--- title: "Pachyderm Software Pricing, Alternatives & More 2026 | Capterra" description: "With the help of Capterra, learn about Pachyderm Software - reviews, pricing plans, popular comparisons to other Artificial Intelligence products and more." source_url: "https://www.capterra.com/p/235292/Pachyderm/" page_type: "product" language: "en" --- # Pachyderm Software Review 2026: Features, Integrations, Pros & Cons Last updated on August 20, 2026 Provider data verified by our Software Research team, and reviews moderated by our Reviews Verification team. [Description](#description)[Use cases](#use-cases)[Alternatives](#alternatives)[FAQs](#faqs)[Features](#features)[Pricing](#pricing)[Support](#support)[Reviews](#reviews) Pachyderm ## What is Pachyderm? Pachyderm is the leader in data versioning and pipelines for MLOps. We help data science teams operationalize the data tasks in their ML lifecycle to iterate on data more quickly and reliably. Pachyderm’s data foundation allows data science teams to automate and scale their machine learning lifecycle while guaranteeing reproducibility. ## What is Pachyderm used for? [Big Data](https://www.capterra.com/big-data-software/)[Machine Learning](https://www.capterra.com/machine-learning-software/)[Artificial Intelligence](https://www.capterra.com/artificial-intelligence-software/) Overall rating Based on 7 user reviews Reviews sentiment Positive \- Neutral \- Negative \- ### Starting price Free trial available Capterra Shortlist charts the highest-rated and most popular products... Our "Best of" badge program showcases products with the highest ratings... Our "Best of" badge program showcases products with the highest ratings... Do you work for Pachyderm?[Manage this product listing](https://digitalmarkets.gartner.com/get-listed/claim-bx?url=https://www.hpe.com&name=Pachyderm) ## Compare with a popular alternative Capterra selects software alternatives based on relevant features, verified user reviews and user interactions. Placement may be influenced by client status. ### Pachyderm 4.0 (7) VS. [### Anaconda](https://www.capterra.com/p/191760/Anaconda/) [4.6 (87)](https://www.capterra.com/p/191760/Anaconda/reviews/) Starting Price Contact vendor Starting Price Contact vendor Free Trial Free Version Pricing Options Free Trial Free Version Ease Of Use 3.3 (7) Ease Of Use 4.4 (87) Value For Money 4.0 (5) Value For Money 4.6 (59) Customer Service 4.9 (7) Customer Service 4.0 (53) ## Pachyderm alternatives Highest Rated [OpenText Analytics Cloud](https://www.capterra.com/p/177019/OpenText-Analytics-Suite/) [5.0 (1)](https://www.capterra.com/p/177019/OpenText-Analytics-Suite/#reviews) Starting price $0.01 Per User, Per Month Pricing Options Free Trial Free Version User Rating 100% of reviewers rated it above 4 stars [Learn More](https://www.capterra.com/p/177019/OpenText-Analytics-Suite/) [Hopsworks](https://www.capterra.com/p/199971/Hopsworks/) [4.7 (3)](https://www.capterra.com/p/199971/Hopsworks/#reviews) Starting price $1.00 Per User, Per Month Pricing Options Free Trial Free Version User Rating 100% of reviewers rated it above 4 stars [Learn More](https://www.capterra.com/p/199971/Hopsworks/) [Google Cloud](https://www.capterra.com/p/268690/Google-Cloud-Platform/) [4.7 (2,322)](https://www.capterra.com/p/268690/Google-Cloud-Platform/reviews/) Starting price Contact vendor for pricing Pricing Options Free Trial Free Version User Rating 96% of reviewers rated it above 4 stars [Learn More](https://www.capterra.com/p/268690/Google-Cloud-Platform/) [Splunk Enterprise](https://www.capterra.com/p/94317/Splunk/) [4.6 (264)](https://www.capterra.com/p/94317/Splunk/reviews/) Starting price Contact vendor for pricing Pricing Options Free Trial Free Version User Rating 95% of reviewers rated it above 4 stars [Learn More](https://www.capterra.com/p/94317/Splunk/) [View all alternatives](https://www.capterra.com/p/235292/Pachyderm/alternatives/) ## FAQs about Pachyderm Overview ### What company size and specific industries is Pachyderm built for? Pachyderm is designed for data science teams, especially in mid-market and enterprise organizations, that need to operationalize data tasks across the machine learning lifecycle. It is suited to teams in any industry that rely on frequent data iteration and dependable ML workflows. Features and Usability ### What are the key features of Pachyderm? Pachyderm offers data capture and transfer, data transformation, data replication, and secure data storage for managing machine learning data pipelines. It includes version control, workflow management, monitoring, access controls, and role-based permissions, plus reporting, visualization, and third-party integrations for tracking and coordinating model training and analytics. Integrations ### Which third-party tools and platforms does Pachyderm integrate with? Pachyderm integrates with The Jupyter Notebook for data exploration and pipeline development. It connects to this notebook environment to support a workflow that moves from analysis to building Pachyderm pipelines. Answer based on 1 reviews Getting Started and Support ### What training