Google Big Table
Google Bigtable is a fully managed, scalable NoSQL wide-column database service designed for large analytical and operational workloads. It's ideal for applications requiring high throughput and low latency, such as IoT, financial, and ad tech applications, and is built on the same infrastructure that powers many core Google services.
Core Information
#core_informationName, description, vendor website, logo, technology type and tags.
Overview & Role
Google Bigtable is a fully managed, scalable NoSQL wide-column database service designed for large analytical and operational workloads. It's ideal for applications requiring high throughput and low latency, such as IoT, financial, and ad tech applications, and is built on the same infrastructure that powers many core Google services.
Domain Classification & Tags
Performance Profile
#performance_profileTypical read and write throughput, payload size and processing latency.
Read Performance Profile
Throughput: Hundreds of thousands to millions of rows/sec (single-digit MB/s to hundreds of MB/s)
Payload Size: 1 KB - 1 MB (typical row size)
Processing Latency: 5-50 ms (for single-row reads or small range scans)
Write Performance Profile
Throughput: Hundreds of thousands to millions of rows/sec (single-digit MB/s to hundreds of MB/s)
Payload Size: 1 KB - 1 MB (typical row size)
Processing Latency: 5-50 ms (for single-row writes or small batch writes)
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 Google Big Table.
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.