kynetradb
One Rust binary: BM25 search + vector + KV + document + auth + files + realtime + agentic admin.
vs
Algolia
SaaS search-as-a-service with typo tolerance, merchandising rules, A/B testing, and analytics.
Feature comparison
| Dimension | kynetradb | Algolia |
|---|---|---|
| Full-text search | BM25 — reference catalogue | BM25 |
| Vector search | Brute-force cosine evaluationAlgolia uses HNSW which scales better past ~100k vectors | HNSW |
| Auth | Preview scope | None |
| Row-Level Security | Preview scope | No |
| File storage | Preview scope | None |
| Realtime | Preview scope | None |
| Edge Functions | Preview scope | No |
| TypeScript SDK | Preview scope | No official client SDK |
| KV lookups | Preview scope | No |
| Document filter | Preview scope | Yes |
| LLM runtime | Preview scope | No |
| Outbound DB sync | Preview scope | No |
| Self-host | Preview scope | No (managed only) |
| Single binary | Preview scope | No |
| License | Preview terms — request a scoped evaluation | SaaS-only |
| Deploy targets | 19 target profiles | 0 listed target profiles |
| Free tier | Preview access by request | yes — 10k records, 10k search requests/mo |
When to pick Algolia
Best-in-class typo tolerance, DPR (dynamic re-ranking), and analytics for storefront search. Kynetra has no merchandising rules or analytics today.
- You need merchandising rules, A/B search testing, or built-in analytics — kynetradb has none of those today.
- Your team is already invested in Algolia's SDK and ecosystem.
When to pick kynetradb
- You want a comparison-led conversation about BM25 full-text, vector evaluation, and data-plane trade-offs.
- You need a product-specific implementation scope rather than a generic migration claim.
- You want to assess 19 hosting target profiles, including 5 Indian providers.
- You want a scoped preview conversation about the data, deployment, and operating boundary.
- You need to run on your own infra — Algolia is managed-only.
- You want a single binary with no runtime dependencies — no container fleet to operate.
Search query — both APIs side by side
Full-text search call. These are documentation-accurate shapes, not runnable end-to-end examples.
kynetradb
# kynetradb — BM25 search
curl -X POST https://your.host/v1/search \
-H "Authorization: Bearer $KEY" \
-H "Content-Type: application/json" \
-d '{
"q": "aurora espresso",
"top_k": 10,
"kind": "product"
}'Algolia
// Algolia — JavaScript client
const results = await index.search('aurora espresso', {
filters: 'kind:product',
hitsPerPage: 10,
});