and onboarding options does Pachyderm offer? Pachyderm provides in person training, live online sessions, webinars, documentation, and videos. In person and live online formats support guided instruction, webinars cover scheduled group learning, documentation offers written reference material, and videos provide visual self-paced guidance for teams getting started. Getting Started and Support ### What customer support options does Pachyderm offer? Pachyderm provides email/help desk support, a FAQ/forum, and a knowledge base. These channels give users a place to send questions, search common answers, and review self-service documentation. No reviewer feedback about support experience is available, so no claims can be made about response time or helpfulness. ## Features AI summary Based on 5,440 Artificial Intelligence reviews Not all Artificial Intelligence products cover every feature buyers care about most. Here is what Capterra reviewers identify as essential when choosing a solution: - **Generative AI** (**36%** of reviewers rated this feature as critical) - **Data Import/Export** (**31%**) - **Natural Language Processing** (**34%**) Pachyderm includes **Data Import/Export** and **Natural Language Processing**, so teams can move data in and out of the system and work with text-based inputs more effectively. However, it does not offer **Generative AI**. Instead, it provides **Machine Learning** (**33%**) and **Multi-Language** (**29%**), which can support model development and broader language accessibility, helping businesses build AI workflows that fit varied data and user needs. Machine Learning 5.0 (2) 100.00% of 2 reviewers that rated this feature as important or highly important Enable businesses to implement machine learning algorithms on business data such as sales and revenue High Volume Processing 4.5 (2) 100.00% of 2 reviewers that rated this feature as important or highly important Process and analyze large volume of data Workflow Automation 5.0 (1) 100.00% of 1 reviewers that rated this feature as important or highly important Streamlining repetitive tasks and activities through automated and predefined workflows Access Controls/Permissions Define levels of authorization for access to specific files or systems Activity Dashboard Dashboard to view the status of ongoing processes, identify current incidents and track past activities API Application programming interface that allows for integration with other systems/databases Pachyderm 43 features ### All Features - Access Controls/Permissions: Define levels of authorization for access to specific files or systems - Activity Dashboard: Dashboard to view the status of ongoing processes, identify current incidents and track past activities - API: Application programming interface that allows for integration with other systems/databases - Asynchronous Learning: Supports flexible learning at different times (i.e., learners can access course materials at their own pace) - Collaboration Tools: Provides a channel for team members to share AI models, media files, communicate, and work together - Compliance Management: Track and manage adherence to policies for any service, product, process, or supplier - Configurable Workflow: Configure existing workflows to meet your organization's needs - Data Capture and Transfer: Import, collect, and capture data from multiple sources - Data Cleansing: Removes data that is incomplete, inaccurate, or irrelevant from a dataset - Data Connectors: Connect to big data sources - Data Extraction: Automatically retrieve and pull information from documents, websites, images, data sets, and other sources - Data Import/Export: Import and export data to and from software applications - Data Storage Management: Manage and store data in a database - Data Transformation: Translate EDI formats into data suitable for use with company applications. - Data Visualization: Graphical representation of data - Deep Learning: Artificial neural networks using multiple layers of processing are used to extract progressively higher level features from data. - For eCommerce: Intended to be used by online stores - High Volume Processing: Process and analyze large volume of data - Image Analysis: Evaluating and identifying the fundamental components in an image for extracting medical information. - Machine Learning: Enable businesses to implement machine learning algorithms on business data such as sales and revenue - ML Algorithm Library: Share, track, and store machine learning models and data. - Model Training: Process of testing an ML algorithm by feeding it training data to learn from - Monitoring: Observe and track the demand, usage, progress or quality of a system, product, or user - Multi-Language: Manage and support multiple languages - Multiple Data Sources: Allows users to manage data from a number of sources - Natural Language Processing: Process and analyze human language in text or audio form - Neural Network Modeling: A classification and/or predictive modeling technique used for data analysis - Performance Management: Organize and manage the accomplishments and development of