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Connic
Platform

Database

Every environment includes a managed database. Store data in named collections, query with expressive filters, and browse your data in the dashboard. No migrations, no schema setup, no external hosting required.

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Collections
Group documents into named collections. Names must start with a letter and use only lowercase letters, digits, and underscores (max 50 chars).
Zero-setup, auto-creation
Collections are created on-demand the first time you insert a document. No setup or configuration before your agents start writing data via database tools.
Expressive filters
Filter with $eq, $ne, $gt, $gte, $lt, $lte, $in, $nin, $and, $or, $not, $exists, $contains, $regex. Sort, paginate, project fields, or enumerate distinct values.
Fast at scale
Queries are indexed and optimized for fast lookups across large collections. All filter values are parameterized, never string-interpolated.

Data model

Each document is free-form. You define the fields. There's no fixed schema. Every document gets three system-managed fields:

  • _id: auto-generated UUID, unique within the collection
  • _created_at: ISO 8601 timestamp set on insert
  • _updated_at: ISO 8601 timestamp updated on every write
document-shape.py
# Every document has these system fields alongside your own data:
{
    "order_id": "ORD-001",
    "status":   "pending",
    "amount":   99.50,
    "_id":         "550e8400-e29b-41d4-a716-446655440000",  # auto-generated UUID
    "_created_at": "2026-01-15T10:30:00Z",
    "_updated_at": "2026-01-15T10:30:00Z",
}

Auto-creation

You never need to create a collection explicitly. The first call to db_insert creates the collection.

tools/orders.py
# No setup needed - the collection "orders" is created automatically
# the first time db_insert runs
result = await db_insert("orders", {
    "order_id": "ORD-001",
    "customer": "alice@example.com",
    "amount":   99.50,
    "status":   "pending",
})

You can also create collections manually from the Storage → Database tab in the dashboard.

Dashboard

The Storage → Database tab in the project dashboard lets you:

  • View all collections with document counts and storage sizes
  • Browse documents with filter and sort controls
  • Generate filters and sort order from plain-language requests
  • Insert documents manually
  • View the inferred schema: field names, types, and fill rates
  • Create and delete collections
The Storage → Database tab in the dashboard: a Collections sidebar listing customers (3), incidents (2), and orders (3), beside the selected customers collection — 3 docs, 56.0 KB — with its Browse tab showing three documents in a table of id, name, tier, health, created_at, and updated_at columns.
The Database tab: collections with their document counts on the left, and the selected collection's documents on the right.
The Schema tab for the customers collection: an inferred field table listing health, id, name, and tier, each typed as string with a 100% fill-rate bar and example values such as enterprise, pro.
The Schema tab infers each field's type and fill rate from a sample of the collection's documents.

Database tools reference

Full reference for db_find, db_insert, db_update, db_upsert, db_delete, db_count, and db_list_collections.

Knowledge base

Semantic search and long-term memory backed by vector embeddings.

Environments

How environments are isolated and how the database is scoped per environment.

Observability

See database tool calls in run traces and monitor usage.