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Hexagraph Core implements a high-performance Redis cache layer to deliver low-latency API responses across all REST and GraphQL endpoints. To prevent memory bloat and redundant processing, Hexagraph stores only final transformed Hexagraph JSON payloads in cache — raw upstream provider responses are never stored.

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Time-To-Live (TTL) Settings

Different categories of data carry tailored TTL settings based on update frequency:

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Automated Memory Management & Eviction

To ensure gateway stability and maintain high availability, Hexagraph Core performs automated memory management:
  • Automated Memory Eviction: If cache RAM usage reaches capacity, the gateway automatically executes non-blocking purge operations on response payloads.
  • Rate-Limit Counter Protection: Rate-limit counters are always preserved during cache eviction cycles to ensure continuous quota enforcement.

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Developer Best Practices

  • Shared Multi-User Cache: The cache is shared globally across users. If an output or author was recently queried by another user, your request will hit the cache and return near-instantly.
  • Identical Payloads Across Interfaces: REST endpoints and GraphQL queries share 100% of the underlying service cache — a lookup via REST warms the cache for GraphQL and vice versa.