employees or performance of applications or systems - Performance Metrics: A set of indicators that tracks the performance of networks, applications, systems, teams, etc. - Predictive Analytics: Predict future data based on historical data sets - Predictive Modeling: Analyzing historical and current data and generating a model to help predict future outcomes. - Real-Time Analytics: Analyze and gain insights into data in real-time - Real-Time Monitoring: Active monitoring of systems, applications, or networks - Reporting & Statistics: Collection, analysis, and representation of numerical data and generation of reports to understand various patterns - Role-Based Permissions: Set & manage permission levels based on user roles and restrict access to only authorized individuals - Sentiment Analysis: Categorize emotions expressed and identify if they are positive, negative or neutral - Speech Recognition: Train your system to interpret and transcribe voice messages - Synchronous Learning: Real-time, interactive learning experiences where participants engage in learning activities simultaneously - Third-Party Integrations: Set up connections to third-party platforms to improve business processes - Version Control: Track revisions and updates made to files and navigate between different versions - Visualization: Graphical representation of data or processes - Workflow Automation: Streamlining repetitive tasks and activities through automated and predefined workflows - Workflow Management: Create, design and manage workflows for repetitive tasks --- Get Advice We can help you find the software with the features you need. Features 4.6 (7) 4.6 Based on 7 reviews ## Pricing Value for money 4.0 (5) ### Starting price Free trial available Value for money 4.0 (5) 4.0 Based on 5 reviews Connect with a Capterra advisor for a free 15-minute consultation Get a personalized software list aligned to your business needs with guidance from our expert advisors. Our team has helped 1 million+ businesses like yours find options that fit their needs. ## Support, customer service and training options Customer Service 4.9 (7) Support - Email/Help Desk - FAQs/Forum - Knowledge Base - Phone Support - 24/7 (Live rep) - Chat Training - In Person - Live Online - Webinars - Documentation - Videos Deployment - Web - Android - iPhone/iPad Typical users - Freelancers - Small businesses - Mid size businesses - Enterprises Customer Service 4.9 (7) 4.9 Based on 7 reviews ## User reviews Overall rating 4.0 Based on 7 reviews Filter by rating 5(1) 4(5) 3(1) 2(0) 1(0) Mentioned topic Sorted by most recent CC Cove C. Data Scientist Research ### "Game changer for handling dynamic data" 4.0 Overall Rating 4.0 4.0 Ease of Use 4.0 4.0 Features 5.0 5.0 Customer Service 5.0 5.0 Likelihood to Recommend 10/10 November 17, 2021 Pachyderm meets many previously unmet needs for our organization, including complete data provenance, automatic handling of data change, and modular/portable processing architecture, which facilitates the joint development of processing pipelines between software developers and scientists. Pachyderm engineers have been extremely responsive to our issues and development requests, and we plan to work well into the future with this software. Pros Perhaps the most important aspect we benefit from operationally is the awareness and automatic handling of data change. Generation of our data products involves multiple processing steps and several sources of data and metadata that enter the processing sequence at various points and may change at any time. Pachyderm automatically knows what has changed and triggers downstream (re)processing, removing the need for error-prone human management. Cons In Pachyderm 1.X there was a relatively high amount of overhead associated with processing each datum. Our data typically consists of small but numerous datums, and we needed to artificially combine datums for performance. However, Pachyderm has been working with us on this issue and we expect to see big improvements in 2.0 and beyond. Review source Incentivized review: software users are invited to submit an honest review and offered a nominal incentive for their time and effort. All incentivized reviews are subject to our verification process prior to publication. Clayton L. Lead Software Engineer Hospital & Health Care ### "Rethinking Data in AI and ML" 4.0 Overall Rating 4.0 4.0 Ease of Use 3.0 3.0 Features 5.0 5.0 Customer Service 5.0 5.0 Likelihood to Recommend 10/10 November 11, 2021 Like any tool, Pachyderm is no silver bullet for the entire AI/ML stack. However, from a data processing and management perspective, it has fulfilled every application requirement I've needed it for and continues to be a flexible tool in meeting additional requirements. For example, after having computed some results from a pipeline, I needed to serve these results to an existing application. Pachyderm made this simple by exposing the data through a built-in S3 REST API. Since the application was already compatible with S3, Pachyderm served as a drop-in replacement for an S3 bucket. For anyone that strives to design