Skip to main content
Kinetica is a real-time database purpose built for enabling analytics and generative AI on time-series & spatial data.

​
Chat Model

The Kinetica LLM wrapper uses the Kinetica SqlAssist LLM to transform natural language into SQL to simplify the process of data retrieval. See Kinetica Language To SQL Chat Model for usage. 
from langchain_community.chat_models.kinetica import ChatKinetica

​
Vector Store

The Kinetca vectorstore wrapper leverages Kinetica’s native support for vector similarity search. See Kinetica Vectorstore API for usage. 
from langchain_community.vectorstores import Kinetica

​
Document Loader

The Kinetica Document loader can be used to load LangChain Documents from the Kinetica database. See Kinetica Document Loader for usage 
from langchain_community.document_loaders.kinetica_loader import KineticaLoader

​
Retriever

The Kinetica Retriever can return documents given an unstructured query. See Kinetica VectorStore based Retriever for usage
Edit the source of this page on GitHub.
Connect these docs programmatically to Claude, VSCode, and more via MCP for real-time answers.
⌘I