Explore documentation
  1. Welcome to Warehouse 👋
  2. Ingesting data
    1. Ingesting events
    2. S3 vs NVMe hosted data
    3. Host events in your S3 bucket
  3. Querying data
    1. Querying events & time series
    2. Writing ClickHouse SQL queries
    3. Query speeds
    4. Ad-hoc SQL API
    5. Generate client-facing APIs
    6. Visualizing data
  4. Vector embeddings
    1. Introduction to embeddings
    2. Using built-in embeddings
    3. Bringing your own embeddings
    4. Data structures and indices
  5. Use cases
    1. Retrieval Augmented Generation
  6. Management
    1. Controlling costs

Bringing your own embeddings

You can use any third party API to generate embeddings for your events prior to sending them to Better Stack data warehouse.

Better Stack's built-in model embeddinggemma:300 should cover most use cases but if you want to use an external provider, we recommend OpenAI's embedding models for the best price/performance ratio.

Simply send us the embedding along side the original text in a dedicated attribute as an array of floats.

Storing embeddings as time series

Go to Sources -> Your source -> Time series on NVMe SSDs and click + Time series. Use JSON dot notation to write the name of the target column from the previous step and chose BFloat16 and choose your Vector index.

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Using built-in embeddings

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Vector embedding data structures and indices