--- title: "Pachyderm Software Reviews, Demo & Pricing - 2026" description: "Review of Pachyderm Software: system overview, features, price and cost information. Get free demos and compare to similar programs." source_url: "https://www.softwareadvice.com/machine-learning/pachyderm-profile/" page_type: "product" language: "en" --- [Home](https://www.softwareadvice.com/) / [Big Data Software](https://www.softwareadvice.com/bi/big-data-comparison/) / Pachyderm Software Advice offers objective insights based on verified user reviews and independent product and market research. When our advisors match you to a software provider, we may earn a referral fee. Overview # Pachyderm Review Custom quote Free trial 1 plan Wondering if Pachyderm is right for your organization? Our Big Data Software selection experts can help you in 15 minutes or less. On this page - Overview - User Interface - Popular Alternatives - Pricing and Plans - Features - User Reviews ## Overview Pachyderm 4.0 [(7)](https://www.softwareadvice.com/machine-learning/pachyderm-profile/#reviews) Pricing Pricing available upon request ### About Pachyderm Company: Pachyderm is the leader in data versioning and pipelines for MLOps. We provide the data foundation that allows data science teams to automate and scale their machine learning lifecycle while guaranteeing reproducibility. With over $40 million in three rounds of funding from leading investors like Benchmark, Microsoft M12, Y Combinator, and others, Pachyderm, Inc. offers a commercial Pachyderm Enterprise Edition and an open source Pachyderm Community Edition. Pachyderm helps customers get their ML and AI projects to market faster, lower data processing and storage costs, and supports strict data governance requirements.. Products: Pachyderm is for data science teams who want to operationalize the data tasks in their ML lifecycle to iterate on data more quickly and reliably. Pachyderm is the leader in data versioning and pipelines for MLOps, and this data foundation allows data science teams to automate and scale their machine learning lifecycle while guaranteeing reproducibility. Unlike other data versioning and pipeline products Pachyderm provides data-driven automation, petabyte scalability and end-to-end reproducibility. Pachyderm Enterprise Edition: Pachyderm Enterpr... ise Edition is our commercial offering designed for the largest projects in highly secure environments. Along with world-class support, your team also gets access to our full range of premium features including Pachyderm Console, authentication and access controls (RBAC), no scaling limits, JupyterHub integration, and centralized multiple cluster management. Pachyderm Community Edition: Pachyderm Community Edition is our open source version of Pachyderm. With Pachyderm Community Edition, you get the core Data Versioning and Pipeline features of Pachyderm that you can deploy locally or in the cloud of your choosing. If you need help, there’s an entire community of experts ready to offer their assistance. Wondering if Pachyderm is right for your organization? Our Big Data Software selection experts can help you in 15 minutes or less. ## Pachyderm User Interface ## Popular Pachyderm Alternatives Main Product Pachyderm 4.0 [(7)](https://www.softwareadvice.com/machine-learning/pachyderm-profile/#reviews) Ratings Breakdown - 3.29Ease of use - 4.0Value for money - 4.86Customer support - 4.57Functionality Pricing Available upon request Get Price Alternative Product [Anaconda](https://www.softwareadvice.com/machine-learning/anaconda-profile/) 4.6 [(87)](https://www.softwareadvice.com/machine-learning/anaconda-profile/reviews/) Ratings Breakdown - 4.39Ease of use - 4.59Value for money - 3.98Customer support - 4.64Functionality Pricing Available upon request Get Price Alternative Product [Google Cloud](https://www.softwareadvice.com/compliance/google-cloud-platform-profile/) 4.7 [(2328)](https://www.softwareadvice.com/compliance/google-cloud-platform-profile/reviews/) Ratings Breakdown - 4.48Ease of use - 4.42Value for money - 4.31Customer support - 4.60Functionality Pricing Available upon request Get Price Alternative Product [Splunk Enterprise](https://www.softwareadvice.com/aiops-platforms/splunk-enterprise-profile/) 4.6 [(264)](https://www.softwareadvice.com/aiops-platforms/splunk-enterprise-profile/reviews/) Ratings Breakdown - 4.13Ease of use - 4.26Value for money - 4.26Customer support - 4.52Functionality Pricing Available upon request Get Price Alternative Product [Zerve](https://www.softwareadvice.com/product/522850-Zerve/) 5.0 [(2)](https://www.softwareadvice.com/product/522850-Zerve/#reviews) Ratings Breakdown - 5.0Ease of use - 5.0Value for money - 5.0Customer support - 5.0Functionality Pricing Starting at $25.00 per month Get Price Alternative Product [Hopsworks](https://www.softwareadvice.com/data-management/hopsworks-profile/) 4.7 [(3)](https://www.softwareadvice.com/data-management/hopsworks-profile/#reviews) Ratings Breakdown - 4.67Ease of use - 5.0Value for money - 5.0Customer support - 5.0Functionality Pricing Starting at $1.00 per month Get Price ## Pachyderm Pricing and Plans Starting price: Connect with an advisor for pricing Free Trial Free Version Basic Pricing available upon request No plan information available Confused about pricing? We've got you covered. Get a personalized pricing breakdown tailored to your specific needs—no guesswork, no generic estimates. ## Pachyderm Features - Popular features found in Big Data Access Controls/Permissions Collaboration Tools Data Blending Data Connectors Data Security Data Visualization Data Warehousing Forecasting High Volume Processing Predictive Analytics Statistical Analysis - More features of Pachyderm Activity Dashboard API Asynchronous Learning Compliance Management Configurable Workflow Data Capture and Transfer Data Cleansing Data