Database Stats

stats = client.databases.stats(database="your database id")

const stats = await client.databases.stats({
  database: "my_first_database",
});

curl -X GET 'https://api.hydradb.com/databases/stats?database=my_first_database' \
  -H "Authorization: Bearer <your_api_key>" \
  -H "API-Version: 2"

{
  "success": true,
  "data": {
    "database": "my_first_database",
    "knowledge_collection": {
      "row_count": 42318
    },
    "memory_collection": {
      "row_count": 287
    },
    "message": "Successfully retrieved tenant collection statistics"
  },
  "error": null,
  "meta": {
    "request_id": "9d13aef4-02f4-4e73-8c62-4c2601d04f9d",
    "latency_ms": 12.3
  }
}

{
  "success": true,
  "data": {
    "database": "my_first_database",
    "knowledge_collection": { "row_count": 0 },
    "memory_collection": { "row_count": 0 },
    "message": "Successfully retrieved tenant collection statistics"
  },
  "error": null,
  "meta": {
    "request_id": "9d13aef4-02f4-4e73-8c62-4c2601d04f9d",
    "latency_ms": 12.3
  }
}

{
  "success": false,
  "data": null,
  "error": {
    "code": "DATABASE_NOT_FOUND",
    "message": "Database not found"
  },
  "meta": {
    "request_id": "9d13aef4-02f4-4e73-8c62-4c2601d04f9d",
    "latency_ms": 4.8
  }
}

GET

databases

stats

stats = client.databases.stats(database="your database id")

const stats = await client.databases.stats({
  database: "my_first_database",
});

curl -X GET 'https://api.hydradb.com/databases/stats?database=my_first_database' \
  -H "Authorization: Bearer <your_api_key>" \
  -H "API-Version: 2"

{
  "success": true,
  "data": {
    "database": "my_first_database",
    "knowledge_collection": {
      "row_count": 42318
    },
    "memory_collection": {
      "row_count": 287
    },
    "message": "Successfully retrieved tenant collection statistics"
  },
  "error": null,
  "meta": {
    "request_id": "9d13aef4-02f4-4e73-8c62-4c2601d04f9d",
    "latency_ms": 12.3
  }
}

{
  "success": true,
  "data": {
    "database": "my_first_database",
    "knowledge_collection": { "row_count": 0 },
    "memory_collection": { "row_count": 0 },
    "message": "Successfully retrieved tenant collection statistics"
  },
  "error": null,
  "meta": {
    "request_id": "9d13aef4-02f4-4e73-8c62-4c2601d04f9d",
    "latency_ms": 12.3
  }
}

{
  "success": false,
  "data": null,
  "error": {
    "code": "DATABASE_NOT_FOUND",
    "message": "Database not found"
  },
  "meta": {
    "request_id": "9d13aef4-02f4-4e73-8c62-4c2601d04f9d",
    "latency_ms": 4.8
  }
}

Get detailed metrics including storage growth and object counts. The response splits stats into two database-wide collections: data.knowledge_collection (Knowledge) and data.memory_collection (User memories), each with its own row count. Counts aggregate across all collections in the database.

stats = client.databases.stats(database="your database id")

const stats = await client.databases.stats({
  database: "my_first_database",
});

curl -X GET 'https://api.hydradb.com/databases/stats?database=my_first_database' \
  -H "Authorization: Bearer <your_api_key>" \
  -H "API-Version: 2"

{
  "success": true,
  "data": {
    "database": "my_first_database",
    "knowledge_collection": {
      "row_count": 42318
    },
    "memory_collection": {
      "row_count": 287
    },
    "message": "Successfully retrieved tenant collection statistics"
  },
  "error": null,
  "meta": {
    "request_id": "9d13aef4-02f4-4e73-8c62-4c2601d04f9d",
    "latency_ms": 12.3
  }
}

{
  "success": true,
  "data": {
    "database": "my_first_database",
    "knowledge_collection": { "row_count": 0 },
    "memory_collection": { "row_count": 0 },
    "message": "Successfully retrieved tenant collection statistics"
  },
  "error": null,
  "meta": {
    "request_id": "9d13aef4-02f4-4e73-8c62-4c2601d04f9d",
    "latency_ms": 12.3
  }
}

{
  "success": false,
  "data": null,
  "error": {
    "code": "DATABASE_NOT_FOUND",
    "message": "Database not found"
  },
  "meta": {
    "request_id": "9d13aef4-02f4-4e73-8c62-4c2601d04f9d",
    "latency_ms": 4.8
  }
}

Behavior notes

row_count is chunks, not sources. One ingested document typically becomes many chunks (e.g., a 30-page PDF can produce 100+ rows). To count distinct sources, use List Documents with page_size=1 and read total.

Both collections always exist: Even if you’ve only ingested knowledge (or only memories), both collections are provisioned. Empty collections report row_count: 0.
Stats are eventually consistent: Immediately after ingestion or deletion, counts may lag until background processing completes. Check Ingestion Status for recently ingested IDs before treating counts as final.

Related Resources

List sources/memories: List Documents
List collections: List Collections
Check provisioning: Database Status
Read more: Concepts → Multi-Tenant Support

Authorizations

Authorization

string

header

required

API key sent as a Bearer token: "Bearer prefix.secret"

Query Parameters

database

string

required

Database identifier

Example:

"acme_corp"

Response

data

object

Show child attributes

Example:

{
  "database": "acme_corp",
  "knowledge_collection": { "dimensions": 1536, "row_count": 1280 },
  "memory_collection": { "dimensions": 1536, "row_count": 1280 },
  "message": "Success",
  "tenant_id": "tenant_1234"
}

error

object

Error message, empty string on success.

Show child attributes

Example:

{
  "code": "DATABASE_NOT_FOUND",
  "message": "Database not found"
}

API Documentation

Databases

Context

Query

Connectors

Miscellaneous

Behavior notes

Authorizations

Query Parameters

Response

​Behavior notes

Authorizations

Query Parameters

Response

Behavior notes