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Tools/DVC vs ZenML
DVC

DVC

mlops
vs
ZenML

ZenML

mlops

DVC vs ZenML — Comparison

Overview
What each tool does and who it's for

DVC

Open-source version control system for Data Science and Machine Learning projects. Git-like experience to organize your data, models, and experiments.

We’re thrilled to welcome the DVC Community to the lakeFS family. Keep updated on blog posts with our RSS Feed! We use cookies to improve your experience and understand how our site is used. Learn more in our Privacy Policy We provide short articles on common data science scenarios where DVC can help. Our example scenarios are not written to be run end-to-end like tutorials. For more hands-on experience with DVC, see Get Started. Even with all the success we've seen in machine learning, especially with deep learning and its applications in business, data scientists still lack best practices for organizing their projects and collaborating effectively. This is a critical challenge: while ML algorithms and methods are no longer tribal knowledge, they are still difficult to develop, reuse, and manage. If you store and process data files or datasets to produce other data or machine learning models, and you want to Choose a page from the navigation sidebar to the left. ✅ Check out our GitHub repositories: DVC give us a ⭐ if you like the project! We use cookies to improve your experience and understand how our site is used. Learn more in our Privacy Policy

ZenML

One layer for orchestration, versioning, and governance — from training pipelines to agent evals, local to Kubernetes.

Stop writing fragile scripts to connect your tools. ZenML provides a standardized protocol to bind your data retrieval (LlamaIndex), reasoning (LangChain), and training (PyTorch) steps into a single, cohesive system. Teams lose velocity rewriting notebook code for the cloud. ZenML allows the exact same @step to run locally for debugging, in batch for massive evaluations, and then deploy seamlessly to your production serving infrastructure. Your current orchestrator runs the job, but it doesn't track the data. ZenML adds a metadata layer to tools like Airflow or Kubeflow, giving you the artifact lineage and reproducibility that raw orchestrators lack. Built on Apache 2.0 for flexibility, hardened for the enterprise. Deploy ZenML inside your own VPC. Keep full sovereignty over your data, models, and API secrets while meeting SOC2 and ISO 27001 standards. Join thousands of teams using ZenML to eliminate chaos and accelerate AI delivery 60+ integrations across the AI ecosystem. From sklearn to LangGraph. We have put down our expertise around building production-ready, scalable AI platforms, building on insights from our top customers. Learn how teams are using ZenML to save time and simplify their MLOps. ZenML tracks production AI deployments across the industry Former Chief Scientist Salesforce and Founder of You.com ML Engineer / ML Ops / ML Solution architect at ADEO Services Professor of Linguistics and CS at Stanford Machine Learning Engineer at WiseTech Global Stay updated on the latest developments, announcements, and updates from the ZenML ecosystem. ZenML is a metadata layer on top of your existing infrastructure, meaning all data and compute stays on your side. ZenML is SOC2 and ISO 27001 compliant, validating our adherence to industry-leading standards for data security, availability, and confidentiality in our ongoing commitment to protecting your ML workflows and data. Subscribe to the ZenML newsletter and receive regular product updates, tutorials, examples, and more. Thanks for subscribing! Check your inbox to confirm. We care about your data in our privacy policy. Everything you need to know about the product. Predictable, transparent pricing that scales with value. Apply for a special price to access ZenML Pro features for early-stage companies building ML-powered products, universities, research institutions, and educational use cases. ZenML is a metadata layer on top of your existing infrastructure, meaning all data and compute stays on your side. ZenML is SOC2 and ISO 27001 Compliant ZenML is SOC2 and ISO 27001 compliant, validating our adherence to industry-leading standards for data security, availability, and confidentiality in our ongoing commitment to protecting your ML workflows and data. Everything you need to know about the product. Join the ZenML Community and start improving your MLOps stacks registered last 12 months ZenML offers the capability to build end-to-end ML workflows t

Key Metrics
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Avg Rating
—
0
Mentions (30d)
0
15,488
GitHub Stars
—
1,288
GitHub Forks
—
—
npm Downloads/wk
—
—
PyPI Downloads/mo
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Community Sentiment
How developers feel about each tool based on mentions and reviews

DVC

0% positive100% neutral0% negative

ZenML

0% positive100% neutral0% negative
Pricing

DVC

tiered

ZenML

subscription + contract + tiered

Pricing found: $399 /month, $999 /month, $2,499 /month, $399/mo, $999/mo

Features

Only in DVC (4)

track and save data and machine learning models the same way you capture code;understand how datasets and ML artifacts were built in the first place;adopt engineering tools and best practices in data science projects;Subscribe for updates. We won't spam you.

Only in ZenML (8)

Iterate at warp speedLimitless scalingAuto-track everythingBackend flexibility, zero lock-inShared ML building blocksStreamline cloud expensesSecurity guardrails, alwaysStart deploying reproducible AI workflows today
Developer Ecosystem
131
GitHub Repos
—
952
GitHub Followers
—
20
npm Packages
20
21
HuggingFace Models
—
—
SO Reputation
—
Product Screenshots

DVC

DVC screenshot 1

ZenML

ZenML screenshot 1ZenML screenshot 2ZenML screenshot 3ZenML screenshot 4
Company Intel
—
Industry
information technology & services
—
Employees
18
—
Funding
$6.4M
—
Stage
Seed
Supported Languages & Categories

DVC

DevOpsDeveloper Tools

ZenML

AI/MLDevOpsSecuritySaaSDeveloper Tools
View DVC Profile View ZenML Profile