Extraction Data Import/Export Data Storage Management Data Transformation Deep Learning For eCommerce Image Analysis Machine Learning ML Algorithm Library Model Training Monitoring Multi-Language Multiple Data Sources Natural Language Processing Neural Network Modeling Performance Management Performance Metrics Predictive Modeling Real-Time Analytics Real-Time Monitoring Reporting & Statistics Role-Based Permissions Sentiment Analysis Speech Recognition Synchronous Learning Third-Party Integrations Version Control Visualization Workflow Automation Workflow Management ## Pachyderm User Reviews ## Pachyderm customer ratings - Overall rating: 4/5 - Total reviews: 7 ### Rating distribution - 5 stars: 1 reviews (14%) - 4 stars: 5 reviews (71%) - 3 stars: 1 reviews (14%) - 2 stars: 0 reviews (0%) - 1 star: 0 reviews (0%) ### Secondary ratings - Ease of use: 3.3/5 - Value for money: 4/5 - Customer support: 4.9/5 - Functionality: 4.6/5 --- Have you used Pachyderm and would like to share your experience with others? ### Rethinking Data in AI and ML - Overall rating: 4/5 - Reviewer: Clayton L. - Verified reviewer: Yes - Industry: Hospital & Health Care - Company size: 10000+ employees - Product usage: Used daily for less than 2 years - Reviewed: November 2021 - Review source details: This reviewer was invited by us to submit an honest review and offered a nominal incentive as a thank you. 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. #### Ratings breakdown - Ease of use: 3/5 - Value for money: 4/5 - Customer support: 5/5 - Functionality: 5/5 #### 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. #### 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. #### Reasons for switching to Pachyderm 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. #### Vendor response Thank you for your very thorough review Clayton. Replied November 2021 --- ### Game changer for handling dynamic data - Overall rating: 4/5 - Reviewer: Cove C. - Verified reviewer: Yes - Industry: Research - Company size: 201-500 employees - Product usage: Used daily for more than 2 years - Reviewed: November 2021 - Review source details: This reviewer was invited by us to submit an honest review and offered a nominal incentive as a thank you. 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. #### Ratings breakdown - Ease of use: 4/5 - Customer support: 5/5 - Functionality: 5/5 #### 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. --- ### Great in theory - Overall rating: 3/5 - Reviewer: Martin L. - Verified reviewer: Yes - Industry: Biotechnology - Company size: 51-200 employees - Product usage: Used weekly for less than 12 months - Reviewed: October 2021 - Review source details: This reviewer was invited by us to submit an honest review and offered a nominal incentive as a thank you. 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. #### Ratings breakdown - Ease of use: 2/5 - Customer support: 4/5 - Functionality: 4/5 #### 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. #### Vendor response 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. Replied November 2021 --- ### Pachyderm is a great data processing platform on cloud. - Overall rating: 4/5 - Reviewer: Xubo F. - Verified reviewer: Yes - Industry: Biotechnology - Company size: 201-500 employees - Product usage: Used daily for less than 2 years - Reviewed: October 2021 - Review source details: This reviewer was invited by us to submit an honest review and offered a nominal incentive as a thank you. 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. #### Ratings breakdown - Ease of use: 5/5 - Value for money: 4/5 - Customer support: 5/5 - Functionality: 5/5 #### 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. #### Vendor response 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 Replied October 2021 --- ### Scalable machine learning without the mlops - Overall rating: 5/5 - Reviewer: Chris K. - Verified reviewer: Yes - Industry: Marketing and Advertising - Company size: 2-10 employees - Product usage: Used daily for less than 12 months - Reviewed: October 2021 - Review source details: This reviewer was invited by us to submit an honest review and offered a nominal incentive as a thank you. #### Ratings breakdown - Ease of use: 3/5 - Value for money: 4/5 - Customer support: 5/5 - Functionality: 5/5 #### 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. #### Vendor response Thank you for your review Chris! Replied November 2021 --- ### Pachyderm for data pipelines - Overall rating: 4/5 - Reviewer: Chris H. - Verified reviewer: Yes - Industry: Information Technology and Services - Company size: 2-10 employees - Product usage: Used weekly for less than 2 years - Reviewed: October 2021 - Review source details: This reviewer was invited by us to submit an honest review and offered a nominal incentive as a thank you. #### Ratings breakdown - Ease of use: 4/5 - Value for money: 4/5 - Customer support: 5/5 - Functionality: 5/5 #### 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. #### Vendor response 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. Replied November 2021 --- ### The missing ingredient for reproducible research - Overall rating: 4/5 - Reviewer: Will O. - Verified reviewer: Yes - Industry: Information Technology and Services - Company size: 51-200 employees - Product usage: Used weekly for less than 12 months - Reviewed: November 2021 - Review source details: This reviewer was invited by us to submit an honest review and offered a nominal incentive as a thank you. 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. #### Ratings breakdown - Ease of use: 2/5 - Value for money: 4/5 - Customer support: 5/5 - Functionality: 3/5 #### 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. #### Vendor response Thank you for the review, Will. 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