products

Seven shapes. One substrate. One atomic write.

SQL, vector, graph, full-text, natural-language /ask, and BYOK LLM - all on a single hash-keyed k/v store. Cross-shape writes are atomic by construction.

01 Database

Single hash-keyed substrate. One atomic write spans every shape.

· atomic cross-shape writes
· snapshot bootstrap HA
· dedicated per-tenant compute

02 SQL

The SQL you'd write on paper.

· correlated EXISTS
· aggregate over expression
· window functions
· CASE WHEN

03 Vector

Four metrics. Four index variants.

· L2 · IP · Cosine · Manhattan
· dense HNSW + sparse
· PQ scaffold
· adaptive over-fetch

04 Graph

Seven algorithms shipped, not stubbed.

· PageRank
· all-simple-paths (bidir)
· shortest-path BFS
· triangle enumeration

05 Full-text

BM25 relevance on the same atomic write.

· BM25 · boolean · phrase
· 18-language stemming
· 9-language lemmatization
· UAX #29 + ICU tokenizers

06 /ask

Natural-language query routed across every shape.

· cost-informed planning
· EXPLAIN + cost annotations
· deterministic dispatch

07 BYOK LLM

Your key. Your audit. Your bill.

· OpenAI · Anthropic · Gemini · Groq
· envelope-encrypted at rest
· per-provider audit

how they compose

Any query can call any shape. EXPLAIN reveals the plan with per-node cost. /ask orchestrates the shapes when you don't want to write the plan yourself. Every write - across SQL, vector, graph, and full-text - commits atomically: all shapes or none.

full capability matrix

Every capability, one bearer token.

The whole surface, grouped into six pillars, one row per capability. Everything runs against the same managed instance - one endpoint, one writer, one consistency model.

query & modalities

Query & modalities.

Five query shapes over one row store, one writer, one bearer token — no glue, no drift.

SQL

Feature	What it does
SELECT / INSERT / UPDATE / DELETE	The standard four. UPDATE and DELETE address rows by primary key or by a WHERE that resolves to a key range.
GROUP BY + HAVING + aggregates	SUM, AVG, MIN, MAX, COUNT, COUNT DISTINCT. HAVING filters post-aggregation. Group keys can be expressions, not just bare columns.
INNER / LEFT / RIGHT / FULL OUTER JOIN	All four canonical join types with arbitrary boolean ON clauses. The planner picks hash, merge, or nested-loop based on key cardinality.
JOIN USING / NATURAL JOIN	Shorthand joins when both sides share a column name. Useful when junction tables follow a consistent key convention.
CROSS JOIN	Cartesian product for generated-data scenarios and small lookup-cross-product reports.
Joins up to 5 tables	Single-statement joins across up to five tables. Beyond five, break the query into intermediate views or pipeline the result through /ask.
Correlated subqueries	EXISTS, scalar subqueries in SELECT, and IN (subquery) in WHERE. The outer-row binding is resolved without materializing the inner side.
Window functions	ROW_NUMBER, RANK, DENSE_RANK, LAG, LEAD, SUM OVER, AVG OVER, with PARTITION BY, ORDER BY, and ROWS BETWEEN frames.
Recursive CTEs	WITH RECURSIVE for hierarchical walks (org charts, comment trees, dependency closures) that don't need the full Cypher surface.
JSON path operators	-> and ->> read a field from a JSON column. Indexable when the path is fixed; otherwise scanned.
EXPLAIN ANALYZE	Full plan tree with row-count estimates, actual rows, per-node time, and the index choice the planner made. Use ?explain=true on any /query call.
MVCC transactions (snapshot isolation)	Begin a transaction with /tx/begin, stage multi-statement writes, then commit or rollback atomically. Snapshot-isolation today.
Atomic cross-shape writes	A single INSERT can stage a row, its embedding, its full-text shards, and its outbound edges in one transaction. No two-phase glue in the app.

