Replace four infrastructure systems with one managed database. Rows, vector embeddings, full-text postings and graph edges commit on the log together - every write atomically visible to every shape. Single-tenant. Region-isolated. Sub-100 ms in-region.
$ curl https://oc-thunder.ap-south-1.originchain.ai/v1/ask \
-H "Authorization: Bearer $OC_TOKEN" \
-d '{"q": "last 7 closes for NIFTY"}'{
"plan_id": "tpl_nifty_close_lastN",
"rows": [
{ "date": "2026-04-15", "close": 22456.30 },
{ "date": "2026-04-16", "close": 22512.85 },
{ "date": "2026-04-17", "close": 22489.10 },
{ "date": "2026-04-18", "close": 22534.75 },
{ "date": "2026-04-21", "close": 22601.40 }
],
"meta": { "latency_ms": 42, "cache_hit": true,
"region": "ap-south-1" }
}
Working with NVIDIA on GPU-accelerated vector search, managed embedding hosting, and self-hosted LLM tiers. Learn more →
Most modern AI stacks fan a single user action across four databases - a relational store, a vector index, a search engine, and a graph. Each has its own bearer, its own SDK, its own billing line, and its own way of being out of sync at 3 am. OriginChain replaces all four with one managed database. One write lands every shape atomically.
Retire four contracts. Onboard one. Stop coordinating four maintenance windows for a single feature release.
The row, its embedding, its full-text postings, and its graph edges commit on the log together. No reconciliation jobs. No "the search index is 8 hours behind" disclaimers.
One SDK, one auth model, one observability surface. New AI features land without a Debezium pipeline + four retry queues + a 3 am reconciliation cron.
SQL, vector, full-text, graph, and natural language all run against the same managed database - single tenant, region-isolated, with replication and point-in-time recovery you don't have to wire up.
SQL · Vector · Full-text · Graph · Natural language, all on the same store and the same bearer. Write your data once, query it four ways without bolting on a separate engine.
p99 under 8 ms for typed SQL. HNSW vector top-k at 100k vectors: recall@10 = 0.96 with p99 109 ms in default high_recall mode, or p99 37 ms in fast mode (recall 0.69). Warm natural-language queries return in under 50 ms thanks to plan caching.
Your own EC2, your own EBS, your own bearer - locked to the region you pick. Zero shared resources, zero noisy neighbours, zero cross-tenant blast radius.
Provisioning, TLS, backups, replication, and observability run for you. You ship product features; we run the database underneath them.
POST a sentence to /ask and get rows back. Plan-cached natural-language queries execute in-region with sub-50 ms warm latency and a stable schema-aware response shape.
RPO=0 on paid tiers and ~25 second failover keep your application online through hardware loss. WAL is archived to S3 continuously, so you can restore to any timestamp.
Every customer gets a dedicated database instance in their chosen region. No shared compute. No shared storage. No cross-tenant query path. The architecture is the compliance answer - not a checkbox bolted on top.
GDPR, DPDP, and sector-specific data-residency rules are satisfied by where the bytes live and who can touch them - and you hand both answers to an auditor in writing.
One EC2 per customer, not a shared cluster. Noisy neighbours cannot exist by construction.
Frankfurt, Paris, Stockholm - pick where the bytes live. EU-resident data never leaves the EU.
Each tenant's bearer scopes to its own ULID. A leaked credential cannot reach another customer's instance.
DPA, sub-processor list, deletion timelines all in writing. Self-service account deletion with a 30-day grace window.
Concrete p99 numbers, not averages - the ceiling your app can plan around for SLAs, agent loops, and user-facing reads on a managed database.
End-to-end p99 in-region for typed queries against your managed database.
After the first ask of a shape, the plan is durably cached and every repeat skips compile.
Default high_recall mode hits recall@10 = 0.96 at 100k vectors. Fast mode runs p99 37 ms at recall 0.69 when latency dominates.
First ask of a brand-new shape from another continent - including the round trip.
p99 measured at the API edge · in-region unless noted · vector topk on managed HNSW with f32 SIMD distance kernels, default high_recall mode (recall@10 = 0.96 at 100k)
Open a connection to /watch
and receive row-level inserts, updates, and deletes the moment they
commit. Standard server-sent events, ordered, exactly-once,
resumable from any cursor - no client SDK required.
