columnar
PGM-index
columnar | PGM-index | |
---|---|---|
5 | 6 | |
77 | 758 | |
- | - | |
8.3 | 6.2 | |
3 days ago | 11 days ago | |
C++ | C++ | |
Apache License 2.0 | Apache License 2.0 |
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columnar
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Manticore Search 6
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. Thereās also a new command ALTER TABLE table_name REBUILD SECONDARY to rebuild your secondary indexes, e.g. when you upgrade from a previous version.
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Manticore: a faster alternative to Elasticsearch in C++ with a 21-year history
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.
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Manticore Search 5
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.
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Manticore Search: 3 years after forking from Sphinx
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):
PGM-index
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Self-indexing RDBMS? Could AI help?
PGM Index
- Piecewise Geometric Model Index
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Manticore Search 5
Manticore Columnar Library uses Piecewise Geometric Model index, which exploits a learned mapping between the indexed keys and their location in memory. The succinctness of this mapping, coupled with a peculiar recursive construction algorithm, makes the PGM-index a data structure that dominates traditional indexes by orders of magnitude in space while still offering the best query and update time performance.
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PGM Indexes: Learned indexes that match B-tree performance with 83x less space
Yep, I'm working on a multidimensional version that I hope to upload to the main repo (https://github.com/gvinciguerra/PGM-index) in a few weeks.
What are some alternatives?
manticoresearch - Easy to use open source fast database for search | Good alternative to Elasticsearch now | Drop-in replacement for E in the ELK soon
ALEX - A library for building an in-memory, Adaptive Learned indEX
manticoresearch-php - Official PHP client for Manticore Search
beir - A Heterogeneous Benchmark for Information Retrieval. Easy to use, evaluate your models across 15+ diverse IR datasets.
robin-map - C++ implementation of a fast hash map and hash set using robin hood hashing
kantan.csv - CSV handling library for Scala
sdsl-lite - Succinct Data Structure Library 3.0
sv - Comma (and other) separated values
SOSD - A Benchmark for Learned Indexes
icu - The home of the ICU project source code.
RadixSpline - A Single-Pass Learned Index