Painless migration
Works with what you already use. Keep your existing queries and drivers, and switch in an afternoon, not a quarter.

Ultra-high-performance data systems
Why TETRA
Tetra is a graph database rebuilt from the ground up.
Faster
Products, lower costs, painless migration.
Works with what you already use. Keep your existing queries and drivers, and switch in an afternoon, not a quarter.
A single, lightweight engine that runs anywhere and embeds directly inside your product. no heavy stack to babysit.
Efficiency is savings. The same work on a fraction of the memory means smaller instances and a lighter monthly bill.
Compact storage means smaller snapshots, cheaper retention, and faster recovery when it matters most.
Benchmarks
What you actually get moving off a pointer-and-index engine.
Full methodology, datasets and reproduction steps ship with the public benchmark suite.
TETRA SaaS
A managed graph layer that sits on top of the stack you already run. Point it at your data, keep your app and queries, and let TETRA handle the engine, scaling and ops.
The graph layer, run for you. Point a Bolt driver at it and send Cypher. Updates, backups and failover are ours.
Untouched. Same Bolt driver, same Cypher. The connection string is the change.
Stays where it is. TETRA layers on top of what you already run rather than replacing it, so there is nothing to rip out.
Wherever it already lives. No reserved RAM to size, no cluster to stand up. You pay for the queries you run.
Flat managed pricing on top of your stack. No reserved RAM, no idle cost.
TETRA Embedded · On-prem
One small binary you ship inside your application: on a laptop, at the edge, or in your customer's private cloud. For TETRA, on-prem and embedded are the same thing: there is no separate cluster to run, so there is nothing to install in the datacentre but your own product.
Collapsive architecture
We collapse the time and money it takes to build and run software.
A pointer-and-index engine spends its life chasing references around memory. TETRA does not chase them at all. Once nothing is chasing pointers, whole layers of the stack have nothing left to do: no index to maintain, no cache to warm, no cluster to babysit. That is what collapses. Not the query. The stack.
A graph stack today
The same stack, on TETRA
Every layer that disappeared had the same job: finding things quickly in a structure
built for chasing pointers. Change the structure and the job stops existing, so
there is nothing left to maintain, warm, or babysit.
How we change it is maths, and the maths is ours for now. It is the
one thing on this page we're not publishing yet, so the benchmarks ship with their
datasets and reproduction steps instead, and you're welcome to watch it run on a
graph of your own.
Where TETRA fits
Stay close to the build
We're opening TETRA up slowly, and we'd like to know who's out there. Tell us what you're working on and we'll keep you in the loop as we get closer to launch. If it turns out we're a good fit for each other, there may be more to talk about.
Register your interest
Tell us who you are and what you're working on. It takes about a minute, and a real person reads it.