clean and straightforward AI/ML architectures, I can definitely recommend Pachyderm as a must for the foundational data component. Pros AI/ML production systems typically consist of multiple data processing steps organized as a DAG. Many automation frameworks manage these DAGs as tightly coupled steps ordered by \_code execution\_. What I like so much about Pachyderm is that it approaches DAG management as loosely coupled steps ordered by \_data dependencies\_. This alternative way of thinking has enabled me to design AI/ML architectures with data at the center, which has revolutionized the development and production workflows I've participated in. I can confidently store, process, and otherwise manage the data because Pachyderm provides a solid foundation for data provenance, data versioning, data storage patterns, and efficient incremental processing. Since AI/ML models are effectively a form of data, model versioning and management can be built as an extension of Pachyderm's data foundation. Furthermore, I really like that Pachyderm is powered by Kubernetes, because it passes on important architectural properties to Pachyderm, such as high scalability, robustness, efficiency, and portability (i.e. cloud agnosticism). I can containerize my pipelines, quickly test them locally through Docker Desktop or minikube, then scale them up to massive amounts of data in an on-prem or cloud cluster. If autoscaling is supported in a cloud cluster, I can especially reap the benefits of cost efficiency because I only pay for the compute resources I use. Cons \- In 1.X versions of Pachyderm, there are a few performance pain points, especially around handling very small files when uploading/downloading to/from a repo. These pain points have been significantly improved in Pachyderm 2.X. - Also in 1.X, debugging pipeline failures can sometimes be challenging without extra tools or integrating external logging services. Pachyderm 2.X improves upon this as well. - When Pachyderm processes data files in a pipeline, it groups the files into logical structures called datums for provenance and data efficiency reasons, and then it invokes the pipeline on each datum. This is necessary for scalability, but the downside is that each invocation of the pipeline incurs an overhead cost of just starting the processing code. The bright side is that there are several straightforward ways to engineer around the problem. It's also important to recognize that the impact of the problem is minimized by the benefits of incremental processing(i.e. only processing data that has changed on future pipeline runs). - This isn't necessarily a problem, but prospective buyers should be aware that although compute costs may go down due to incremental processing, storage costs may go up due to storing multiple versions of data. Switched from [Apache Airflow](https://www.capterra.com/p/239023/Apache-Airflow/) Airflow is mainly geared for pipeline orchestration. My team had to build in a custom data management layer, but there was much to be desired in terms of provenance and versioning. Since Pachyderm already provided these features plus pipeline orchestration, it made more sense to not reinvent the wheel with Airflow. Reasons for choosing Pachyderm Although DVC provides data version control features and AI/ML pipeline management, it lacks containerized pipeline orchestration and seems better suited for small teams in startup or research environments. We needed an enterprise-level service. Review source Incentivized review: software users are invited to submit an honest review and offered a nominal incentive for their time and effort. All incentivized reviews are subject to our verification process prior to publication. Response from Vendor November 16, 2021 Thank you for your very thorough review Clayton. WO Will O. Principle Engineer Information Technology and Services ### "The missing ingredient for reproducible research" 4.0 Overall Rating 4.0 4.0 Ease of Use 2.0 2.0 Features 3.0 3.0 Customer Service 5.0 5.0 Likelihood to Recommend 10/10 November 5, 2021 I'm a big fan of the pachyderm approach; it's young software and needs to be understood a little to get the best out of it; but when stuff works, it works so damn well. Pros The systematic recording of provenance for training and benchmarking results. Cons When things go wrong, it's hard to diagnose. Reasons for choosing Pachyderm For NLP, the requirements around data curation for training are slightly singular, pachyderms offering was the only sensible one for us. Review source Incentivized review: software users are invited to submit an honest review and offered a nominal incentive for their time and effort. All incentivized reviews are subject to our verification process prior to publication. Response from Vendor November 12, 2021 Thank you for the review, Will. CK Chris K. Director of Engineering and Data Science Marketing and Advertising ### "Scalable machine learning without the mlops " 5.0 Overall Rating 5.0 5.0 Ease of Use 3.0 3.0 Features 5.0 5.0 Customer Service 5.0 5.0 Likelihood to Recommend 10/10 October 29, 2021 Pros The ability to scale