columnar VS manticoresearch

If you use our Manticore Columnar Library, which is highly recommended, secondary indexes are now ON by default. After their introduction in the previous major release they were significantly improved and we now believe having them enabled by default makes sense for most users. There’s also a new command ALTER TABLE table_name REBUILD SECONDARY to rebuild your secondary indexes, e.g. when you upgrade from a previous version.

Speaking about the other differences, the most important is probably the same as if we compare Manticore with Typesense: MeiliSearch isn't supposed to be used in a big data scenario. They say that the max index size is 100 GB and that 8.6MB dataset when indexed by MeiliSearch takes 300+ MB of RAM . Manticore Search for example is used by Craigslist that would probably go broke if they had to spend 300MB of RAM for each 9MB of data. And we made it even better when we developed the columnar storage.

In Manticore 5 we addded Fast fetching for attributes backed by Manticore Columnar Library: queries like select * from are now much faster than previously, especially if there are many fields in the schema.

We already have a beta version ready and here are some first results comparing Manticore Columnar Library + Manticore Search vs Elasticsearch on the same dataset as above (excluding full-text queries, i.e. mostly grouping queries):

Note, you need to do it in the root folder of a clone from https://github.com/manticoresoftware/manticoresearch

Interesting, how does it compare to Mantico search?

Where Manticore Search? https://manticoresearch.com/

It's not open source since 2017. The open source fork is https://github.com/manticoresoftware/manticoresearch

I haven't looked at the code, but I've seen https://github.com/manticoresoftware/manticoresearch popping up in a few places. Might be worth looking at. It would be great to have a faster drop-in replacement for Elasticsearch that's not written in Java. They blogged about it here: https://manticoresearch.com/blog/manticore-alternative-to-elasticsearch/

I don't see anywhere where they claim that it's faster simply because it's written in C++. They do mention that they make use of C++ to add low level optimizations that make queries faster and the memory imprint smaller, but any claims about performance in the readme are linked to benchmarks to back up their claims

https://github.com/manticoresoftware/manticoresearch/

https://db-benchmarks.com/test-taxi/#manticore-search-vs-ela...

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