Cypher / graph query

Feature	What it does
MATCH + WHERE	Pattern-match nodes and edges, then filter on properties. The standard entry point for every graph query.
CREATE / SET / DELETE / MERGE	Add nodes and edges, update properties, remove them, or upsert with MERGE. Writes commit atomically with the row store.
OPTIONAL MATCH	Left-outer-join semantics for graph patterns. The match either binds or returns NULL for the optional part.
WITH	Pipeline operator. Project intermediate results, aggregate, then pass into the next match - the way you chain stages in a Cypher query.
Single-hop, multi-hop, undirected	Patterns like (a)-[:R]->(b), longer chains, and undirected (a)-[:R]-(b) for symmetric relationships.
Backward hop	<-[:R]- hops both as a standalone match and inside chains. The inverse edge index makes 'who points at me' as cheap as forward expansion.
Variable-length paths	(a)-[:R*1..5]->(b) for paths between one and five hops. Bounded so the planner can pick BFS depth-limit instead of unbounded expansion.
length(p) / nodes(p) / relationships(p)	Built-in functions for path inspection. length(p) returns hop count; nodes(p) and relationships(p) return the path's vertex and edge lists.
UNWIND	Turn a list into rows. Works on literals, the output of nodes(p) / relationships(p), and mixed lists from prior WITH clauses.
Parameters ($param)	Bind query inputs by name in WHERE, RETURN, and UNWIND. Lets you cache the compiled plan across calls with different bound values.
List comprehensions	[x IN coll WHERE pred \| expr] over literal lists at compile time and over column-path lists at runtime - the standard Cypher fold.
FOREACH (nested up to 3 levels)	Iterate a list and run a write block per element. Nested FOREACH unrolls to a flat write sequence so each element commits atomically.
CALL { subquery }	Inline a read-only subquery with CALL { ... } and consume its results via YIELD. Compose larger queries without breaking the single-statement boundary.
shortestPath	Shortest path between two nodes by hop count. For weighted shortest path, see the Graph algorithms section.
ORDER BY / SKIP / LIMIT / DISTINCT	Sort and paginate Cypher RETURN clauses. DISTINCT deduplicates result rows the same way it does in SQL.

Graph algorithms

Feature	What it does
Neighbors / BFS / DFS	Forward expansion from a starting node. Pluggable depth cap; results stream as the frontier expands.
Reverse traversal	Same expansion against the inverse edge index, so "who points at me" queries are O(degree), not full scan.
Shortest path (unweighted)	BFS-based shortest path between two nodes. Returns the path itself, not just the length.
Weighted shortest path (Dijkstra)	Dijkstra on a numeric edge property. Useful for cost, latency, or distance routing.
K-shortest paths (Yen's algorithm)	Top-K diverse shortest paths between two nodes. Use when one route isn't enough - rerouting, alternative-recommendation, lineage trees.
All simple paths	Enumerate every loop-free path between two nodes up to a hop bound. Bounded so the call terminates on dense graphs.
Connected components	Partition the graph into reachability classes. Returns a component id per node.
Triangle counting	Count triangles globally or per node. The local count is a clustering-coefficient input.
Degree centrality	Rank nodes by their in-degree, out-degree, or total degree.
Betweenness centrality	Brandes' algorithm. Identifies the bridge nodes whose removal would disconnect or fragment the graph.
Eigenvector centrality	Iterative eigenvector solve. Captures recursive importance - the well-connected-to-the-well-connected signal.
PageRank	Damped random-walk centrality with tunable damping factor and convergence tolerance. The standard ranking primitive.
Label propagation	Community detection by majority-label propagation. Converges quickly on most real graphs.
Louvain community detection	Modularity-optimisation community detection. Finds tighter communities than label propagation on graphs with clearer hierarchical structure.
Random walk + biased Node2Vec walks	Uniform random walks and Node2Vec p/q-biased walks. The walk stream feeds either downstream analytics or the embedding trainer.
Node2Vec embeddings	Skip-gram with negative sampling over Node2Vec walks. Persisted on the engine; topk_node2vec serves 'find similar nodes' without round-tripping through Python.