model builds in native python is something that has been missing in this space until now. Utilizing spark and/or dask comes with a large amount of overhead that can be avoided leveraging pachyderm. Cons The learning curve is quite steep since there are some core concepts that are foundational to understand before using pachyderm. Review source Incentivized review: software users are invited to submit an honest review and offered a nominal incentive for their time and effort. All incentivized reviews are subject to our verification process prior to publication. Response from Vendor November 2, 2021 Thank you for your review Chris! CH Chris H. Lead Developer Information Technology and Services ### "Pachyderm for data pipelines" 4.0 Overall Rating 4.0 4.0 Ease of Use 4.0 4.0 Features 5.0 5.0 Customer Service 5.0 5.0 Likelihood to Recommend 6/10 October 29, 2021 Pros Pachyderm pipelines are an intuitive way to split and process data concurrently using autoscaling compute clusters. Writing a program to interact with data in a pipeline is straightforward due to working similar to a native filesystem, requiring no additional libraries or integrations. Cons We ran into issues with Pachyderm that required deleting and recreating pipelines. As an upside, support was very responsive to resolving our problems and providing upgrades to Pachyderm. Review source Incentivized review: software users are invited to submit an honest review and offered a nominal incentive for their time and effort. All incentivized reviews are subject to our verification process prior to publication. Response from Vendor November 1, 2021 Chris, Thank you for your great feedback. We're glad to hear that our support team has been a great asset to you. We'll make sure to pass along the feedback. ML Martin L. Sr. Data Scientist Biotechnology ### "Great in theory" 3.0 Overall Rating 3.0 3.0 Ease of Use 2.0 2.0 Features 4.0 4.0 Customer Service 4.0 4.0 Likelihood to Recommend 6/10 October 26, 2021 We achieved some of our goals with Pachyderm. However, we were really hoping to spend more time on solving the problems directly related with our goal. Instead, we spent a significant amount on time solving problems with Pachyderm and tailoring our problem to it. Pros Great concept, really fits what we would like to do. Re-computing only the pieces where the data has changed is super valuable. Cons Working with it in practice is very hard. We would like to use Pachyderm also for research, developing research pipelines that can be executed easily on big amounts of data on the cluster. However, during research/development, pipelines naturally crash often. Translating something that works locally to something that works in pachyderm has several scenarios in which it can fail. Inspecting those types of errors is incredibly difficult, unless you invest a significant amount of time into setting up logging/monitoring manually. Review source Incentivized review: software users are invited to submit an honest review and offered a nominal incentive for their time and effort. All incentivized reviews are subject to our verification process prior to publication. Response from Vendor November 1, 2021 Hello Martin, thank you for your feedback, we truly appreciated it. Pachyderm 2 will have several enhancements around the troubleshooting workflow for pipelines and the new Console (dashboard) will likely be of great help here. However, we're striving to further improve the user experience of Pachyderm with every release. Thank you. XF Xubo F. Staff Data Engineer Biotechnology ### "Pachyderm is a great data processing platform on cloud." 4.0 Overall Rating 4.0 4.0 Ease of Use 5.0 5.0 Features 5.0 5.0 Customer Service 5.0 5.0 Likelihood to Recommend 9/10 October 25, 2021 We have used Pachyderm for more than a year. Overall experience is Good. We love the core technology and features provided by Pachyderm. We experienced frustrated issues, like the download speed, deployment, system stability. We get excellent support from the Pachyderm team all the time. Pros Data Driven Automation. It supports incremental data processing. Reproducibility. Perfectly match our tech stacks: K8s, S3. Community facing. Cons We expect fully automated data replication/export to external storage system. The logging & debugging support could be improved. Reasons for choosing Pachyderm Data Driven Automation. It supports incremental data processing. Easy integration with our infrastructure. Review source Incentivized review: software users are invited to submit an honest review and offered a nominal incentive for their time and effort. All incentivized reviews are subject to our verification process prior to publication. Response from Vendor October 27, 2021 Xubo, Thank you for your review, we greatly appreciate your feedback. We'll make sure to pass your feedback around logging and debugging on to our product team. - Pachyderm [View all Reviews](https://www.capterra.com/p/235292/Pachyderm/reviews/) ## Top-rated software of 2026 ### Fill out the form and we'll send a list of the top-rated software based on real user reviews directly to your inbox.