It's similar in some ways except Loki went all out in abandoning indexing of the log lines themselves, a quote from the homepage:

> It does not index the contents of the logs, but rather a set of labels for each log stream.

This system is different because not only does it index the contents of your log messages it accelerates regex queries which are great for structured messages produced by machines.

Similar to Loki though it does index data by "labels", though not quite in the same way. Instead every field of a log is treated the same (except for time, it's special). Nested structures are flattened by path, i.e '{"message: "a", "structure": {"nest1": "b"}' is flattened to "message" and "structure.nest1". Under the hood it also stores column per type so if you later send a number at the same field you previously sent text it doesn't coerce like Elasticsearch. Instead depending on your query it will either search "structure.nest1"(text) or "structure.nest1"(number), i.e if you use a regex it will infer you are searching the textual version, if you attempt a range query it will infer number as the type.

Loki is definitely an interesting system and looks like it could handle great ingest volume but I don't think it could match my targets for sub-second queries on ~10TB of logs.