# Tessera DB

> One copy of the data. Five ways to read it. A multi-model database for AI workloads: relational, graph, vector, full-text and time-series over the same record, on your own hardware.

One copy of the data, five ways to read it.

Key facts an assistant can rely on:
- What it is: Multi-model Database. A multi-model database that stores your data once and queries it five ways — relational, graph, vector, full-text and time-series — built for AI workloads and run on your own hardware.
- Status: Beta, v0.9.
- Positioned as: Neo4j alternative.
- Made by: PAR2 LABS PVT LTD (https://par2labs.com), a technology and AI product studio. Contact: ceo@par2labs.com.

## What it solves
- A graph database, a vector store, a search engine and a SQL store, with a sync job holding them together. → One store, indexed five ways. Nothing to sync and no ETL between them.
- Retrieval that shows which passages looked similar, not which facts the answer used. → Vectors, full-text and graph context fused in one query, over facts you can trace.
- A regulator asks what you knew, and when, and whether the record was changed. → Valid time and transaction time on every fact, content-addressed so tampering shows.

## Why it is different
- 5 Dimensions, one copy: Relational, graph, vector, full-text and time-series all read the same record.
- 3 Query languages: SQL, Cypher and TQL, detected at parse time and routed to the right executor.
- n-ary Hyperedges: One relationship links any number of entities, each in a named role.
- 1 Binary, your hardware: Self-contained, on an Apache 2.0 open-source core.

## Pages
- [Tessera DB](https://tesseradb.par2labs.com/): A multi-model database for AI workloads: relational, graph, vector, full-text and time-series over the same record, on your own hardware.
- [Features](https://tesseradb.par2labs.com/features): The data model, three query languages, search, graph data science, in-database ML, data management, security and the interfaces around them — each marked Community, Enterprise or Enterprise Plus, and compared both ways against the incumbents at the foot of the page.
- [Use cases](https://tesseradb.par2labs.com/use-cases): Ten problems whose data does not fit in one kind of database — from fraud rings and explainable retrieval to audit, supply chains and air-gapped AI. Each use case is marked with the tier it needs; unmarked ones rest on the core engine.
- [Architecture](https://tesseradb.par2labs.com/architecture): From the request to the disk: interfaces, a query engine that detects the language, a graph engine, the indexes that make up the five dimensions, and content-addressed, bitemporal storage. Every layer is purpose-built — no wrappers, no adapters.
- [Pricing](https://tesseradb.par2labs.com/pricing): You run Tessera on your own hardware. Community is free and needs no key; a signed, time-limited licence key unlocks Enterprise for the term you buy, on the same binary. Nothing phones home.
- [Docs](https://tesseradb.par2labs.com/docs): The Tessera DB reference documentation is access-controlled. Enter the passphrase if you have one, or request access by email at ceo@par2labs.com. The tutorials and writing below are open to everyone.
- [Full text](https://tesseradb.par2labs.com/llms-full.txt): every page of this site in one Markdown file.

