List of data science software

Last updated October 07, 2025

This is a list of data science software and platforms used in data science, which includes programming languages, programming environments, machine learning frameworks, data engineering tools, statistical software, data analysis, plotting, MLOps systems, and more.

Programming languages

Development environments

These interactive notebooks, IDEs, and platforms provide specialised development environments.

Machine and deep learning software

The Machine learning / deep learning tools support development in those fields.

Data engineering

Examples of Data engineering tools.

Data mining

Examples of Data mining tools.

Free and open-source

Proprietary

Database management

Data warehouses

Data warehouse environments include:

Data lakes

Data lake environments include:

Algorithms

Apriori algorithm – frequent itemset mining and association rule learning in market basket analysis
Backpropagation – algorithm for training artificial neural networks using gradient descent
Decision Trees – tree-based algorithm for classification and regression
Expectation–maximization algorithm – iterative procedure for maximum likelihood estimation with latent variables
Gradient descent – iterative optimization algorithm for minimizing a loss function
ID3 algorithm – used to generate a decision tree from a dataset
K-Means – clustering algorithm based on minimizing within-cluster distances
K-Nearest Neighbors (KNN) – instance-based learning and classification method
Linear regression – estimation method for predicting a dependent variable based on independent variables
Logistic regression – classification algorithm for predicting a binary outcome
Naive Bayes – probabilistic classifier based on Bayes' theorem
Ordinary least squares – estimation method for parameters in linear regression
PageRank – graph-based algorithm for link analysis and search ranking
Principal component analysis – technique to reduce high-dimensional data while preserving variance
Q-learning – reinforcement learning algorithm for learning optimal actions
Random forest – ensemble of decision trees for improved classification or regression
Sequential minimal optimization – solver for training support vector machines
Stochastic gradient descent – randomized variant of gradient descent for large-scale machine learning
Support Vector Machines (SVM) – algorithm for finding a hyperplane to separate classes^[13]^[14]

Statistical software

Public domain

Freeware

Data processing

Tools for Data processing and analysis:

Data and information visualization

Software for Data visualization:

Plotting software

Software for plotting data to support processing and visualise resuls.

Maps and geospatial visualization

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

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

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). Proceedings 2014 Paper SAS302-2014. Cary, NC: SAS Institute Inc.
↑ "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". IEEE Data Eng. Bull.– via GitHub.
↑ "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".
↑ https://archive.ics.uci.edu
↑ "OpenML".

External links

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[1] "Top 10 Java Libraries for Data Science". GeeksforGeeks. September 22, 2024.

[2] "Swift for Data Science: An Introduction - Alibaba Cloud". www.alibabacloud.com.

[3] "Top 12 Data Science Programming Languages | MDS@Rice". csweb.rice.edu.

[4] "5 Types of Programming Languages for Data Scientists".

[5] "The Role of Programming Languages in Data Science". New York Tech Online College of Engineering & Computer Sciences.

[6] "Apache Zeppelin 0.10.0 Documentation". zeppelin.apache.org.

[7] Monaco, Michael A.; Dexter, Marie; Tamburro, Jennifer. "Introduction to SAS® Studio" (PDF). Proceedings 2014 Paper SAS302-2014. Cary, NC: SAS Institute Inc.

[8] "6 Best Python IDEs for Data Science in 2025". www.datacamp.com.

[9] "8 Best Machine Learning Software To Use in 2025".

[10] Hiter, Shelby (April 25, 2023). "10 Best Data Mining Tools & Software".

[11] "Cloud Data Warehouse Comparison: Amazon Redshift, Google BigQuery, Azure Synapse, Snowflake, and Databricks". www.linkedin.com.

[12] Darley, James (September 24, 2025). "Top 10: AI Data Lakes". aimagazine.com.

[13] "Top 10 Algorithms for Data Science".

[14] "Machine Learning Algorithms". 17 August 2023.

[15] Staff, Coursera (May 9, 2025). "15 Data Analysis Tools and When to Use Them". Coursera.

[16] "BentoML". GitHub.

[17] "MLflow". mlflow.org.

[18] 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". IEEE Data Eng. Bull.– via GitHub.

[19] "Production-ready ML Serving Framework | Seldon Core 2". docs.seldon.ai.

[20] "Streamlit/Streamlit". GitHub .

[21] ttps://docs.streamlit.io

[22] "Serving Models | TFX". TensorFlow.

[23] "tensorflow/serving". September 27, 2025 – via GitHub.

[24] "wandb/wandb". September 28, 2025 – via GitHub.

[25] "Find Open Datasets and Machine Learning Projects | Kaggle".

[26] ttps://archive.ics.uci.edu

[27] "OpenML".

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List of data science software

Contents

Programming languages

Development environments

Machine and deep learning software

Data engineering

Data mining

Free and open-source

Proprietary

Database management

Data warehouses

Data lakes

Algorithms

Statistical software

Open-source

Public domain

Freeware

Proprietary

Data processing

Data and information visualization

Plotting software

Maps and geospatial visualization

Machine learning

Data repositories

See also

References

External links