Power live dashboards without a polling loop. Drive agent loops on fresh state. Invalidate caches the instant a row changes. The same managed database serves your queries and pushes your changes - no separate change-data pipeline to operate.
curl -N https://oc-thunder.ap-south-1.originchain.ai/v1/tenants/acme/watch \
-H "Authorization: Bearer $OC_TOKEN" \
-H "Accept: text/event-stream" \
-d '{"table": "orders", "where": "status = \'pending\'"}'event: row.insert
data: { "id": 48201, "customer": "Aether Labs", "total": 1842.00,
"status": "pending", "ts": "2026-05-01T09:14:22.018Z" }
event: row.update
data: { "id": 48198, "status": "pending → paid",
"ts": "2026-05-01T09:14:22.214Z" }
event: row.insert
data: { "id": 48202, "customer": "Northwind", "total": 612.50,
"status": "pending", "ts": "2026-05-01T09:14:22.881Z" }
event: row.delete
data: { "id": 48180, "reason": "cancelled",
"ts": "2026-05-01T09:14:23.402Z" }
// ... the connection stays open. Every change to a matching row
// arrives within milliseconds, in order, exactly once.Push row-level changes straight to the browser. The dashboard stays in sync with the database to the millisecond, on any tier, in any region.
Wake your agent when the world changes, not on a timer. Subscribe to the rows that matter and react the instant they commit.
Bust the right cache key the moment a row changes. No TTL guesses, no race windows, no stampede when many keys expire at once.
SQL, vector search, full-text BM25, and graph traversal on one managed database. The same write is visible to every shape, atomically. One bearer token, one billing line, one consistency model - instead of three services kept in sync by hand.
| what you build → | SQL with JOINs INNER / OUTER / GROUP BY / HAVING | Vector search managed HNSW with filters | Full-text BM25 ranked search, 18 languages | Graph traversal BFS, paths, weighted Dijkstra | Plain-English /ask sentence in, rows out | Reactive /watch SSE stream of deltas | Point-in-time recovery sub-second restore granularity | Single-tenant region-isolated EC2 per customer |
|---|---|---|---|---|---|---|---|---|
| OriginChain the AI-native database SQL, vector, full-text, and graph against a single managed database. One bearer token, one consistency model, one bill. Atomic writes across every shape. | ● | ● | ● | ● | ● | ● | ● | ● |
| Pinecone managed vector database Vector-only. No SQL, no full-text, no graph, no point-in-time recovery, no single-tenant deployment. You bring a relational store and stitch joins in your app. | ○ | ● | ○ | ○ | ○ | ○ | ○ | ○ |
| Postgres row-store + extensions SQL is great. pgvector and tsvector exist but you operate them. No managed HNSW at scale, no native BM25 ranking, no graph traversal, no /ask, no reactive views. | ● | ◐ | ◐ | ○ | ○ | ○ | ● | ◐ |
| Elasticsearch search index Full-text BM25 is first-class. SQL is a translation layer with no real JOINs. Vector is bolted on. No graph. No natural-language /ask. Snapshots, not sub-second PITR. | ◐ | ◐ | ● | ○ | ○ | ○ | ◐ | ◐ |
| Neo4j graph database Cypher graph traversal is first-class. No SQL, no managed HNSW vector search, no native BM25, no plain-English ask. You operate it; you stitch the rest yourself. | ○ | ◐ | ◐ | ● | ○ | ○ | ◐ | ◐ |
Ship faster with one SDK, one auth model, and one observability surface. No more reconciling three vendor invoices or coordinating four maintenance windows for a single feature release.
Atomic writes across rows, vectors, indexes, and graph edges. No dual-write logic, no eventual-consistency bugs between your relational store and your vector index, no stale search results after an update.
A dedicated, region-isolated database per customer. Predictable performance, no noisy neighbours, and residency you can hand to your auditor in writing.
OriginChain is the AI-native database for teams that need SQL, vector, full-text, graph, and natural-language queries on one managed endpoint. Single tenant, region-isolated, fully hosted - provision in under two minutes, query in milliseconds.
Pick a region, pick a tier, and we provision a single-tenant instance on AWS. The first query you send is the first query we'll show you how to write - in English.