What should I use for a data API with low latency?

For a low-latency data API, the best choice depends on your access pattern, scale, and consistency needs. In general:

Good default choices

• gRPC: Often the best for very low latency service-to-service APIs.

  • Binary protocol, smaller payloads, faster than JSON/HTTP in many cases
  • Strongly typed contracts via Protobuf
  • Great for internal APIs, microservices, and high-throughput systems

• REST over HTTP/JSON: Easier to adopt, but usually slower and heavier than gRPC.

  • Best if compatibility and simplicity matter more than raw latency
  • Can still be low-latency with caching, compression, and careful design

• GraphQL: Usually not ideal for lowest latency.

  • Flexible, but often adds server complexity and overhead
  • Better for client flexibility than for strict performance

If latency is extremely important

Consider:

• gRPC with HTTP/2
• Binary serialization like Protobuf or FlatBuffers
• Caching at the edge or application layer
• Read replicas / in-memory stores like Redis
• Batching requests where possible
• Precomputed views / denormalized data
• Co-locating services in the same region or network zone

If it’s a public API

A practical setup is:

• REST or gRPC gateway
• CDN / edge caching
• Fast backend store (Redis, DynamoDB, ScyllaDB, Cassandra, etc.)
• Aggressive query optimization

Rule of thumb

• Internal, high-performance API → gRPC
• Public, developer-facing API → REST, with caching and optimization
• Flexible client querying → GraphQL, only if flexibility is worth the overhead

If you tell me:

1. whether this is internal or public,
2. expected requests per second, and
3. whether you need read-heavy or write-heavy,

I can recommend a specific stack.