Data Store

gllm-datastore | Related tutorials: Index Your Data with Vector Data Store | API Reference

What is a Datastore?

A datastore is an object that provides the capability to save, retrieve, and manage data in specific types of storage systems. In the GL SDK, datastores serve as abstractions that handle the complexity of interacting with different database technologies while providing a consistent interface for data operations.

What You Can Do with a Datastore

GL SDK provides several datastore types, each designed for specific use cases and data storage requirements:

1. Vector Data Store - For storing and searching vector embeddings

2. SQL Data Store - For relational database operations

3. Graph Data Store - For storing and querying graph-structured data

GL SDK makes it easy to perform common data operations regardless of which datastore type you choose. One of the most powerful features of the GL SDK is its unified approach to data storage. All datastores support storing data in a structured format using the Chunk schema.

Think of chunks as standardized containers for your data - they provide a consistent way to represent information across different storage types, making it easy to switch between datastores or combine them in your application.

from gllm_core.schema import Chunk

# Create chunks with structured content
chunks = [
    Chunk(content="AI is the future of technology."),
    Chunk(content="Machine learning enables pattern recognition."),
    Chunk(content="Deep learning powers modern AI applications.")
]