Readme
Source
- Canonical Cookbook page: https://developers.openai.com/cookbook/examples/vector_databases/cassandra_astradb/readme
- OpenAI Cookbook source: https://github.com/openai/openai-cookbook/blob/main/examples/vector_databases/cassandra_astradb/README.md
- Raw source: https://raw.githubusercontent.com/openai/openai-cookbook/main/examples/vector_databases/cassandra_astradb/README.md
- Source path:
examples/vector_databases/cassandra_astradb/README.md - Source kind:
examples - Source format:
.md - License basis: OpenAI Cookbook repository MIT license.
- Content hash:
c195e22bf41b95cca2231b74c16673b9aadbeb28192a1aa5b7792d2feb78b011
Classification
- Primary category: RAG / retrieval / vector databases
- Wiki collection: 2026-05-15-openai-cookbook
- Taxonomy page: openai-cookbook-taxonomy
- Topic hub: openai-cookbook
Summary
RAG with Astra DB and Cassandra The demos in this directory show how to use the Vector Search capabilities available today in DataStax Astra DB , a serverless Database-as-a-Service built on Apache Cassandra®. These example notebooks demonstrate implementation of the same GenAI standard RAG workload with different libraries and APIs. To use Astra DB with its…
What This Teaches
- How to connect OpenAI models with retrieval, embeddings, or external knowledge stores.
Implementation Use Cases
- Use as a concrete implementation reference when building OpenAI API systems in this category.
- Compare against current official API docs before copying model names, SDK calls, or parameters into production code.
- Preserve this page as a mirrored source; prefer synthesis pages for personal recommendations or project-specific decisions.
Mirrored Content
RAG with Astra DB and Cassandra
The demos in this directory show how to use the Vector Search capabilities available today in DataStax Astra DB, a serverless Database-as-a-Service built on Apache Cassandra®.
These example notebooks demonstrate implementation of the same GenAI standard RAG workload with different libraries and APIs.
To use Astra DB
with its HTTP API interface, head to the “AstraPy” notebook (astrapy
is the Python client to interact with the database).
If you prefer CQL access to the database (either with Astra DB or a Cassandra cluster supporting vector search), check the “CQL” or “CassIO” notebooks — they differ in the level of abstraction you get to work at.
If you want to know more about Astra DB and its Vector Search capabilities, head over to datastax.com.
Example notebooks
The following examples show how easily OpenAI and DataStax Astra DB can work together to power vector-based AI applications. You can run them either with your local Jupyter engine or as Colab notebooks:
| Use case | Target database | Framework | Notebook | Google Colab |
|---|---|---|---|---|
| Search/generate quotes | Astra DB | AstraPy | Notebook |  |
| Search/generate quotes | Cassandra / Astra DB through CQL | CassIO | Notebook | |
| Search/generate quotes | Cassandra / Astra DB through CQL | Plain Cassandra language | Notebook | |
Vector similarity, visual representation
