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Product · seven mechanisms

Drawn from how the engine really works.

Each mechanism is shown as the thing it does. Hover a row and the engine speeds up.

01 / Tundra storage

Hot, warm, cold. One engine.

Automatic tiering keeps hot data on NVMe with many parallel IO queues and moves cold data to object storage. One query surface over all of it.

-- nothing to configure: tiering is automatic
SELECT * FROM orders
WHERE placed_at < now() - INTERVAL '2 years';
Fig. 01 · hover
02 / ANODE vectors

Vectors on the write path.

Native approximate nearest-neighbour search runs on the same rows you write, and the semantic layer is exposed to agents over MCP. No separate vector store to keep in sync.

Fig. 02 · hover
03 / DILITH commit

Atomic across servers.

A transfer between two accounts on different servers still commits atomically. DILITH is the distributed commit protocol behind multi-node writes.

Fig. 03 · hover
04 / Clone and PITR

Branch it. Rewind it. Merge it.

Instant clones of a database and point-in-time recovery are built in. Fork production to inspect a problem, or rewind to before it happened.

CREATE DATABASE dev CLONE prod;
Fig. 04 · hover
05 / JIT compilation

Queries compile to native code.

Queries are compiled to native machine code.

Fig. 05 · hover
06 / Global

One binary, any topology.

Nodes autodiscover each other, span zones, tolerate failures and can form a global cluster. Run standalone or clustered on the same binary.

Fig. 06 · hover
07 / Autonomous

The database that drives itself.

The database observes the workload and retunes memory and workers as it runs, keeping or rolling back each change. No tuning sprints.

Fig. 07 · hover

Every edition includes all of it.

No feature gates. The same engine runs on one node or a global cluster.

Postgres compatibleFull SQL surfaceJIT to native codeGPU executionOne live copySerializable MVCCPoint-in-time recoveryInstant branchingAutomatic cloud tieringUDFs in eight languages15 analytics packagesPartitioning and matviewsTLS and authentication
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