data. KDS allows you to process and analyze this data in real-time using standard stream processing frameworks.
Core Information
#core_informationName, description, vendor website, logo, technology type and tags.
Overview & Role
Amazon Kinesis Data Streams (KDS) is a massively scalable and durable real-time data streaming service. It enables you to continuously capture gigabytes of data per second from hundreds of thousands of sources, such as website clickstreams, database event streams, financial transactions, social media feeds, and IoT device data. KDS allows you to process and analyze this data in real-time using standard stream processing frameworks.
Domain Classification & Tags
Performance Profile
#performance_profileTypical read and write throughput, payload size and processing latency.
Read Performance Profile
Throughput: Up to 2 MB/sec or 2,000 records/sec per shard (can scale by adding shards)
Payload Size: Up to 1 MB per record (typical records are much smaller, e.g., 1 KB - 100 KB)
Processing Latency: Typically < 70 ms (from write to read, for GetRecords calls)
Write Performance Profile
Throughput: Up to 1 MB/sec or 1,000 records/sec per shard (can scale by adding shards)
Payload Size: Up to 1 MB per record (typical records are much smaller, e.g., 1 KB - 100 KB)
Processing Latency: Typically < 100 ms (for PutRecord/PutRecords API calls)
Architecture Diagram
#architecture_diagramReference diagram of the technology's internal architecture.
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 Kinesis Data Streams.
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.