configuring-lookup-caches

In-memory lookup caches speed up cross-reference ID mapping by storing reference data as key-value entries, eliminating slow, repeated external API calls during flow execution. You load mappings into the cache and retrieve them via import or export lookups.

In-memory state tracking works by upserting timestamps, batch markers, or composite keys into a lookup cache, maintaining workflow state across integration runs without adding custom storage. You retrieve keys by exact match or prefix during flow execution.

The best way to prevent duplicate records is using lookup caches for deduplication. You upsert processed record IDs or composite keys into the cache, then check the cache during flow execution to skip records that have already been processed.

Yes, you can store JSON objects in a lookup cache by JSON-stringifying them as string values. When configuring import or export lookups, you retrieve the cached value and extract specific fields using an extract JSON path.

You manage lookup cache size and data lifecycle by deleting selected keys, purging all entries, and applying size governance with pagination limits. This ensures caches remain efficient and do not exceed operational boundaries during integration processing.

Yes, Celigo lookup caches work with static reference tables by caching relatively stable data such as category hierarchies or overrides. You can optionally include these caches in templates and cloning to maintain consistent reference data across integration flows.