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List of data science software

From Wikipedia, the free encyclopedia

This is alist of data science software and platforms used indata science, which includesprogramming languages, programming environments,machine learning frameworks,data engineering tools,statistical software,data analysis,plotting,MLOps systems, and more.

Programming languages

See also:List of data-oriented programming languages

Development environments

Theseinteractive notebooks,IDEs, and platforms provide specialised development environments.

Machine and deep learning software

TheMachine learning /deep learning tools support development in those fields.

See also:Comparison of deep learning software,List of data mining and machine learning software,List of open-source machine learning software, andList of neural network software

Data engineering

Examples ofData engineering tools.

See also:Comparison of data modeling tools

Data mining

Examples ofData mining tools.

See also:List of data mining software

Free and open-source

Proprietary

Database management

See also:List of relational database management systems,List of NoSQL databases,List of SQL software and tools,List of NoSQL software and tools,Comparison of database administration tools, andList of time series databases

Data warehouses

Data warehouse environments include:

Data lakes

Data lake environments include:

Algorithms

See also:List of algorithms,List of machine learning algorithms,List of optimization algorithms, andList of database algorithms

Apriori algorithm – frequent itemset mining andassociation rule learning inmarket basket analysis
Backpropagation – algorithm for trainingartificial neural networks usinggradient descent
Decision Trees –tree-based algorithm for classification and regression
Expectation–maximization algorithm – iterative procedure formaximum likelihood estimation withlatent variables
Gradient descent – iterativeoptimization algorithm for minimizing aloss function
ID3 algorithm – used to generate adecision tree from a dataset
K-Means –clustering algorithm based on minimizing within-clusterdistances
K-Nearest Neighbors (KNN) –instance-based learning andclassification method
Linear regression –estimation method for predicting adependent variable based onindependent variables
Logistic regression –classification algorithm for predicting abinary outcome
Naive Bayes –probabilistic classifier based onBayes' theorem
Ordinary least squares –estimation method for parameters inlinear regression
PageRank –graph-based algorithm forlink analysis andsearch ranking
Principal component analysis – technique to reducehigh-dimensional data while preserving variance
Q-learning –reinforcement learning algorithm for learningoptimal actions
Random forest – ensemble ofdecision trees for improvedclassification or regression
Sequential minimal optimization – solver for trainingsupport vector machines
Stochastic gradient descent – randomized variant ofgradient descent for large-scalemachine learning
Support Vector Machines (SVM) – algorithm for finding ahyperplane to separate classes^[13]^[14]

Statistical software

See also:List of statistical software andComparison of statistical packages

Open-source

Public domain

Freeware

Proprietary

Data processing

Tools forData processing and analysis:

See also:List of data analysis software andComparison of OLAP servers

Data and information visualization

Software forData visualization:

See also:List of information graphics software,List of charting software,Comparison of JavaScript charting libraries, andList of free data visualization software

Plotting software

Software forplotting data to support processing and visualise resuls.

Maps and geospatial visualization

See also:List of GIS mapping software

Machine learning

MLOps and model deployment:

BentoML^[16]
Data Version Control (DVC)
Kubeflow
MLflow^[17]^[18]
Seldon Core^[19]
Streamlit^[20]^[21]
TensorFlow Serving^[22]^[23]
Weights & Biases^[24]

Data repositories

See also:List of datasets for machine-learning research,Comparison of source-code-hosting facilities, andComparison of data-serialization formats

Kaggle – platform for data science competitions, datasets,^[25] and notebooks.
OpenML – collaborative platform for sharing datasets, algorithms, and experiments.^[26]
University of California, Irvine Machine Learning Repository^[27]
Zenodo – open-access repository supported byCERN and theEU.

Educational data science software

See also:Jupyter Notebook andGoogle Colab

Kaggle – online platform for data science education, competitions, datasets, and collaborative learning.
KNIME – open-source data analytics platform used for teaching data science, machine learning, and workflow-based analysis.
RapidMiner – used in academic research and education for data mining and machine learning.
Statistics Online Computational Resource (SOCR) – online tools and instructional resources for statistics education.
Tanagra (machine learning) – data mining software developed for research and teaching purposes.
TinkerPlots – explore and analyze data through visual modeling.

See also

Wikibooks has a book on the topic of:Data Science: An Introduction

Business intelligence software
List of data science journals
List of R software and tools
Lists of mathematical software andList of open-source software for mathematics
List of numerical-analysis software andList of numerical analysis topics
List of open-source data science software
Common Crawl –nonprofit thatcrawls the web and freely provides its archives and datasets to the public under anMIT License

References

^"Top 10 Java Libraries for Data Science".GeeksforGeeks. September 22, 2024.
^"Swift for Data Science: An Introduction - Alibaba Cloud".www.alibabacloud.com.
^"Top 12 Data Science Programming Languages | MDS@Rice".csweb.rice.edu.
^"5 Types of Programming Languages for Data Scientists".
^"The Role of Programming Languages in Data Science".New York Tech Online College of Engineering & Computer Sciences.
^"Apache Zeppelin 0.10.0 Documentation".zeppelin.apache.org.
^Monaco, Michael A.; Dexter, Marie; Tamburro, Jennifer."Introduction to SAS® Studio"(PDF).
^"6 Best Python IDEs for Data Science in 2025".www.datacamp.com.
^"8 Best Machine Learning Software To Use in 2025".
^Hiter, Shelby (April 25, 2023)."10 Best Data Mining Tools & Software".
^"Cloud Data Warehouse Comparison: Amazon Redshift, Google BigQuery, Azure Synapse, Snowflake, and Databricks".www.linkedin.com.
^Darley, James (September 24, 2025)."Top 10: AI Data Lakes".aimagazine.com.
^"Top 10 Algorithms for Data Science".
^"Machine Learning Algorithms". 17 August 2023.
^Staff, Coursera (May 9, 2025)."15 Data Analysis Tools and When to Use Them".Coursera.
^"BentoML".GitHub.
^"MLflow".mlflow.org.
^Zaharia, Matei A.; Chen, Andrew; Davidson, Aaron; Ghodsi, Ali; Hong, Sue Ann; Konwinski, Andy; Murching, Siddharth; Nykodym, Tomas; Ogilvie, Paul; Parkhe, Mani; Xie, Fen; Zumar, Corey (September 28, 2018)."Accelerating the Machine Learning Lifecycle with MLflow"(PDF).Bulletin of the IEEE Computer Society Technical Committee on Data Engineering:39–45.
^"Production-ready ML Serving Framework | Seldon Core 2".docs.seldon.ai.
^"Streamlit/Streamlit".GitHub.
^https://docs.streamlit.io
^"Serving Models | TFX".TensorFlow.
^"tensorflow/serving". September 27, 2025 – via GitHub.
^"wandb/wandb". September 28, 2025 – via GitHub.
^"Find Open Datasets and Machine Learning Projects | Kaggle".
^"OpenML".
^https://archive.ics.uci.edu

External links

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