Datafold Pricing in 2026

FreemiumStarts at $29.00/mo

Visit Datafold

Free

$0forever
  • 1 user

Pro

$29/mo
  • Unlimited users
  • Priority support

Pricing information was last verified on March 11, 2026. Pricing may have changed. Visit Datafold for current pricing.

Pricing Overview

Datafold's pricing model is a freemium structure, offering a free tier and a paid Pro plan. This approach allows users to try out the tool without committing to a purchase, while also providing a clear upgrade path for those who need more features.

The core product is available at $0 cost to users.

Plan Comparison

FeatureFree TierPro
Number of Users1Unlimited
Data SourcesLimited to 5 sourcesUnlimited data sources
Data TransformationBasic transformation capabilitiesAdvanced transformation capabilities, including custom functions and workflows
Data Quality ChecksLimited quality checksComprehensive quality checks, including data validation and profiling
SupportCommunity support onlyPriority email support, plus access to documentation and knowledge base
Storage1 GB storageUnlimited storage
API AccessNo API accessFull API access for custom integrations

Hidden Costs and Considerations

While the pricing page provides a clear outline of what's included in each tier, there are some potential hidden costs and considerations to keep in mind:

  • If you need to support multiple users, the free tier will not be sufficient. Upgrading to Pro will add $29 per month for each additional user.
  • Data storage is unlimited on the Pro plan, but if your team generates a large amount of data, you may want to consider implementing data retention policies to avoid unnecessary storage costs.
  • The API access on the Pro plan is useful for custom integrations, but you'll need to have a good understanding of API development and security to take full advantage of this feature.

Cost Estimates by Team Size

To help estimate the monthly cost of Datafold, here are some rough estimates based on team size:

  • Solo user: $29 per month (Pro plan)
  • Small team (2-5 users): varies by usage per month (Pro plan for each additional user)
  • Medium-sized team (6-20 users): varies by usage per month (Pro plan for each additional user)
  • Large enterprise (21+ users): custom pricing, but expect to pay at least varies by usage per month

Keep in mind that these estimates are rough and may vary depending on your specific needs and usage.

How Datafold Pricing Compares

To give you a better understanding of how Datafold's pricing compares to other tools in the market, here's a brief comparison with three competitors:

  • Fivetran: Fivetran offers a freemium model similar to Datafold, but with more restrictive limits on the free tier. The Pro plan starts with varying pricing per month for 1-10 users.
  • Matillion: Matillion offers a pay-as-you-go pricing model, where you only pay for what you use. However, this can add up quickly, especially for large datasets.
  • Stitch: Stitch offers a flat monthly fee based on the number of sources and destinations. The pricing is more transparent than Datafold's, but may not be as flexible.

Keep in mind that these comparisons are simplified and don't take into account all the features and nuances of each tool. It's essential to evaluate each tool based on your specific needs and requirements.

Datafold Pricing FAQ

Is the free tier available for all users?

Yes, our free tier is available for individual users with up to 1 user. This plan includes limited features and data storage.

How much does it cost for teams to use Datafold?

For teams, we offer a Pro plan starting at $29/month per user. Discounts are available for larger teams and enterprises.

Are there any hidden costs or fees associated with using Datafold?

No, our pricing is transparent and straightforward. There are no hidden costs or fees beyond the monthly subscription fee.

Can I get a refund if I'm not satisfied with Datafold?

Yes, we offer a 30-day money-back guarantee. If you're not satisfied with our service, you can request a full refund within 30 days of signing up.

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