Best Vector Databases for ChatGPT

Compare the Top Vector Databases that integrate with ChatGPT as of October 2025

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This a list of Vector Databases that integrate with ChatGPT. Use the filters on the left to add additional filters for products that have integrations with ChatGPT. View the products that work with ChatGPT in the table below.

What are Vector Databases for ChatGPT?

Vector databases are a type of database that use vector-based data structures, rather than the traditional relational models, to store information. They are used in artificial intelligence (AI) applications such as machine learning, natural language processing and image recognition. Vector databases support fast and efficient data storage and retrieval processes, making them an ideal choice for AI use cases. They also enable the integration of structured and unstructured datasets into a single system, offering enhanced scalability for complex projects. Compare and read user reviews of the best Vector Databases for ChatGPT currently available using the table below. This list is updated regularly.

1

Zilliz Cloud

Zilliz

Zilliz Cloud is a fully managed vector database based on the popular open-source Milvus. Zilliz Cloud helps to unlock high-performance similarity searches with no previous experience or extra effort needed for infrastructure management. It is ultra-fast and enables 10x faster vector retrieval, a feat unparalleled by any other vector database management system. Zilliz includes support for multiple vector search indexes, built-in filtering, and complete data encryption in transit, a requirement for enterprise-grade applications. Zilliz is a cost-effective way to build similarity search, recommender systems, and anomaly detection into applications to keep that competitive edge.

Starting Price: $0

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2

Deep Lake

activeloop

Generative AI may be new, but we've been building for this day for the past 5 years. Deep Lake thus combines the power of both data lakes and vector databases to build and fine-tune enterprise-grade, LLM-based solutions, and iteratively improve them over time. Vector search does not resolve retrieval. To solve it, you need a serverless query for multi-modal data, including embeddings or metadata. Filter, search, & more from the cloud or your laptop. Visualize and understand your data, as well as the embeddings. Track & compare versions over time to improve your data & your model. Competitive businesses are not built on OpenAI APIs. Fine-tune your LLMs on your data. Efficiently stream data from remote storage to the GPUs as models are trained. Deep Lake datasets are visualized right in your browser or Jupyter Notebook. Instantly retrieve different versions of your data, materialize new datasets via queries on the fly, and stream them to PyTorch or TensorFlow.

Starting Price: $995 per month

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3

Pinecone

Pinecone

The AI Knowledge Platform. The Pinecone Database, Inference, and Assistant make building high-performance vector search apps easy. Developer-friendly, fully managed, and easily scalable without infrastructure hassles. Once you have vector embeddings, manage and search through them in Pinecone to power semantic search, recommenders, and other applications that rely on relevant information retrieval. Ultra-low query latency, even with billions of items. Give users a great experience. Live index updates when you add, edit, or delete data. Your data is ready right away. Combine vector search with metadata filters for more relevant and faster results. Launch, use, and scale your vector search service with our easy API, without worrying about infrastructure or algorithms. We'll keep it running smoothly and securely.

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4

ConfidentialMind

ConfidentialMind

We've done the work of bundling and pre-configuring all the components you need for building solutions and integrating LLMs directly into your business processes. With ConfidentialMind you can jump right into action. Deploys an endpoint for the most powerful open source LLMs like Llama-2, turning it into an internal LLM API. Imagine ChatGPT in your very own cloud. This is the most secure solution possible. Connects the rest of the stack with the APIs of the largest hosted LLM providers like Azure OpenAI, AWS Bedrock, or IBM. ConfidentialMind deploys a playground UI based on Streamlit with a selection of LLM-powered productivity tools for your company such as writing assistants and document analysts. Includes a vector database, critical components for the most common LLM applications for shifting through massive knowledge bases with thousands of documents efficiently. Allows you to control the access to the solutions your team builds and what data the LLMs have access to.

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