Pachyderm Reviews & Product Details

With its container-based architecture, Pachyderm is designed to handle large amounts of data efficiently by allowing computations to be easily scaled across a cluster of machines. As an open-source platform, Pachyderm is available to a wide range of users and has a thriving community of developers who contribute to its growth and development. Review collected by and hosted on G2.com.

Pachyderm can present a challenge to some users, particularly those without experience in big data processing or container-based architecture. Despite integration with some widely used big data tools, Pachyderm's technology ecosystem is relatively limited compared to others, which may restrict its compatibility with some tools and technologies. Review collected by and hosted on G2.com.

Pachyderm eases the MLOPs for Data Scientists and Data/ML Engineers to a great extent. Its key strength lies in tracking model lineage & version control that no other tool offers so seamlessly and in a simplified UI. It now offers model pipeline where you may run model experiments from a singular user interface. Review collected by and hosted on G2.com.

There must be a free-to-use subscription since community edition does not provides all of the functions as compared to the enterprise edition. The free-to-use edition must provide all the features in limited capability to evaluate the product and the enterprise edition must have unlimited access and runtime to all the features. Maybe in future, Pachyderm may design a single product stack that meets the requirements of end to end MLOps including model build, train, serve, deploy and monitor along with CI/CD pipelines. Review collected by and hosted on G2.com.

Pachyderm satisfies stringent data governance standards, helps companies get their ML and AI initiatives to market more quickly, and lowers the cost of data processing and storage. Review collected by and hosted on G2.com.

The drawback is that Pachyderm had a lot of commits. Using lineage and provenance reasoning was more challenging because every label modification resulted in a new data commit. Review collected by and hosted on G2.com.

I was trying to learn ML and then came across Pachyderm, its has a great and intuitive UI that helps to understand the various feature it offers including pipeline, version control, lineage, workflows, etc. Very neatly designed product for a good beginning of ML. Review collected by and hosted on G2.com.

Whatever I have explored so far is great but there were times I was trying to get support for some of the issues I faced. There is a community but wish I had some chat options to get instance support from the product engineers. That would have been a great option! Review collected by and hosted on G2.com.

The product provides a one-stop solution to manage model lineage and model versioning. This is one of the key ask for enterprises leveraging MLOps pipelines. The model pipeline is also one of a great feature that Pachyderm offers. Review collected by and hosted on G2.com.

The license aspect is something that needs to be looked into from a wider adoption point of view. It should also bring in features related to data catalog and enrich the observability for model performance and platform. I would also like to see the product being offered in marketplaces of major cloud providers for early and quick adoption to wider use base. Review collected by and hosted on G2.com.

To provide a meaningful platform to automate pipelines. Adapts on the change of data, cost effective, working on multiple language and platforms are some perks of pachyderm. Review collected by and hosted on G2.com.

Implementing is tough and can require skillset to properly use it.

However, it's good for data driven parameters, having a data at first is difficult, so, not good for a majority of projects. Review collected by and hosted on G2.com.

Pachyderm is disrupting (at least for our needs) approach on data management. For us, game changer was definitely auto trigger that allows for flexible adjustment based on data changes. Review collected by and hosted on G2.com.

We feel that the product is still in relatively young phase of development. There are definitely some of the features missing, especielly with more exotic languages, but I think that the product team know their staff and I'm sure (or hope) that backlog is being addressed Review collected by and hosted on G2.com.

Ability to keep branches of your data sets when you are testing new transformation pipelines.

Also, the use of native python support is just way too powerful and unique to this tool. Review collected by and hosted on G2.com.

Too much overhead in certain scenarios and overcomplicated for some infrastructures. And Since it's storage heavy for processing multiple versions of data, it is a big pain point from a financial perspective. Review collected by and hosted on G2.com.

Kubernetes powers Pachyderm which makes it efficient, highly scalable, portable and robust. It enables me to test my pipelines locally and scale them up to a large extent. Review collected by and hosted on G2.com.

In Pachyderm 1.x, there were frequent pipeline crashes which made it pretty hard to be used for developing research pipelines. Review collected by and hosted on G2.com.

Keeps data sets up to date and delivers versioning of the data Review collected by and hosted on G2.com.

Steep learning curve as there are core concepts that needs to understood before using it Review collected by and hosted on G2.com.