How do I combine multiple data sources through one API?

To combine multiple data sources through one API, you typically build a single aggregation layer that acts as a unified interface in front of all your sources.

Common patterns

1. API Gateway + Backend Aggregation

Your API receives one request, then the backend calls multiple services/databases and merges the results.

Flow: Client → Your API → Source A / Source B / Source C → combined response

Good for:

• Cross-system lookups
• Custom merging logic
• Returning one clean response shape

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2. Federation

Each source keeps ownership of part of the data, and the API layer resolves fields from different sources.

Good for:

• GraphQL-style APIs
• Systems where data is distributed across services
• Avoiding a monolithic database

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3. ETL / ELT into a Unified Store

You periodically sync data from multiple sources into one database or warehouse, then expose that via one API.

Good for:

• Reporting and analytics
• Faster queries
• Heavy joins across sources

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4. Orchestration via Microservices

Your API acts as an orchestrator that calls multiple internal APIs and composes the final response.

Good for:

• Business workflows
• Enriching one source with another
• External APIs you don’t control

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Typical implementation steps

1. Define the unified schema

   • Decide what the combined response should look like.
   • Map each source to that schema.

2. Build connectors for each source

   • REST, GraphQL, SQL, files, queues, third-party APIs, etc.

3. Normalize data

   • Convert timestamps, IDs, naming, types, and missing fields into a common format.

4. Merge and resolve conflicts

   • Decide what happens when sources disagree.
   • Example: source priority, latest timestamp wins, or source-specific fields preserved.

5. Add caching

   • Reduce repeated calls to slow sources.

6. Handle failures gracefully

   • Timeouts, retries, partial responses, fallbacks.

7. Secure access

   • Auth, rate limits, secrets management, auditing.

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Example architecture

If you’re combining CRM + billing + support data:

• /customer/{id} API
• Backend fetches:
  • CRM profile
  • Billing status
  • Support tickets
• Merges into:

  {
    "customerId": "123",
    "name": "Acme Co",
    "plan": "Enterprise",
    "openTickets": 2
  }
  

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Tools/patterns that help

• GraphQL for flexible composition
• OpenAPI + backend service layer for REST
• Apache Camel / MuleSoft / Boomi / n8n / Zapier for integration-heavy workflows
• Kafka / Airflow / dbt / Fivetran for syncing data into a warehouse
• Redis for caching
• API gateways like Kong, Apigee, AWS API Gateway for routing/security

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Important design choice

Ask yourself:

• Do you need real-time combined data?
  • Use API composition / federation
• Do you need fast analytics?
  • Use ETL into a unified store
• Do you need loose coupling between sources?
  • Use orchestration or federation

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If you want, I can sketch a concrete design for your case—e.g. REST API, GraphQL, or database + third-party APIs.