Vector Database

Find Vector Database Configuration in Helm Chart Values

Display Helm Chart Values

helm show values dify/dify

Vector Database Configuration Overview

In the Helm chart values, vector databases are configured through the vectorDB field. Dify supports two deployment modes:

Mode	When to use	Toggle field
External connection (recommended for production)	Connect to a self-managed or cloud-hosted vector database	`vectorDB.useExternal: true`
Built-in deployment (testing only)	Helm chart provisions an in-cluster vector database	`vectorDB.useExternal: false`

The 3.9.x chart defaults to useExternal: true + externalType: "qdrant". Out of the box it is in “connect to external Qdrant” mode — you must replace externalQdrant.endpoint / apiKey with your actual cluster values, otherwise the api / worker Pods will fail to start because they cannot reach the vector database.

1. Using a Built-in Vector Database

⚠️ Use with caution in production: Built-in options are only suitable for local trials and feature validation. They do not provide high availability, backups, or capacity scaling. Use the external connection method in section 2 for production environments.

The Helm chart provides two in-cluster vector databases that can be enabled.

Built-in Qdrant

Set vectorDB.useExternal to false and enable qdrant.enabled to use this option.

vectorDB:
  useExternal: false

qdrant:
  enabled: true
  replicaCount: 3
  image:
    repository: langgenius/qdrant
    pullPolicy: IfNotPresent
    tag: "v1.7.3"
  apiKey: "dify123456"
  persistence:
    accessModes: ["ReadWriteOnce"]
    size: 10Gi
  resources: {}
    # limits:
    #   cpu: 100m
    #   memory: 128Mi
    # requests:
    #   cpu: 100m
    #   memory: 128Mi

Field	Description	Default
`qdrant.enabled`	Whether to enable built-in Qdrant	`false`
`qdrant.replicaCount`	Number of replicas	`3`
`qdrant.image.repository`	Image repository	`langgenius/qdrant`
`qdrant.image.tag`	Image version	`v1.7.3`
`qdrant.apiKey`	Qdrant API Key	`dify123456`
`qdrant.persistence.accessModes`	Persistent storage access modes	`["ReadWriteOnce"]`
`qdrant.persistence.size`	Persistent storage size	`10Gi`
`qdrant.resources`	Resource limits (CPU / memory)	`{}`

Built-in Weaviate

weaviate only exposes the enabled toggle in the parent chart’s values.yaml, but it is actually a nested subchart (located at dify/charts/weaviate/ in the chart tarball, with about 947 lines of values). All fields of this subchart can be overridden in your values.yaml as weaviate.<field> — the common ones are listed below.

weaviate:
  enabled: true
  image:
    repo: semitechnologies/weaviate
    tag: "1.18.0"
  replicas: 1
  storage:
    size: 32Gi
    storageClassName: ""
  service:
    type: LoadBalancer  # also accepts ClusterIP / NodePort
  resources: {}
  authentication: {}
  authorization: {}
  modules: {}

Field	Description	Subchart default
`weaviate.enabled`	Whether to enable built-in Weaviate	`false`
`weaviate.image.tag`	Weaviate image version (recommend pinning in your own values)	`1.18.0`
`weaviate.replicas`	Number of replicas (scaling is restricted after data is imported, see subchart notes)	`1`
`weaviate.storage.size`	PVC capacity	`32Gi`
`weaviate.storage.storageClassName`	Storage class	`""` (default SC)
`weaviate.service.type`	Service type	`LoadBalancer`
`weaviate.resources`	Resource limits	`{}`
`weaviate.{startup,liveness,readiness}Probe`	Probe configuration	See subchart
`weaviate.authentication` / `authorization`	Authentication configuration	See subchart
`weaviate.modules`	Extension modules for text/image vectorization (contextionary, img2vec, transformers, etc.)	See subchart

💡 To get the complete field list, download the chart and inspect dify/charts/weaviate/values.yaml:
helm pull dify/dify --untar
less dify/charts/weaviate/values.yaml
If you are connecting to an existing external Weaviate cluster, use the externalWeaviate configuration in Weaviate below instead.

2. Using an External Vector Database

To connect to an external vector database, configuration takes two steps: Step 1: Set vectorDB.useExternal to true and specify externalType. The 3.9.x chart already defaults to this state (externalType: "qdrant"), so you only need to override externalType when switching to a different type.

vectorDB:
  useExternal: true
  externalType: "<type>"

Step 2: Based on the chosen type, fill in the corresponding externalXxx configuration block. The values.yaml already provides a default skeleton for each type — you only need to override the fields of your target type; there is no need to delete the other type blocks. See Section 4 Appendix for field examples of each type.

Supported Types

Types officially supported by Dify Enterprise

Dify Enterprise officially supports the following vector databases. You also receive technical support for the database connection (see Section 3).

qdrant (recommended)
weaviate (optional)
elasticsearch (optional)

Community-supported types

Dify Community offers support for the following vector databases. If you want to use these, Dify Enterprise also supports them, but with limited technical support (see Section 3).

milvus
relyt
pgvector
pgvecto-rs
tencent
analyticdb
opensearch
lindorm

3. Enterprise Edition Technical Support Scope

When Dify Enterprise is deployed on a cloud (e.g., AWS) and connects to an external vector database, the entire chain typically involves three parties: Dify, the vector database vendor, and the cloud provider. The Dify support team will first identify which layer the issue belongs to.

