Find and shape records.
Filter fields, join related tables and aggregate results. Start with a registered schema and declared indexes.
Which articles are published?SQL quickstart Architecture / Distributed multimodal database
SQL, vector, graph and full-text in one engine. Follow a record from your application to its indexes, query results and deployment.
Inside the system
Switch views to see where each responsibility lives.
Prepare fields, an embedding and searchable text.
article:07 id: article:07
title: Battery guide
author: person:03Fields and declared relations
id: article:07
vector: [0.2, 0.8, …]You supply the embeddingEmbedding and metadata
id: article:07
text: Replace the battery…Choose fields to searchTerms and document references
A row write does not also submit its embedding or text. Your application coordinates these calls and their retries.
category = 'guides'Fields & rowsYour query embeddingIDs & distancesarticle → authorNeighbors & paths"battery replacement"IDs & scoresCombine rankings, fetch source records and build context when your workflow needs it.
article:07Source fields + matched evidenceUse one query model or coordinate several. Retrieval, ranking and answer generation remain separate decisions.
Accepts writes while holding the writer lease.
ActiveLag is possible
Replays changes received from the writer.
Promotion is a separate stepAn abrupt writer loss can lose recent writes that have not reached the standby. Promotion is operator-driven by default.
The query layer
A shared record ID connects the representations. Each query interface serves a different kind of question.
Filter fields, join related tables and aggregate results. Start with a registered schema and declared indexes.
Which articles are published?SQL quickstart Store embeddings from your chosen model. Query nearest neighbors with the same dimensions and apply metadata filters.
Which articles are similar?Vector quickstart Declare relations and traverse neighbors or paths. Use relationships to explore the context around a record.
Who wrote this article?Graph quickstart Index selected text fields and query words or phrases. BM25 ranking provides scored document matches.
Where is “battery replacement”?Full-text walkthrough The write path
For the native APIs, saving a row does not also create its embedding or full-text entry.
See the three-call exampleRegister fields, a primary key and relations. Use that record ID in each index entry.
Your application generates embeddings and chooses searchable text. Submit these through their own endpoints.
Track which calls succeeded. Retry failed requests and update or remove related entries when source data changes.
Retrieval
For a search or RAG workflow, query vector and full-text indexes separately, merge rankings in your application, then fetch source records by ID.
Vector hybrid search combines dense and sparse vectors. Combining vector results with BM25 is a separate application workflow.
Build a retrieval workflowDeployment
A dedicated deployment can pair a writer with a standby in the same region.
The writer streams committed changes to a standby. Recent writes may be missing after an abrupt writer loss; promotion is operator-driven by default.
The standby follows the writer; backups provide a separate path to restore data.
Explore deployment optionsOperations
Monitor the writer, observe replication and practice restore. Each gives you a different view of database health.
Learn what a successful write means on the primary, with endpoint-specific behavior in the durability guide.
Write durabilityRestore from snapshots and available archives. The guide covers recovery points and current preview limitations.
Backup and restoreFollow health, usage, write errors and replication lag. Use the operations guide to connect monitoring and incident response.
Operations guideStart building