REST API
A REST API is an application interface built on HTTP principles where resources are accessed through standard URL endpoints and manipulated using HTTP verbs (GET, POST, PUT, DELETE).
REST (Representational State Transfer) is an architectural style for designing networked applications. A REST API exposes resources (data entities) at specific URL paths and uses HTTP methods to indicate the operation: GET retrieves data, POST creates new data, PUT updates existing data, and DELETE removes data. Resources are identified by stable, predictable URLs, and responses typically contain JSON or XML representations of those resources.
REST APIs have become the de facto standard for building data APIs because they align with how the web works. They are stateless (each request contains all information needed to process it), cacheable (HTTP caching mechanisms apply naturally), and simple to understand and debug. Unlike older RPC-style interfaces, REST APIs require no special client libraries: standard HTTP tools like curl, web browsers, and any programming language's HTTP library can interact with them.
In data analytics contexts, REST APIs serve as the primary interface for querying databases, data warehouses, and analytics platforms. They enable web applications, mobile apps, and reporting tools to fetch data without direct database connections. Many modern data platforms (Snowflake, BigQuery, Databricks) provide REST APIs as an alternative to JDBC/ODBC drivers, lowering barriers for API-first application development.
Key Characteristics
- ▶Uses standard HTTP methods (GET, POST, PUT, DELETE) to express operations on resources
- ▶Identifies resources by stable, hierarchical URL paths (e.g., /api/v1/users/123)
- ▶Exchanges data in lightweight formats (JSON) designed for programmatic parsing
- ▶Supports content negotiation so clients can request different data formats
- ▶Leverages standard HTTP caching and conditional requests to improve performance
- ▶Includes HTTP status codes and headers to communicate success, errors, and metadata
Why It Matters
- ▶Enables browser-based and mobile access to data without installing database drivers or client software
- ▶Reduces infrastructure complexity by using standard HTTP infrastructure (firewalls, proxies, CDNs)
- ▶Improves interoperability between teams and systems by using a universal protocol
- ▶Simplifies debugging and monitoring because HTTP traffic is visible and inspectable
- ▶Accelerates development of web and mobile analytics applications that consume data APIs
- ▶Lowers barrier to entry for teams unfamiliar with database-specific connection protocols
Example
A web dashboard queries a REST API endpoint GET /api/v1/analytics/revenue?region=EMEA&year=2024 which returns JSON with revenue figures, regional breakdowns, and summary statistics. The client can cache responses and use HTTP conditional requests to avoid re-fetching unchanged data.
Coginiti Perspective
Coginiti's analytics outputs can be exposed through REST APIs via Coginiti Actions (publishing to external systems) or by leveraging platform-native REST APIs (Snowflake, BigQuery, Redshift) to query materialized tables produced by Coginiti. The semantic layer (SMDL) ensures that REST API consumers access consistent business definitions, while the ODBC driver and Semantic SQL enable building custom REST endpoints that expose governed metrics. Coginiti's multi-platform support enables organizations to publish analytics to platforms with native REST API capabilities, supporting diverse application architectures that prefer HTTP-based data access.
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