I love plain old Redis, but I'm not thrilled with the extension modules from Redis Labs.<p>I experimented with RediSearch using 20 GB of Reddit posts and I was very underwhelmed.<p>First, 20 GB of raw data explodes into 75 GB once it's in RediSearch with zero fault tolerance. While I'd expect some expansion with inverted indexes and word frequencies by document, a 3.75 multiple seems high.<p>And since this is Redis, it's all in RAM, including indexes and raw documents, all uncompressed. That's not cheap. Add replicas for fault tolerance and the RAM needed for a decent sized cluster could be 10x the size of the raw data.<p>Then the tooling and documentation is very limited. Redis Labs provides a Python client, but it doesn't support basic features like returning the score with each document, even though RediSearch provides this capability if you query it directly.<p>Finally, I found stability issues with Redis when the RediSearch module is installed. Using the Python client provided by RedisLabs, certain queries would predictably crash every node in the cluster.<p>Redis itself is rock solid, but Redis with the RediSearch module feels fragile.<p>Overall, interesting concept but not ready for production use by any means.