arctic VS bcolz

Compare arctic vs bcolz and see what are their differences.

arctic

High performance datastore for time series and tick data (by man-group)
tickstore MongoDB Pandas arctic Timeseries timeseries-database Python Database
Source Code
arctic.readthedocs.io
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bcolz

A columnar data container that can be compressed. (by Blosc)
Science and Data analysis column-store Python compressed-data

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arctic bcolz
52 1
3,028 955
0.4% -
7.1 0.0
16 days ago over 1 year ago
Python C
GNU Lesser General Public License v3.0 only BSD 3-clause "New" or "Revised" License
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.

arctic

Posts with mentions or reviews of arctic. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2021-03-12.

bcolz

Posts with mentions or reviews of bcolz. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2021-05-13.
  • Recommendation for a Database for analysis
    5 projects | /r/algotrading | 13 May 2021
    What you need for your use case is a column-oriented store. I recommend explore bcolz or apache arrow for a column file-based systems. These are very fast, support memory mapping, uses compression and SSD speed (and even CPU architecture, in case of arrow) optimally almost out of the box, and has good interfaces to Numpy and Pandas (in case you are using Python for final data consumption and analysis). The columnar structure makes it easy to add or delete a column easily (or even dynamically). If you need a more scalable (albeit at the cost of speed) solution, you can devise a schema over a regular columnar db or an nosql db - see arctic from Man group for an example.

What are some alternatives?

When comparing arctic and bcolz you can also consider the following projects:

kdb - Companion files to kdb+ and q

zipline - Zipline, a Pythonic Algorithmic Trading Library

QuestDB - An open source time-series database for fast ingest and SQL queries

Kedro - Kedro is a toolbox for production-ready data science. It uses software engineering best practices to help you create data engineering and data science pipelines that are reproducible, maintainable, and modular.

pystore - Fast data store for Pandas time-series data

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

Apache Arrow - Apache Arrow is a multi-language toolbox for accelerated data interchange and in-memory processing

Dask - Parallel computing with task scheduling

ta-lib-python - Python wrapper for TA-Lib (http://ta-lib.org/).

blaze - NumPy and Pandas interface to Big Data

kafka-crypto-questdb - Using Kafka to track cryptocurrency price trends

NumPy - The fundamental package for scientific computing with Python.

arctic vs kdb bcolz vs zipline arctic vs QuestDB bcolz vs Kedro arctic vs pystore bcolz vs Pandas arctic vs Apache Arrow bcolz vs Dask arctic vs ta-lib-python bcolz vs blaze arctic vs kafka-crypto-questdb bcolz vs NumPy