Shared Responsibility Model

Scope	Responsible party
Dify-side configuration: database config, connection config, knowledge base config	Dify
Dify database operation logic: connection, Schema/Collection initialization, write, retrieval	Dify
Semantics and value constraints of `vectorDB.*` / `externalXxx` fields in the Helm chart	Dify
Vector database itself: cluster availability, sharding/replicas, version upgrades, performance tuning, backup/restore	Vector database vendor / managed service provider
Infrastructure: VPC, subnets, security groups, IAM/IRSA, DNS, load balancing, cross-AZ network	Cloud provider
Capacity planning and config values: node specs, storage capacity, QPS and concurrency estimation	User (Dify provides recommendations only)

What Dify Does Not Directly Support

The following issues may surface in Dify error messages, but the root cause is not on the Dify side and must be handled by the database vendor, cloud provider, or the user:

Vector database operations: restart, upgrade, scaling, backup/restore
Index parameter tuning on the database side
Network and permission-layer failures: VPC peering, security group rules, IAM/IRSA, TLS certificates
Capacity planning and load testing: node specs, storage capacity, QPS limit estimation (Dify only provides Dify-side recommendations)
Regressions caused by database version bugs or vendor behavior changes (Dify will follow up, but root-cause fixes are on the vendor side)

Differences Between the Two Support Tiers

Support tier	Included products	Capabilities provided by Dify
Officially supported	qdrant, weaviate, elasticsearch	Dify-side connector maintenance, version compatibility testing, Helm config troubleshooting
Community supported	milvus, relyt, pgvector, pgvecto-rs, tencent, analyticdb, opensearch, lindorm	Connector availability, configuration documentation, best-effort troubleshooting; deeper issues should be escalated to the vendor or community first

For more details about the vector databases supported by your Dify Enterprise version, see values.yaml at: https://helm-watchdog.dify.ai/ . Actual technical support coverage will be evaluated by the Dify Enterprise support team based on your specific issue.

4. Appendix: Configuration Examples for Each Vector Database

Qdrant

externalType: "qdrant"

  externalQdrant:
    endpoint: "http://your-qdrant-cluster-url.qdrant.tech/"
    apiKey: "#REPLACE_ME#"

Field	Description	Example
`endpoint`	Qdrant cluster URL	`http://your-qdrant-cluster-url.qdrant.tech/`
`apiKey`	Qdrant API Key	-

Weaviate

externalType: "weaviate"

  externalWeaviate:
    endpoint: "http://weaviate:8080"
    apiKey: "#REPLACE_ME#"

Field	Description	Example
`endpoint`	Weaviate service address	`http://weaviate:8080`
`apiKey`	Weaviate API Key	-

Elasticsearch

externalType: "elasticsearch"

  externalElasticsearch:
    host: "127.0.0.1"
    port: 9200
    username: "elastic"
    password: "#REPLACE_ME#"

Field	Description	Example
`host`	Elasticsearch host	`127.0.0.1`
`port`	Port	`9200`
`username`	Username	`elastic`
`password`	Password	-

Milvus

externalType: "milvus"

  externalMilvus:
    uri: "http://127.0.0.1:19530"
    token: ""
    user: ""
    password: ""
    database: "default"

Field	Description	Example
`uri`	Milvus server connection URI	`http://127.0.0.1:19530`
`token`	Auth token (optional)	-
`user`	Username (optional)	-
`password`	Password (optional)	-
`database`	Database name	`default`

Relyt (pgvectors)

externalType: "relyt"

  externalRelyt:
    host: "your-relyt.domain"
    port: 5431
    user: "postgres"
    password: "#REPLACE_ME#"
    database: "pgvectors"

Field	Description	Example
`host`	Relyt host	`your-relyt.domain`
`port`	Port	`5431`
`user`	Username	`postgres`
`password`	Password	-
`database`	Database name	`pgvectors`

PgVector

externalType: "pgvector"

  externalPgvector:
    host: "your-pgvector.domain"
    port: 5432
    user: "postgres"
    password: "#REPLACE_ME#"
    database: "dify"
    minConnection: 1
    maxConnection: 5
    pgBigm: false

Field	Description	Example
`host`	PgVector host	`your-pgvector.domain`
`port`	Port	`5432`
`user`	Username	`postgres`
`password`	Password	-
`database`	Database name	`dify`
`minConnection`	Minimum connection pool size	`1`
`maxConnection`	Maximum connection pool size	`5`
`pgBigm`	Enable the pg_bigm extension for full-text search	`false`

PgVecto-RS

externalType: "pgvecto-rs"

  externalPgVectoRS:
    host: "your-pgvectors.domain"
    port: 5432
    user: "postgres"
    password: "#REPLACE_ME#"
    database: "pgvectors"

