Google Analytics — Technology Profile & Architecture

Core Information

#core_information

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

Overview & Role

Google Analytics is a web analytics service that tracks and reports website traffic. It provides detailed statistics and insights into user behavior, helping businesses understand how visitors engage with their websites and optimize their online presence. The latest version, Google Analytics 4 (GA4), focuses on event-based data collection across websites and apps.

Domain Classification & Tags

Monitoring and Logging

Performance Profile

#performance_profile

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

Read Performance Profile

Throughput: N/A (data collection, not direct read)

Payload Size: N/A (data collection, not direct read)

Processing Latency: N/A (data collection, not direct read)

Write Performance Profile

Throughput: High (millions of hits/second for large sites)

Payload Size: Small (typically <1 KB per hit)

Processing Latency: Low (client-side beaconing, server-side processing is asynchronous)

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.

Associated with 1 verified reference architecture blueprint:

Fraud Detection and Security Logging

Cassandra's capability to ingest and store massive amounts of event data, such as transaction logs and security events, makes it a strong candidate for fraud detection systems and security information and event management (SIEM) solutions that require real-time analysis of large datasets.

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.