As said on http://jemalloc.net/:
jemalloc is a general purpose malloc(3) implementation that emphasizes fragmentation avoidance and scalable concurrency support.
Some Sphinx and Manticore Search users prefer jemalloc over malloc and say it allows to save some RAM. I’ve tested how jemalloc affects resource consumption and response time for 2 weeks on 3 Manticore clusters (se03/03-2, se04/04-2, se05/05-2) each of which:
[UPDATE] Fresher benchmark is here.
Recently long-awaited Sphinx 3 was released and updated in 3.0.2 . It has got documents storage capabilities, A-indexes, snippets pre-indexing and unfortunately is not open source any more (at least now, in March 2018).
Those all are very nice features, but are you interested in how much they affected the performance of Sphinx 3 and how much that differs from Manticore’s performance? We too!
Between the Manticore query and the final result to the user there can be additional processing. As in most cases, the interest is to sort by a relevance score, it’s important to not lose this sorting.
Plain indexes text data is immutable, this means to refresh the data we need to issue a full reindexing. In many cases, the reindexing can take a long time. For that, a main+delta schema is used. The concept assume a big index that holds a snapshot of the data at a given time and a Read more about Manticore Search kill-list feature[…]