Software development, individually and in a team, is a process fraught with uncertainties—it strongly obeys Murphy’s law, which states that if anything can go wrong, it will. Software development is great when everything works as expected. When it doesn’t, you’re going to wish you had contingencies and a very good insurance policy 😏.

Data versioning is a very convenient tool that enables developers and organizations to leverage and assess the evolution of code and other digital assets. For developers who commit frequently, data versioning is a lifesaver if one gets lost in the maze of software development.

That said, it’s important to acknowledge the top 7 data versioning tools out there that make software development much more manageable.

1. LakeFS

LakeFS is quickly gaining ground as a reliable open source data versioning tool that gets the job done. Enjoying endorsements from actual developers, you can be certain that you will find their data versioning tool pretty satisfactory. You don’t have to take my word for it. Simply imagine what makes 1,600 developers award a solution the coveted star on GitHub.

LakeFS boasts of features of Git, albeit with some added functionalities like exabytes scale version control that comes very handy in development.

2. Phabricator

Phabricator is on my list (despite being out of support) because they had users like Facebook, Twitter, Uber, etc., onboard despite the competition, which says a lot. However, I can’t rank them any higher because they’re out of support.

Phabricator has end-to-end solutions, making it a great tool for collaboration, version control, and internal chats. Their extra features aren’t as good as that of Slack. Phabricator itself has publicly pointed this out (it’s on their website 😂).

3. RhodeCode

RhodeCode has a lot going for itself—it prides itself on security. Organizations that want a more bespoke offering in terms of security should take RhodeCode seriously. They promise military-grade security, among other nice-to-have features like improved team collaboration features—all within one data versioning tool.

If you’re a Python person, it will interest you to know that RhodeCode is written in Python, and the Pylons framework is responsible for making the magic happen.

4. AWS CodeCommit

You may feel it should rank higher because it’s AWS (and Amazon), but most people don’t know about AWS CodeCommit. It’s built on the features and functionalities of Git, which means teams that are familiar with Git can easily leverage the best AWS CodeCommit has to offer.

One of the finest points about AWS CodeCommit is the fact that they promise a lot in terms of scalability, and it’s perfectly alright to expect that they integrate well with AWS and S3 buckets.

5. Azure DevOps

Like all things Microsoft-related, you can expect a robust, enterprise-level product that does more than you’ll ever know with Azure DevOps. It is built to handle everything from data versioning to other esoterics of the software development lifecycle. With featureslike pipelines and an enviable extensions library, you will be very satisfied with it.

Azure DevOps services very large organizations and has comprehensive documentation, and this justifies their position.

6. BitBucket 

Bitbucket is more like AzureDevOps than any other data versioning solution on my list. This is because they feature massive integrations that ensure they’re able to build an ecosystem around their customers by offering different services that key into the software development lifecycle.

They have Git features coupled with mercurial management features while boasting of a feature that tries to facilitate as many code reviews as possible with inline comments.

7. GitHub

It’s unfair that Microsoft gets to have two products on this list, but it goes to show their dominance. In terms of dominance, GitHub has earned its place in this list. While it’s not as robust as platforms like Azure DevOps or BitBucket, it’s arguably developers’ favorite data versioning tool.

GitHub is built for collaboration and has rapidly grown by adding new features.

Conclusion

At a point in time where data has become invaluable, and with the increased risks that come with managing and manipulating data, it is clear as day that data versioning is a must and not an option. The process of choosing a data versioning tool is one that requires careful thought (depending on use-case) as it’s sometimes an apples and oranges situation.

The metrics for deciding which is the right solution for you may vary depending on a number of factors—price, the predisposition of your team, and the long-term value proposition of the tool. Be that as it may, there exists a wide range of products to choose from, and this puts power where it should be, in the hands of the consumer.