GitLab vs Bitbucket: The Ultimate Comparison for Dev Teams (2025)

Picking the right home for your code is a huge deal for any software team. It’s not just about storing files; it’s the command center for how you collaborate, automate, and actually ship your product. While GitHub usually gets most of the attention, two other major players, GitLab and Bitbucket, offer very different but equally powerful ways to manage the development lifecycle. For professional teams, the best choice isn’t always the most obvious one.

Deciding between GitLab vs Bitbucket will shape your team’s entire workflow, productivity, and even your budget. GitLab goes all-in on being a single DevSecOps platform for everything. Bitbucket, meanwhile, knows its strength lies in being a key part of the tightly knit Atlassian ecosystem. This guide will walk you through the key differences in features, CI/CD, pricing, and integrations to help you figure out which platform is the right fit for your team in 2025.

What is GitLab?

Think of GitLab as the Swiss Army knife for your entire software development process. It’s a single, open-source platform built on a pretty straightforward idea: give teams one unified application for the whole lifecycle. It’s not just a place to host your Git repositories. It’s a complete toolkit designed to take you from planning and source code management all the way to CI/CD, monitoring, and security.

GitLab’s main goal is to get rid of the “toolchain tax”, that hidden headache of paying for, integrating, and maintaining a dozen different apps. It does this by building everything you need right into the platform. You get issue tracking, a seriously powerful CI/CD system, a container registry, security testing, and a lot more, all in one place. Whether you use their cloud-hosted version or manage it yourself, GitLab is for teams who are tired of gluing tools together and just want a single source of truth to get work done.

What is Bitbucket?

Bitbucket is Atlassian’s Git-based tool for code hosting and collaboration. While it nails all the core features you’d expect from a repository manager, its real superpower is its deep, native integration with the rest of the Atlassian family. It’s built to work perfectly with the tools many teams already use day-in and day-out, especially Jira, Confluence, and Trello.

At its core, Bitbucket is for professional teams who want their code management to feel like a natural extension of their project management. It has strong pull request and code review features, plus a built-in CI/CD service called Bitbucket Pipelines. Unlike GitLab’s one-stop-shop approach, Bitbucket positions itself as the best Git solution to use within a larger ecosystem of best-in-class tools. This makes it the go-to choice for the millions of teams already running on Atlassian products.

GitLab vs Bitbucket: A feature-by-feature breakdown

Both platforms handle the basics of source code management well, but they take different paths when it comes to everything else, from planning to deployment. Let’s get into the details.

Source code management and code review

Both GitLab and Bitbucket provide solid, enterprise-ready Git repositories. You’ll get all the essentials: pull requests (GitLab calls them "merge requests"), effective code review workflows, and fine-grained branch permissions to keep your code safe.

The user interface for code review really comes down to personal taste.

Both platforms also give you built-in wikis for each repository, which is handy for creating documentation right next to your code. The downside? These wikis can quickly turn into yet another information silo, cut off from other knowledge bases like Confluence or Google Docs, and disconnected from the places like Slack where your team actually talks.

Issue tracking and project management

This is where you can really see the two platforms go in completely different directions.

GitLab gives you a full-blown project management suite baked right in. Its issue tracker is part of the platform and comes with features like Kanban boards, milestones for tracking deadlines, multi-level epics for organizing big projects, and burndown charts. If you’re looking for a self-contained solution, GitLab provides a surprisingly robust project management system without you having to buy another tool.

Bitbucket does the opposite. Its strength isn’t its built-in issue tracker; it’s the seamless, two-way sync with Jira. Developers can create new branches straight from a Jira ticket, and every commit and pull request automatically links back to the right issue. This gives you amazing context and makes it easy to trace work, which is a huge plus for any team that lives in Jira.

The problem with either setup is that developers are still constantly switching contexts, jumping from their code to an issue tracker to a separate doc just to piece together the information they need. That constant hunt for answers is a quiet but massive drain on productivity.

Built-in CI/CD and DevOps workflows

Continuous Integration and Continuous Delivery (CI/CD) are non-negotiable for modern DevOps, and both platforms have powerful, built-in solutions.

GitLab CI/CD is often called out as one of its best features, and for good reason. It’s mature, flexible, and woven deeply into the platform. You configure everything with a single ".gitlab-ci.yml" file in your repository. With features like Auto DevOps that can automatically build, test, and deploy apps, an integrated container registry, and extensive security scanning, it’s a major reason why many teams go with GitLab.

Bitbucket Pipelines is Bitbucket’s CI/CD solution. It’s also configured with a YAML file ("bitbucket-pipelines.yml") and is known for being incredibly easy to get up and running for basic builds and deployments. It’s powerful and convenient, but it might not have as many bells and whistles out-of-the-box as GitLab’s offering. For really complex, large-scale pipelines, some teams might find it a bit limiting.

