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Support and limitations

Exactly what is implemented, what is not, and which guarantees depend on you rather than on Ptah.

PostgreSQL YDB
Database PostgreSQL with the pgvector extension YDB, through its own vector functions and indexes
Provider API OpenAI-compatible /v1/embeddings OpenAI-compatible /v1/embeddings
Vector types vector, halfvec, sparsevec float
Metrics cosine, l2, inner_product cosine, l2, inner_product
Index methods hnsw, ivfflat vector_kmeans_tree
Consistency modes outbox, immutable immutable
Target layouts source columns, own table source columns, own table

The --db-url scheme decides the engine: a postgres:// URL, or a keyword/value DSN with no scheme, is PostgreSQL, and a ydb:// or ydbs:// URL is YDB. Every verb, and the inference_plan and inference_status tools of ptah mcp, runs the same lifecycle on both.

No other database engine. MySQL, SQLite, ClickHouse, SQL Server, Oracle and the rest are not supported, and a URL naming one is refused by name:

Terminal window
$ ptah inference plan --spec spec.yaml --db-url "mysql://localhost:3306/db"
error: ptah inference works against PostgreSQL with pgvector and against YDB,
and "mysql://" names another engine: a generation's run state and its vectors
need one of those two, so there is nothing here to run against mysql

The PostgreSQL family is refused too. CockroachDB, YugabyteDB and Spanner speak the wire protocol pgvector’s driver connects with and have no pgvector.

The inference_plan and inference_status tools of ptah mcp give the same answers for a configured target, before they connect to it.

No outbox on YDB. The outbox records each source change with a row trigger in the transaction that makes it, and YDB has no triggers. plan reports it as a blocker and prepare refuses it before anything is created:

Terminal window
$ ptah inference prepare --spec spec.yaml --db-url "ydb://localhost:2136/local" --run-id r1
error: not supported on YDB: YDB 26.2.1.14 has no triggers, and the outbox
consistency mode records each source change with a row trigger in the
transaction that makes it; use consistency mode immutable, which is the mode a
YDB generation supports

A YDB source that can change is migrated as a paused source; see Migrate a paused source.

On YDB the key is the primary key. source.key_fields has to name the source table’s primary key, in key order. A YDB table keeps its rows in primary-key order, so the keyset scan is a range read and a write addresses one row; any other key would make each page a full read. A specification naming other columns is refused with the key the table has.

A YDB vector index needs a line that has one. YDB 25.1 builds a vector_kmeans_tree index only with its EnableVectorIndex feature flag on. index refuses on a server whose capabilities have no vector_indexes, and reads the cluster’s flags when the URL names its monitoring endpoint.

On YDB 25.1 and 25.2 an indexed generation takes no more writes. The vector index on those lines answers as it stood at its build, while the table moves on. A write into a generation whose index exists is refused there, naming the capability, vector_index_maintained_on_write, and the line; YDB 25.3 and later take the write into the index. Build the index after the backfill, as the lifecycle does, and the refusal is reached only when a source the specification declares immutable has changed.

No cascade on a YDB table of the generation’s own. YDB has no foreign keys, so deleting a source row does not delete its vectors. Verification reports such a row as outside the generation’s source scope.

No other provider API. A provider that is not OpenAI-compatible needs a gateway in front of it.

One set of chunks per source row, in a table of its own. A row split into several vectors needs layout: own_table; see Choose a target layout.

No change-data-capture connectors. The outbox is triggers on your PostgreSQL table. There is no logical-replication, YDB changefeed or CDC-tool integration.

No Kubernetes operator. Nothing reconciles a generation change from a custom resource. The verbs run as Jobs and a rollout gates on status --require-ready; see Run in Kubernetes.

Ptah is not an inference server. It does not run a model, hold one in memory, schedule a GPU, store model weights, or answer a search query.

  • A change that committed to the source has an outbox event, under outbox, because the event and the change are one transaction — and catch-up reads every one of those events. Its cursor is a transaction identity and a sequence together, so a page that fills partway through a transaction resumes inside that transaction rather than past it.
  • A vector and its checkpoint are written in one transaction, so there is no state in which the work landed and the record of it did not. On YDB it is one serializable transaction, and a conflict with another transaction aborts it and runs it again on what is there now.
  • A write never crosses generations: a row belonging to another generation is refused rather than overwritten.
  • A stale result does not win. A provider answer computed from a source version the row has moved past is discarded rather than written.
  • A deleted row stays deleted: a tombstone survives an embedding that was already in flight.
  • A worker whose lease was taken cannot commit, because the fencing token is checked in the write itself rather than read and then trusted.
  • A cutover binds to a plan digest, and what is true now is checked again at the moment it runs.
  • That the source is what you said it is. mutable: false is a declaration Ptah takes and measures afterwards; it cannot stop a write.
  • That the model is stable. If the provider exposes no immutable revision, plan reports the reproducibility as partial and names the reason. It cannot detect a model that changed under a stable name.
  • That your queries read the active generation. Ptah moves a pointer in its own tables. Your application’s SQL names a column, and connecting the two is yours.
  • That the query vector comes from the same model. A query embedded by a different model is not comparable with the stored vectors, and nothing errors.
  • That the metric and the operator match. <=> for cosine, <-> for l2, <#> for inner product. A mismatch returns the wrong rows in a plausible order.
  • That the results are good. Verification measures shape, coverage and freshness. Quality is evaluate, against a corpus you write.
  • A change made by a path that bypasses the source table’s triggers — COPY with triggers disabled, a replication apply, a direct catalog edit.
  • A provider that logs or retains your inputs.
  • Whether the columns you chose for input_fields are the right ones.
  • Two triggers and one companion-table insert per changed row, under outbox, for the length of the migration.
  • On YDB, a lifecycle operation reads the whole run-state registry inside its transaction, so two operations on different generations can abort each other and run again. A batch checkpoint reads only its own run.
  • Five columns on the target table per generation, and two generations coexist by design.
  • The provider bill for the whole corpus, per generation.
  • A vector index build that is concurrent but not free.

The limits above describe the checked build. Any unavailable inference behavior is marked at the sentence that names it.