SOSD VS la_vector

Compare SOSD vs la_vector and see what are their differences.

SOSD

A Benchmark for Learned Indexes (by learnedsystems)

la_vector

🔶 Compressed bitvector/container supporting efficient random access and rank queries (by gvinciguerra)
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SOSD la_vector
2 1
260 35
3.1% -
0.0 0.0
about 2 years ago over 1 year ago
C++ C++
GNU General Public License v3.0 only Apache License 2.0
The number of mentions indicates the total number of mentions that we've tracked plus the number of user suggested alternatives.
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.

SOSD

Posts with mentions or reviews of SOSD. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2021-01-25.

la_vector

Posts with mentions or reviews of la_vector. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2021-01-25.
  • PGM Indexes: Learned indexes that match B-tree performance with 83x less space
    7 projects | news.ycombinator.com | 25 Jan 2021
    Hi Jouni!

    You may find interesting these other papers of ours:

    - The ALENEX21 paper "A 'learned' approach to quicken and compress rank/select dictionaries" (http://pages.di.unipi.it/vinciguerra/publication/learned-ran..., https://github.com/gvinciguerra/la_vector), where we introduce a compressed bitvector supporting efficient rank and select queries, which is competitive with several well-established implementations of succinct data structures.

    - The ICML20 paper "Why are learned indexes so effective?" (http://pages.di.unipi.it/vinciguerra/publication/learned-ind...) where we prove that, under some general assumptions on the input data, the space of the PGM-index is actually O(n/B^2) whp (versus Θ(n/B) of classic B-trees).

What are some alternatives?

When comparing SOSD and la_vector you can also consider the following projects:

PGM-index - 🏅State-of-the-art learned data structure that enables fast lookup, predecessor, range searches and updates in arrays of billions of items using orders of magnitude less space than traditional indexes

RadixSpline - A Single-Pass Learned Index

ALEX - A library for building an in-memory, Adaptive Learned indEX