How many bitmaps does it take to beat a gorilla?

The text discusses the Gorilla algorithm, initially developed by Facebook for time series caching and storage, highlighting its simplicity and effectiveness in handling monotonically increasing timestamps and float-only, append-only data. While Gorilla has become a standard, it presents challenges in multi-tenant deployments, particularly with out-of-order data and integer support. The author describes an alternative approach that introduces two buffers (compressed and uncompressed) to manage out-of-order data and employs a bitmap for time storage, which improves compression efficiency over Gorilla's delta-of-delta method. This new method, compatible with both integers and floats, trades some CPU efficiency for better memory and storage management, achieving a significant reduction in storage size while being slightly less memory efficient. The approach is tailored to handle both floats and integers, addressing shortcomings in Gorilla's handling of data types and order, ultimately providing a net win in storage efficiency despite increased CPU usage.

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