---
title: Overview
---

Mem0 includes built-in support for various popular databases. Memory can utilize the database provided by the user, ensuring efficient use for specific needs.

## Supported Vector Databases

See the list of supported vector databases below.

<CardGroup cols={3}>
  <Card title="Qdrant" href="/components/vectordbs/dbs/qdrant"></Card>
  <Card title="Chroma" href="/components/vectordbs/dbs/chroma"></Card>
  <Card title="Pgvector" href="/components/vectordbs/dbs/pgvector"></Card>
  <Card title="Milvus" href="/components/vectordbs/dbs/milvus"></Card>
  <Card title="Azure AI Search" href="/components/vectordbs/dbs/azure_ai_search"></Card>
  <Card title="Redis" href="/components/vectordbs/dbs/redis"></Card>
  <Card title="Elasticsearch" href="/components/vectordbs/dbs/elasticsearch"></Card>
</CardGroup>

## Usage

To utilize a vector database, you must provide a configuration to customize its usage. If no configuration is supplied, a default configuration will be applied, and `Qdrant` will be used as the vector database.

For a comprehensive list of available parameters for vector database configuration, please refer to [Config](./config).

## Common issues

### Using model with different dimensions

If you are using customized model, which is having different dimensions other than 1536
for example 768, you may encounter below error:

`ValueError: shapes (0,1536) and (768,) not aligned: 1536 (dim 1) != 768 (dim 0)`

you could add `"embedding_model_dims": 768,` to the config of the vector_store to overcome this issue.