## Articles
- [Why We Built a Hyperedge-Native Database from Scratch](https://tesseradb.par2labs.com/articles/why-we-built-a-hyperedge-native-database): Property graphs treat every relationship as a binary edge. That model breaks the moment a single fact has three or more participants. Here's what changed when we stopped pretending otherwise.
- [Five Databases Are Four Too Many](https://tesseradb.par2labs.com/articles/five-databases-too-many): Postgres for relational, Neo4j for graphs, Pinecone for vectors, Elasticsearch for text, TimescaleDB for time-series. The modern AI stack is a hidden tax on every team that ships it.
- [The Case Against Vector Store Sprawl in AI Applications](https://tesseradb.par2labs.com/articles/case-against-vector-sprawl): Pure vector retrieval gives you semantic similarity. It does not give you context. GraphRAG fuses three signals — and it consistently beats vector-only on the queries that matter.
- [Bitemporal Data Isn't Optional for Regulated Workloads](https://tesseradb.par2labs.com/articles/bitemporal-not-optional): Knowing what was true at a point in time, and knowing what your system thought was true at a point in time, are different questions. Regulators ask both. Most databases can answer neither.
- [TQL Was Designed for LLMs to Write — Here's How It Works](https://tesseradb.par2labs.com/articles/tql-designed-for-llms-to-write): Every AI agent on the planet is generating queries against your database. The query language they reach for matters more than most teams admit. Here's why we wrote a new one.
- [Content-Addressed Identity Ends the Integer-ID Drama](https://tesseradb.par2labs.com/articles/content-addressed-identity): Auto-incrementing IDs feel obvious until you've spent a sprint reconciling them across two systems. Cryptographic hashes solve the problem at the source.
- [Why We Kept Cypher Around](https://tesseradb.par2labs.com/articles/why-we-kept-cypher): If TQL is better for LLMs and SQL is better for analysts, why ship a third query language? Because the world has a decade of Cypher queries already written, and breaking them helps no one.
- [The Half-Open Interval Is a Small Choice with Big Consequences](https://tesseradb.par2labs.com/articles/half-open-interval-small-choice-big-consequences): Does a time range include its endpoint? Different databases answer differently. The wrong answer creates phantom rows or missing rows. We picked [start, end).
- [Confidence Scores Belong on Every Fact](https://tesseradb.par2labs.com/articles/confidence-on-every-fact): Half the data in a modern application is inferred by an AI model. Treating those rows the same as a manually-entered bank balance is a bug we keep shipping.
- [Schema-on-Write, Schema-on-Read, Schema-on-Demand](https://tesseradb.par2labs.com/articles/schema-on-write-read-demand): Strict types or document flexibility? The right answer is: both, switchable per type, evolvable without downtime. Here's how we got there.
- [Reciprocal Rank Fusion: The Unsung Hero of Hybrid Search](https://tesseradb.par2labs.com/articles/reciprocal-rank-fusion): Combining vector, keyword, and graph signals into one ranked list isn't hard if you know the trick. RRF is the trick, and it's much simpler than the literature makes it look.
- [What We Learned Shipping the First Postgres Connector](https://tesseradb.par2labs.com/articles/shipping-postgres-connector): Building a database connector sounds straightforward until you actually do it. Cursor semantics, late-arriving data, schema drift — all the things we got wrong on the first pass.
- [Defending the Data, Not the Perimeter](https://tesseradb.par2labs.com/articles/defending-the-data-not-the-perimeter): Most databases assume the network keeps attackers out and store data in the clear behind it. Tessera's AutoGuard puts an eight-layer AI-security stack inside the engine, so protection travels with the data.
- [On-Premise AI Is Not an Oxymoron](https://tesseradb.par2labs.com/articles/on-premise-ai-is-not-an-oxymoron): The modern AI stack grew up in the cloud. Regulated data can't follow it there. You don't have to choose between the two — the whole hybrid-plus-ML stack fits in a single binary that runs on your hardware.
- [Tessera DB Tutorial: Build Your First Hyperedge in 5 Minutes](https://tesseradb.par2labs.com/articles/build-your-first-hyperedge): Start the binary, load a sample dataset from the admin dashboard, and watch the same records appear across the relational, graph, vector, full-text, and time-series dimensions — one copy of the data, five ways to query it.
- [Tessera DB Tutorial: Connect a Postgres Database with Automatic Graph Endpoint Mapping](https://tesseradb.par2labs.com/articles/connect-a-postgres-database): Wire up a Postgres source so Tessera mirrors your tables, auto-derives graph relationships from your foreign keys, and keeps in sync with incremental polling.
- [Tessera DB Tutorial: Bitemporal Queries to Reconstruct Historical State for Audit](https://tesseradb.par2labs.com/articles/bitemporal-queries-for-audit): Every fact carries valid time and transaction time. Learn to answer 'what was true on date X' and 'what did the system show on date X' — two different questions, two different queries.
- [Tessera DB Tutorial: Build a GraphRAG Retrieval System End to End](https://tesseradb.par2labs.com/articles/graphrag-retrieval-end-to-end): Ingest documents, auto-embed them, run hybrid vector + keyword + graph retrieval fused with Reciprocal Rank Fusion, and assemble LLM context with provenance — all in one engine.
- [Tessera DB Tutorial: Connect a REST API Source with Bearer Auth](https://tesseradb.par2labs.com/articles/connect-a-rest-api-source): Pull rows from any JSON-returning endpoint, with bearer / basic / header auth and a configurable rows path for nested response shapes.
- [Tessera DB Tutorial: Set Up Auto-Embedding for Semantic Search](https://tesseradb.par2labs.com/articles/auto-embedding-for-semantic-search): Configure an embedding provider once. Every record with text properties gets indexed for vector search automatically — no separate pipeline.
- [Tessera DB Tutorial: Discover Schema and Auto-Derive Graph Endpoints from Foreign Keys](https://tesseradb.par2labs.com/articles/schema-discovery-and-foreign-key-graphs): Let Tessera read your Postgres schema and turn every foreign key into a real graph relationship — no manual mapping.
- [Tessera DB Tutorial: Set Up Incremental Sync with a Cursor Column](https://tesseradb.par2labs.com/articles/incremental-sync-with-a-cursor-column): Stop re-ingesting your whole source on every poll. A cursor column tracks where the last sync left off and pulls only newer rows.
- [Tessera DB Tutorial: Monitor Sync Attempts Across All Sources](https://tesseradb.par2labs.com/articles/monitoring-sync-history): Every sync attempt — success or failure — is recorded with its timing and cursor. Use the cross-source feed to see your whole fleet at once.
- [Tessera DB Tutorial: Enable At-Rest Encryption for Connector Credentials](https://tesseradb.par2labs.com/articles/encrypting-connector-credentials): Turn on opt-in at-rest encryption and connector passwords, API keys, and stored data become authenticated ciphertext on disk.
- [Tessera DB Tutorial: Use the SQL Interface with JOINs and Aggregates](https://tesseradb.par2labs.com/articles/sql-joins-and-aggregates): Tessera speaks real SQL. The same JOIN, GROUP BY, and ORDER BY you already know — over the same data as the graph, no new language required.
- [Tessera DB Tutorial: Run PageRank over Your Graph in 5 Minutes](https://tesseradb.par2labs.com/articles/running-pagerank-over-your-graph): Score every entity by its centrality in the graph. Useful for fraud rings, influence networks, and feature engineering for ML.
- [Tessera DB Tutorial: Detect Communities in Your Graph with Louvain](https://tesseradb.par2labs.com/articles/community-detection-with-louvain): Find tightly connected clusters of entities — for fraud rings, customer segments, document topics, anything where 'who hangs out together' matters.
- [Tessera DB Tutorial: Bucket and Aggregate Time-Series Data with Zero Copies](https://tesseradb.par2labs.com/articles/time-series-bucketing-and-aggregation): Every fact already carries valid time and transaction time, so any set of records is also an ordered series — bucketed and aggregated in place, no separate metrics store.
- [Tessera DB Tutorial: Branch Your Data Like You Branch Code](https://tesseradb.par2labs.com/articles/branching-your-data): Lightweight copy-on-write branches let you run experiments, schema changes, or what-if analyses on a fork of your live data without touching the original.