Vector search

Feature	What it does
Dense vectors + top-K	Submit an embedding and receive the top-K nearest documents by the configured distance metric.
HNSW index	Hierarchical Navigable Small World graph. Default index for any table over a few thousand vectors. Tunable ef_search per query.
Brute-force fallback	For small tables or when you want exact recall, top-K falls back to a linear scan. No code change - the planner picks it.
Filtered top-K (metadata)	Restrict the candidate set by an equality predicate on a metadata field before ranking. Stays fast for selective filters.
Pre-filter HNSW walker	Filter inside the HNSW walk instead of post-filtering the top-K. Selective filters never make you over-fetch then discard hits.
Sparse vectors	BM25-style sparse vectors for lexical retrieval. Same put/topk endpoints; the metric is dot-product.
Sparse IVF	Inverted-file index over sparse vectors. Scales sparse retrieval past the brute-force cliff without giving up the BM25-style scoring shape.
Hybrid sparse + dense (RRF)	Reciprocal rank fusion of a sparse and a dense query. One call, one merged ranked list - no client-side stitching.
IVF (inverted file index)	Voronoi-cell partitioning with k-means-trained centroids. Search visits the top-nprobe cells - the standard scale path past the HNSW comfort zone.
IVF-PQ (IVF + product quantization)	IVF partitioning layered on a PQ-compressed posting list. Roughly 32x less memory per resident vector at the same recall - the path to ten-million-plus tables.
Scalar quantization (int8)	Per-dimension int8 quantization. About 4x memory reduction with under 2% recall loss on typical embeddings.
Binary quantization (1-bit)	1-bit-per-dimension quantization with asymmetric scoring. About 32x memory reduction; recall stays at or above 0.80 on structured corpora.
Distance metrics: L2, cosine, dot, Manhattan	Four metrics, picked per table at the first put. The metric is locked once chosen so every query is comparable.
SIMD-accelerated kernels (f32)	AVX2 / NEON float32 kernels for distance computation. Owned in-tree - no math library wrapper to upgrade.
DELETE vector	Removes a vector by id. HNSW tombstones the node; IVF / IVF-PQ evict it from its posting list. Put-after-delete cleanly resurrects the slot.
Per-tenant isolation	Each tenant runs on its own instance. Your vectors share no memory, no cache, and no scheduler with anyone else's.

Full-text search

Feature	What it does
Unicode tokenization (UAX #29)	Unicode-correct word segmentation. Accented Latin, Arabic, and emoji all break on the expected boundaries.
ICU tokenizer (CJK / Thai / Khmer)	ICU segmenter for scripts that don't put spaces between words. Picked per (table, field) when the corpus is CJK or Southeast Asian.
Boolean queries (AND / OR / NOT)	Combine clauses with the standard boolean operators. Returns the full matching set, unranked, when ranking is not needed.
BM25 scoring	Standard BM25 with the canonical defaults (k1=1.2, b=0.75). Returns top-K ranked hits with the raw score per document.
Phrase queries	Match the exact ordered sequence of terms. Uses position lists, so single-word matches are filtered out.
Fuzzy / typo-tolerant matching	Levenshtein edit-distance matching with the term~N syntax. Edit-distance cap of 3 keeps the candidate set bounded on large indexes.
Synonyms	Customer-managed synonym maps, bidirectional expansion, configurable cap per term. Synonyms apply at query time, so changes take effect without a reindex.
Stemming (9 languages)	English Snowball plus stemmers for Spanish, French, German, Italian, Dutch, Swedish, Russian, and Portuguese. Reduces inflections to a shared root.
Multi-language analyzers	LocaleAnalyzer with built-in stopword lists for 9 languages. One field per locale or one mixed-locale field - your call.
Per-locale stopwords config	Override the built-in stopword list per (table, field). Useful when a domain term ('the', 'a') is meaningful in your corpus.
Highlighting / snippets	Returns matched-snippet text per hit with configurable open/close tags. Overlapping matches are merged for clean display.
Faceted search / aggregations	Group counts alongside the ranked hits, capped at 1000 buckets per facet. Supports the standard 'narrow by category' UI without a second query.
JSON document indexing	Index a JSON column field-by-field. Each addressable path becomes its own searchable field; the dotted path is the search field name.
Multi-field weighted merge	Search several fields in one call with per-field weights. Combine title and body, weighting title higher, in a single ranked list.

ai-native

AI-native.

