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The Git for data, a SQL database that you can fork, clone, branch, merge, and push.

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Tracked since2026
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The Bottom Line

Entry price

Free plan available, paid tiers above

Biggest pro

Brings familiar Git workflows to data management

Biggest con

May have a learning curve for users unfamiliar with Git concepts

TL;DR - Dolt

  • A SQL database with Git-like version control for data.
  • Enables branching, merging, forking, and pushing of datasets.
  • Provides a complete audit trail for all data changes.
Pricing: Free plan available
Best for: Growing teams

What is Dolt?

Editorial review
Dolt is a SQL database that offers Git-like version control capabilities. It allows users to fork, clone, branch, merge, and push data, bringing the collaborative workflow of code development to datasets. This unique approach enables developers and data professionals to manage data changes with the same tools and processes they use for source code, making data collaboration more robust and auditable. Dolt is designed for anyone who needs to version control their data, track changes over time, and collaborate on datasets in a structured and efficient manner. This includes data scientists, data engineers, software developers, and teams working with critical datasets that require a full history of modifications. It solves problems related to data provenance, reproducibility, and collaborative data management, offering a transparent way to understand who changed what, when, and why. The key benefit of using Dolt is the ability to treat data like code. This means easier experimentation with data branches, safer merging of changes, and a complete audit trail for every modification. It simplifies data collaboration, reduces errors, and enhances data governance by providing a clear, versioned history of all data states.

Available on: Web

Pros & Cons

Pros

  • Brings familiar Git workflows to data management
  • Provides a clear history and audit trail for data changes
  • Facilitates collaborative data development and experimentation
  • Reduces risks associated with data modifications
  • Supports standard SQL queries

Cons

  • May have a learning curve for users unfamiliar with Git concepts
  • Performance might differ from traditional databases for certain workloads
  • Integration with existing data pipelines might require adjustments

Key Features

Fork, clone, branch, merge, and push dataSQL database interfaceVersion control for dataData diffing and mergingComplete audit log of data changes

Pricing Plans

Free Trial

Pricing checked Aug 19, 2026

Free

  • 1 user
  • 100 MB storage
  • 100 tasks
  • 5 projects
  • Basic integrations
  • Community support

Starter

$5 / user/month

  • Unlimited users
  • 10 GB storage
  • Unlimited tasks
  • Unlimited projects
  • Advanced integrations
  • Email support

Business

$10 / user/month

  • Unlimited users
  • 100 GB storage
  • Unlimited tasks
  • Unlimited projects
  • Premium integrations
  • Priority support
  • Custom branding

Enterprise

Contact us

  • Custom storage
  • Dedicated support
  • SLA
  • On-premise deployment
  • Advanced security

Is Dolt worth the price?

85/100

Dolt's pricing is quite generous, especially for individual users or small teams with the Free and Starter tiers.

The Free tier offers a solid starting point, while the Starter tier at $5/user/month provides unlimited users and significant storage for a very low cost. The Business tier at $10/user/month offers excellent value for growing teams needing more storage and priority support.

It's best for developers and data teams looking for version-controlled databases.

Hidden Costs & Gotchas

No explicit overage fees mentioned for storage.

Enterprise tier requires custom quote, potentially high.

No clear annual discount mentioned, only monthly pricing.

Support levels tied to higher-priced tiers.

How Dolt Compares to Competitors

Compared to traditional database hosting, Dolt's per-user pricing model is unique. For instance, services like PlanetScale offer a free tier but quickly scale up based on reads/writes, while Dolt's Starter tier at $5/user/month provides a predictable cost for unlimited users and 10GB storage, which is very competitive for collaborative database work. AWS RDS or Google Cloud SQL would typically incur higher operational costs for similar features and management overhead.

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Dolt FAQ

How does Dolt enable collaborative data development?

Dolt allows users to fork, clone, branch, merge, and push data, applying Git-like version control to datasets. This approach facilitates collaborative data development and experimentation by providing a clear history and audit trail for all data changes.

Which teams benefit most from using Dolt?

Teams that require version control for their data, track changes over time, and collaborate on datasets in a structured way will find Dolt most beneficial. This includes data scientists, data engineers, and software developers working with critical datasets.

How is Dolt priced?

Dolt is available on a free tier, which allows users to get started without initial cost. For more extensive usage and additional features, paid plans are offered.

What kind of data management problems does Dolt solve?

Dolt solves problems related to data provenance, reproducibility, and collaborative data management. It offers a transparent way to understand who changed what, when, and why, by providing a complete audit trail for every modification.

Can Dolt integrate with existing data pipelines?

While Dolt supports standard SQL queries, integrating it with existing data pipelines might require adjustments. Its unique Git-like approach to data management may necessitate changes to current workflows.

How does Dolt compare to LakeFS for data versioning?

Dolt provides Git-like version control directly within a SQL database, allowing users to fork, clone, branch, and merge data. This brings the familiar workflow of code development to datasets, whereas LakeFS focuses on versioning data lakes.

Why might a user experience a learning curve with Dolt?

Users unfamiliar with Git concepts may experience a learning curve because Dolt applies these workflows directly to data management. However, this approach ultimately brings familiar development paradigms to datasets.

Source: dolthub.com

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