How to Migrate from Algolia to Typesense Without Downtime: A Step-by-Step Guide
A seven-step migration plan — parallel setup, side-by-side testing, feature-flag cutover, and a rollback window — built so search never goes down and nothing gets lost.
The biggest reason teams delay leaving Algolia isn't cost tolerance — it's fear of breaking search during a busy sales period, or losing months of relevance tuning in the process. Done right, neither has to happen. Most teams complete the full process in two to three weeks — longer if ranking rules are complex, but rarely more than a month. Here's the process.
Audit what you actually use
Before touching infrastructure, list every Algolia feature your storefront depends on: typo tolerance settings, synonyms, custom ranking rules, faceting, geo-search, merchandising rules. This becomes your migration checklist — the goal is feature parity, not a downgrade.
Stand up Typesense in parallel
Provision a Typesense Cloud cluster (or self-hosted instance) alongside your existing Algolia setup — don't touch production yet. Define your collection schema, mapping each Algolia index attribute to its Typesense equivalent. This is the single biggest structural difference to plan for: Algolia is schema-less, so new attributes can be added on the fly, while Typesense enforces a typed schema — every field needs a declared type before it can be indexed. Map this out before writing any migration code, not during.
Migrate data and rebuild relevance rules
Export your Algolia index and bulk-import into Typesense. Then rebuild the relevance logic one rule at a time: typo tolerance thresholds, synonyms, custom ranking (Typesense's sort_by and field weighting cover most of what Algolia's custom ranking does). This step is where most of the real engineering time goes — budget for it.
Run both systems side-by-side
Point a small percentage of search traffic (or an internal staging environment) at Typesense while production still runs on Algolia. Compare result quality, relevance ordering, and response times side-by-side on real queries — not synthetic ones.
Cut over with a feature flag
Use a feature flag or simple environment toggle to switch the storefront's search calls from Algolia to Typesense. This makes cutover instant and instantly reversible — if anything looks off, flip back with zero downtime while you fix it.
Keep Algolia live for a short overlap window
Don't cancel Algolia the moment you cut over. Run a 1–2 week overlap so you have an immediate fallback and can catch any edge-case query behavior your testing missed.
Decommission and reconcile costs
Once you're confident, turn off Algolia indexing, cancel the plan, and confirm your actual new hosting cost against what you projected.
What can go wrong (and how to avoid it)
- Relevance drift — solved by Step 4's side-by-side comparison before cutover, not after.
- Sync gaps during the overlap window — keep both indexes updated from the same product feed until Algolia is fully decommissioned.
- Underestimating ranking rule rebuild time — this is consistently the most time-consuming part; don't schedule cutover around a sale until it's done and tested.
Don't want to do this yourself?
This is exactly the migration work Indexwright handles end-to-end — schema mapping, relevance parity, zero-downtime cutover — so your team doesn't have to learn a new search engine from scratch.