Ask in plain English across every shape, or wire your own models and agents in.

Natural language & AI

Feature	What it does
Natural-language /ask	Plain-English questions compiled to a real query plan across SQL, vector, graph and full-text. The cost-walker informs the plan, so /ask picks the execution the planner would.
Cross-shape planning	One /ask can join a vector search to a graph walk to a SQL filter in a single request - no manual plan, no stitching across separate engines.
Bring-your-own-key LLM	Point /ask and embeddings at your own OpenAI, Anthropic or Gemini key. Your model choice, your rate limits, your spend.
MCP server	The official @originchain/mcp-server exposes query, vector and schema tools over Model Context Protocol to any MCP-aware agent, IDE or assistant.
RAG framework integrations	First-class LangChain and LlamaIndex integrations so retrieval, embedding and generation stay on one database.

scale & performance

Scale & performance.

A cost-based planner, SIMD kernels, MVCC, and both vertical and horizontal scale.

Scale & performance

Feature	What it does
Cost-based query planner	The planner chooses hash / merge / nested-loop joins, index vs scan, and shape order from real cost estimates - not a fixed rule set.
Cardinality bounds	Closed-form plus AGM / degree-LP row-count bounds tighten join order and index choice before a single row is read.
MVCC transactions	Snapshot-isolation transactions: begin, stage multi-statement writes, then commit or roll back atomically against a durable WAL.
Vertical scale	Resize compute from 2 vCPU to 64 vCPU per node with no export / import - your data stays where it is.
SIMD-accelerated kernels	AVX2 / NEON float32 distance and scan kernels owned in-tree - no third-party math library in the hot path.
EXPLAIN ANALYZE	Per-node cost estimate, actual rows and time, and the index the planner chose - on any query shape via ?explain=true.

reliability & operations

Reliability & operations.

High availability, recovery, self-healing, and zero-downtime schema change.

Reliability & operations

Feature	What it does
Multi-AZ high availability	A hot standby in a second availability zone with automatic failover on writer loss - lease-fenced, so there is never a split-brain writer.
Health monitoring & auto-heal	On-read health probes raise a degraded badge and alert; the control plane reconciles and restarts a hung engine without a human.
Online schema migrations	Add, alter and drop columns while reads and writes continue. Versioned, monotonic, applied with zero downtime.
Audit logs	Every authenticated request captured and queryable, with tamper-evident retention from 30 days to years.

security & governance

Security & governance.

Access control down to the row, encryption everywhere, and audit you can query.

Security & governance

Feature	What it does
Role-based access control	Fine-grained grants per role x object, enforced before a query executes - not filtered after the fact.
Row-level security	Per-row access policies so a tenant, team or user only ever sees the rows they are entitled to.
Scoped API keys	Per-key scopes, rotation and rate limits. Issue a read-only key for a dashboard, a write key for an ingest job.
Encryption everywhere (BYOK CMK)	Encrypted at rest and in transit, with customer-managed keys so you hold and can revoke the root of trust.
IP allow-list & private networking	Restrict all traffic to your CIDR ranges, or reach your instance over private networking only.

developer experience

Developer experience.

Native SDKs, Postgres wire, live subscriptions, ingestion, and a free tier to start.

Developer experience

Feature	What it does
Native SDKs (HTTP, Python, TS, Go)	Typed clients with retries and pagination built in, across HTTP, Python, TypeScript and Go.
Postgres wire compatible	Point existing psql clients, drivers and ORMs straight at your instance over the Postgres wire protocol.
Reactive /watch	Live subscriptions that push committed changes to your app as they happen - no polling loop.
Ingestion connectors	CSV / NDJSON upload and webhooks in the box; managed database sync for continuous load is in preview.
Query workbench	Tabs, saved queries and history synced to your account across devices - run SQL, Cypher, vector and FTS from the console.
Free tier	1 GB and the full multi-modal engine at $0 - scales to zero when idle, one endpoint, no card required.

try it

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