AI Briefingmurrdb/murr - Sub-millisecond cache for ML/AI workloads
Key point
A high-performance RocksDB-based tiered cache solution that can replace Redis for optimizing AI inference workloads.
Details
An NVMe/S3 cache built on RocksDB designed for AI inference workloads, optimized for low-latency zero-copy reads and writes in a batch-processing style.
As a data serving layer, it supports Parquet input and Arrow-Flight output, with a tiered storage structure that keeps hot data in memory and cold data on disk. Its stateless design preserves all state in S3, enabling fast recovery even in the event of node failure.
Key Features and Benefits:
- Zero-copy wire protocol:
np.ndarray,pd.DataFrame, andpt.Tensorcan be constructed instantly from API responses without conversion. - Efficient data handling: 1GB-scale Parquet/Arrow files can be fed directly into the Ingestion API as-is, and with Sparse columns support, columns without data take up no space.
- Cost and performance: It shows roughly 12x faster performance than Redis on HSET and 3x lower RAM usage, and can operate at roughly 10x lower cost than DynamoDB.
Since this tool is not a general-purpose DB, it is recommended to use Postgres for OLTP, Clickhouse for analytics, and Redis for general-purpose caching.
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