Field	Description	Example
`host`	PgVecto-RS host	`your-pgvectors.domain`
`port`	Port	`5432`
`user`	Username	`postgres`
`password`	Password	-
`database`	Database name	`pgvectors`

Tencent VectorDB

externalType: "tencent"

  externalTencentVectorDB:
    host: "your-tencent-vector-db.domain"
    apiKey: "#REPLACE_ME#"
    timeout: 30
    username: "tencent"
    password: "#REPLACE_ME#"
    shard: 1
    replicas: 2
    database: "tencent"

Field	Description	Example
`host`	Tencent VectorDB host	`your-tencent-vector-db.domain`
`apiKey`	API Key	-
`timeout`	Connection timeout (seconds)	`30`
`username`	Username	`tencent`
`password`	Password	-
`shard`	Number of shards	`1`
`replicas`	Number of replicas	`2`
`database`	Database name	`tencent`

OpenSearch

externalType: "opensearch"

  externalOpenSearch:
    host: "your-opensearch.domain"
    port: 9200
    user: ""
    password: "#REPLACE_ME#"
    useTLS: false

Field	Description	Example
`host`	OpenSearch host	`your-opensearch.domain`
`port`	Port	`9200`
`user`	Username (optional)	-
`password`	Password	-
`useTLS`	Whether to enable TLS	`false`

AnalyticDB

externalType: "analyticdb"

  externalAnalyticDB:
    keyID: "#REPLACE_ME#"
    keySecret: "#REPLACE_ME#"
    regionID: "#REPLACE_ME#"
    instanceID: "#REPLACE_ME#"
    account: "#REPLACE_ME#"
    password: "#REPLACE_ME#"
    host: "#REPLACE_ME#"
    port: 5432
    namespace: ""
    namespacePassword: ""
    minConnection: 1
    maxConnection: 5

Field	Description	Example
`keyID`	Alibaba Cloud AccessKey ID	-
`keySecret`	Alibaba Cloud AccessKey Secret	-
`regionID`	Region ID	-
`instanceID`	Instance ID	-
`account`	Account	-
`password`	Password	-
`host`	Host	-
`port`	Port	`5432`
`namespace`	Namespace (optional)	-
`namespacePassword`	Namespace password (optional)	-
`minConnection`	Minimum connections	`1`
`maxConnection`	Maximum connections	`5`

Lindorm

externalType: "lindorm"

  externalLindorm:
    url: "http://localhost:30070"
    username: "admin"
    password: "admin"
    indexType: "hnsw"
    distanceType: "l2"
    usingUgc: true
    queryTimeout: 2.0

Field	Description	Example
`url`	Lindorm search engine URL	`http://localhost:30070`
`username`	Username	`admin`
`password`	Password	`admin`
`indexType`	Index type	`hnsw`
`distanceType`	Distance metric	`l2`
`usingUgc`	Whether to use UGC mode	`true`
`queryTimeout`	Query timeout (seconds)	`2.0`

Deployment

Advanced Configuration

Cloud Infrastructure

Find Vector Database Configuration in Helm Chart Values

Display Helm Chart Values

Vector Database Configuration Overview

1. Using a Built-in Vector Database

Built-in Qdrant

Built-in Weaviate

2. Using an External Vector Database

Supported Types

Types officially supported by Dify Enterprise

Community-supported types

3. Enterprise Edition Technical Support Scope

Shared Responsibility Model

What Dify Does Not Directly Support

Differences Between the Two Support Tiers

4. Appendix: Configuration Examples for Each Vector Database

Qdrant

Weaviate

Elasticsearch

Milvus

Relyt (pgvectors)

PgVector

PgVecto-RS

Tencent VectorDB

OpenSearch

AnalyticDB

Lindorm

​Find Vector Database Configuration in Helm Chart Values

​Display Helm Chart Values

​Vector Database Configuration Overview

​1. Using a Built-in Vector Database

​Built-in Qdrant

​Built-in Weaviate

​2. Using an External Vector Database

​Supported Types

​Types officially supported by Dify Enterprise

​Community-supported types

​3. Enterprise Edition Technical Support Scope

​Shared Responsibility Model

​What Dify Does Not Directly Support

​Differences Between the Two Support Tiers

​4. Appendix: Configuration Examples for Each Vector Database

​Qdrant

​Weaviate

​Elasticsearch

​Milvus

​Relyt (pgvectors)

​PgVector

​PgVecto-RS

​Tencent VectorDB

​OpenSearch

​AnalyticDB

​Lindorm

Find Vector Database Configuration in Helm Chart Values

Display Helm Chart Values

Vector Database Configuration Overview

1. Using a Built-in Vector Database

Built-in Qdrant

Built-in Weaviate

2. Using an External Vector Database

Supported Types

Types officially supported by Dify Enterprise

Community-supported types

3. Enterprise Edition Technical Support Scope

Shared Responsibility Model

What Dify Does Not Directly Support

Differences Between the Two Support Tiers

4. Appendix: Configuration Examples for Each Vector Database

Qdrant

Weaviate

Elasticsearch

Milvus

Relyt (pgvectors)

PgVector

PgVecto-RS

Tencent VectorDB

OpenSearch

AnalyticDB

Lindorm