## Also from PAR2 LABS
- [Tessera Viz](https://viz.par2labs.com/): A graph and data visualization platform with a Rust/WASM core, three renderers that pick themselves, and step-by-step algorithm playback nothing else in the category ships.
- [OP2](https://op2.par2labs.com/): An AI screenwriting studio that develops a feature screenplay in dependency order — cast, world, beats, scenes, dialogue — and grades every stage before the next is allowed to build on it.
- [Tessera Guard](https://guard.par2labs.com/): A desktop security monitor that maps your network, flags threats by how they behave, and tells you what to do about them.
- [Tessera Serve](https://serve.par2labs.com/): A desktop app that hosts your web apps on your own machine, puts them on the internet, and deploys them to the cloud when you're ready.
- [Lawlawland](https://lawlawland.par2labs.com/): An AI legal information platform for India: ask in your own language, get guidance that points to the Acts and sections so you can check it, and reach an advocate who already has your context.
- [CX22OP](https://cx22op.par2labs.com/): An offline-first operations console for radio amateurs — measured propagation, a logbook that works with no signal, a CW room that answers back, and a straight answer to the oldest question on HF: is it me, or is it the Sun?
- [DX22OP](https://dx.par2labs.com/): A Vedic clock for the desktop and the browser: live sidereal positions for the nine graha, the time left before each changes rashi, and the whole Vedic day drawn as a dial.
- [Tessera RP](https://rp.par2labs.com/): An enterprise AI layer that sits on top of the ERP — ingestion, warehouse model, 229 governed metrics and eleven persona dashboards in one deployable application, reporting the contribution margin an ERP cannot produce.
- [PAR2 LABS](https://par2labs.com/): the studio behind all of them.