Even with these great built-in tools, the knowledge needed to use them gets scattered across complicated YAML files, internal wikis, and old Slack threads. This makes it tough for anyone to get a quick answer about a specific deployment or figure out why a build is failing.

GitLab vs Bitbucket: A complete pricing breakdown

Alright, let’s talk money. This is often where the GitLab vs Bitbucket decision gets real. Their pricing models reflect their different philosophies: GitLab costs more because it aims to be an all-in-one platform, while Bitbucket has a lower entry fee because it’s part of a larger ecosystem you likely already pay for.

GitLab pricing

GitLab’s per-user price is higher, but the argument is that it could replace several other tools you’re paying for, like project management software or standalone security scanners.

Plan	Price (per user/month, billed annually)	Key Features	Compute Minutes/mo
Free	$0	SCM & CI/CD, 5 users, 10 GiB storage	400
Premium	$29	Advanced CI/CD, release controls, priority support	10,000
Ultimate	Contact Sales for Pricing	Advanced security & compliance, vulnerability management, portfolio management	50,000

GitLab also sells AI add-ons like GitLab Duo Pro for an extra $19/user/month, which gives you AI-powered code suggestions, a chat feature, and more.

Bitbucket pricing

Bitbucket is much cheaper per user, which makes it a very appealing choice for teams already paying for other Atlassian tools like Jira and Confluence.

| Plan | Price (per user/month) | User Limit | Key Features | Build Minutes/mo | | :--- | :--- | :--- | :--- | | Free | $0 | Up to 5 users | Unlimited private repos, Jira integration | 50 | | Standard | $3.30 | Unlimited | Merge checks, 100 deployment environments | 2,500 | | Premium | $6.60 | Unlimited | IP allowlisting, required 2FA, deployment permissions | 3,500 |

Atlassian Intelligence features, like AI that generates pull request summaries, are already included in the Standard and Premium plans, giving you built-in AI help without an extra fee.

GitLab vs Bitbucket integrations: All-in-one vs. best-in-class ecosystem

The choice between GitLab and Bitbucket really comes down to a strategic decision about your tools. Do you want one platform that handles everything, or a collection of specialized tools that play nicely together?

The GitLab Approach (All-in-One): GitLab’s mission is to be the single place for your entire DevOps process. The big advantage here is simplicity; you aren’t managing integrations, user accounts, and separate bills for a bunch of different tools. The trade-off is that you’re pretty much locked into GitLab’s way of doing things. If you’re not a fan of its issue tracker or its security scanning is missing a feature you need, you don’t have an easy out.

The Bitbucket Approach (Ecosystem): Bitbucket is built to be the code repository piece of the Atlassian puzzle. Its real power shines when you pair it with Jira for planning and Confluence for documentation. This lets you use what many people consider to be the best tools for each specific job. The catch is that this can create a disjointed user experience and, more importantly, it spreads your team’s knowledge across different silos.

No matter which platform you choose, your team’s most important development knowledge will end up scattered, in a GitLab wiki, a Confluence space, technical specs in Google Docs, and hundreds of conversations in Slack or MS Teams. This fragmentation forces your developers into a constant scavenger hunt for information, breaking their focus and slowing everything down.

The challenge of scattered development knowledge

That constant searching across different apps is a silent killer of developer productivity. But instead of trying to cram all your information into one rigid tool, what if you could create a smart knowledge layer that just sits on top of everything you already use?

This is where an AI platform can completely change how your team works. Instead of digging through wikis, issue trackers, and chat logs, a developer can just ask an AI assistant a question and get an immediate, accurate answer pulled from all of your team’s collective knowledge.

A screenshot of the eesel AI Internal Chat answering a developer's question directly within Slack.

eesel AI does exactly that. It connects to all your different knowledge sources, Confluence, Google Docs, Notion, Slack, and more, to create a single, unified brain for your team. With eesel AI’s AI Internal Chat, you can give your development team an instant Q&A assistant right inside Slack or MS Teams. It’s trained securely on all your internal documentation, cutting down on interruptions and helping everyone from new hires to senior engineers find what they need to stay in their workflow.

GitLab vs Bitbucket: Which platform is right for your team?

Both GitLab and Bitbucket are excellent platforms, but they’re built for different teams with different priorities.

Choose GitLab if: You want a powerful, all-in-one DevOps platform with fantastic, built-in CI/CD. It’s perfect for teams that would rather have a single, unified tool for their entire workflow, and for those who value open-source or need a self-hosted option.

Choose Bitbucket if: Your team is already deep into the Atlassian ecosystem, especially Jira and Confluence. It’s a cost-effective, high-quality Git repository that offers unmatched integration with top-tier project management tools.

This video compares Bitbucket and GitLab to help you decide which version control repository is best for your team's needs.

At the end of the day, managing code is only half the battle. The real challenge is managing the knowledge that allows your team to build, ship, and innovate effectively.

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