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 (parallel, 1.07 ms @ 100k) | BM25 |
| Vector search | Brute-force cosine (2.21 ms @ 100k, no HNSW yet) Algolia uses HNSW which scales better past ~100k vectors | HNSW |
| Auth | Built-in (bcrypt + JWT, 3 roles) | None |
| File storage | Built-in (local + S3-compatible, SigV4) | None |
| Realtime | SSE (topic + kind filters) | None |
| KV lookups | Yes (point lookup by ID) | No |
| Document filter | Yes (JSON predicates) | Yes |
| LLM runtime | Yes (Anthropic + OpenAI + Ollama) | No |
| Outbound DB sync | Yes (12 sinks: Postgres, DynamoDB, BQ, Firestore, CF, Mongo, Redis, Pinecone) | No |
| Self-host | Yes (single binary) | No (managed only) |
| Single binary | Yes | No |
| License | Apache-2.0 | SaaS-only |
| Deploy targets | 18 (1-click) | 0 (1-click) |
| Free tier | Yes — Apache-2.0, self-host free | 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 need BM25 full-text + vector similarity + auth + files + realtime in one process — no external services.
- You want to deploy to 18 targets (including 5 Indian providers) from one Dockerfile.
- You need outbound sync to 12 databases (Postgres, DynamoDB, BigQuery, Firestore, Cloudflare, MongoDB, Redis, Pinecone) with zero extra code.
- You want an agentic admin with 10 typed LLM-driven actions and a persisted audit trail.
- You want Apache-2.0 with a self-host path that doesn't require an ops team.
- You need to run on your own infra — Algolia is managed-only.
- You want a single binary with no runtime dependencies.
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,
});