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Db-benchmark Alternatives
Similar projects and alternatives to db-benchmark
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polars
Dataframes powered by a multithreaded, vectorized query engine, written in Rust
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InfluxDB
Collect and Analyze Billions of Data Points in Real Time. Manage all types of time series data in a single, purpose-built database. Run at any scale in any environment in the cloud, on-premises, or at the edge.
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Apache Arrow
Apache Arrow is a multi-language toolbox for accelerated data interchange and in-memory processing
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databend
Modern alternative to Snowflake. Cost-effective and simple for massive-scale analytics. Cloud: https://databend.com
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Onboard AI
Learn any GitHub repo in 59 seconds. Onboard AI learns any GitHub repo in minutes and lets you chat with it to locate functionality, understand different parts, and generate new code. Use it for free at www.getonboard.dev.
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datatable
A Python package for manipulating 2-dimensional tabular data structures
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disk.frame
Fast Disk-Based Parallelized Data Manipulation Framework for Larger-than-RAM Data
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Nim
Nim is a statically typed compiled systems programming language. It combines successful concepts from mature languages like Python, Ada and Modula. Its design focuses on efficiency, expressiveness, and elegance (in that order of priority).
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explorer
Series (one-dimensional) and dataframes (two-dimensional) for fast and elegant data exploration in Elixir
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DataFrame
C++ DataFrame for statistical, Financial, and ML analysis -- in modern C++ using native types and contiguous memory storage
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Pandas
Flexible and powerful data analysis / manipulation library for Python, providing labeled data structures similar to R data.frame objects, statistical functions, and much more
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simdjson
Parsing gigabytes of JSON per second : used by Facebook/Meta Velox, WatermelonDB, Apache Doris, Milvus, StarRocks
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SaaSHub
SaaSHub - Software Alternatives and Reviews. SaaSHub helps you find the best software and product alternatives
NOTE:
The number of mentions on this list indicates mentions on common posts plus user suggested alternatives.
Hence, a higher number means a better db-benchmark alternative or higher similarity.
db-benchmark reviews and mentions
Posts with mentions or reviews of db-benchmark.
We have used some of these posts to build our list of alternatives
and similar projects. The last one was on 2023-11-06.
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DuckDB performance improvements with the latest release
I do think it was important for duckdb to put out a new version of the results as the earlier version of that benchmark [1] went dormant with a very old version of duckdb with very bad performance, especially against polars.
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Show HN: SimSIMD vs. SciPy: How AVX-512 and SVE make SIMD cleaner and ML faster
https://news.ycombinator.com/item?id=33270638 :
> Apache Ballista and Polars do Apache Arrow and SIMD.
> The Polars homepage links to the "Database-like ops benchmark" of {Polars, data.table, DataFrames.jl, ClickHouse, cuDF, spark, (py)datatable, dplyr, pandas, dask, Arrow, DuckDB, Modin,} but not yet PostgresML? https://h2oai.github.io/db-benchmark/ *
LLM -> Vector database: https://en.wikipedia.org/wiki/Vector_database
/? inurl:awesome site:github.com "vector database"
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Pandas vs. Julia – cheat sheet and comparison
I agree with your conclusion but want to add that switching from Julia may not make sense either.
According to these benchmarks: https://h2oai.github.io/db-benchmark/, DF.jl is the fastest library for some things, data.table for others, polars for others. Which is fastest depends on the query and whether it takes advantage of the features/properties of each.
For what it's worth, data.table is my favourite to use and I believe it has the nicest ergonomics of the three I spoke about.
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Any faster Python alternatives?
Same. Numba does wonders for me in most scenarios. Yesterday I've discovered pola-rs and looks like I will add it to the stack. It's API is similar to pandas. Have a look at the benchmarks of cuDF, spark, dask, pandas compared to it: Benchmarks
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Pandas v2.0 Released
If interested in benchmarks comparing different dataframe implementations, here is one:
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Python "programmers" when I show them how much faster their naive code runs when translated to C++ (this is a joke, I love python)
Bad examples. Both numpy and pandas are notoriously un-optimized packages, losing handily to pretty much all their competitors (R, Julia, kdb+, vaex, polars). See https://h2oai.github.io/db-benchmark/ for a partial comparison.
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Best alternative to Pandas 2023?
And what's your rating scale? Objectively, pandas loses in performance against everything relevant. It has a wonky syntax that requires using lambda all over the place or to retype your df name at least twice for many operations.
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Tutorial on Intro to Rust Programming
There has been an upward trend in opensource tools written in Rust with interfaces to python eg: pydantic (moved to Rust in the recent release), polars which is very fast as indicated in the H2Oai benchmarks.
- How do I work with GIGANTIC csv files (20-100 gigabytes)?
- PostgresML is 8-40x faster than Python HTTP microservices
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A note from our sponsor - InfluxDB
www.influxdata.com | 3 Dec 2023
Stats
Basic db-benchmark repo stats
89
304
0.0
5 months ago
h2oai/db-benchmark is an open source project licensed under Mozilla Public License 2.0 which is an OSI approved license.
The primary programming language of db-benchmark is R.
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