| Product | Ideal for | Price from | Free version | |
|---|---|---|---|---|
| Review inside GitHub | Free | Yes | Visit | |
| Review inside GitLab | Free | Yes | Visit | |
| Review inside Atlassian | Free | Yes | Visit | |
| Patch-based review for large teams | Free | Yes | Visit | |
| Standalone review tool | Free | Yes | Visit | |
| Atlassian code review | See website | Free trial | Visit | |
| AI code review on pull requests | Free | Yes | Visit | |
| Stacked pull requests for speed | See website | Free trial | Visit |
We compared code review tools on pull request workflows, AI assistance, integrations, async collaboration and pricing. Distributed teams need reviews that work across time zones, so async features matter more than real-time ones. Our pick for most teams is GitHub for its ecosystem, with CodeRabbit as the AI layer on top.

Ideal for: Review inside GitHub

GitHub pull requests offer code review inside the platform most teams already use, with reviewers, code owners, suggested changes and Actions integrations. That integration is why teams default to it. Advanced code security and review features need paid plans, and review depth depends on team discipline as much as tooling.
For most readers, the deciding question with GitHub Pull Requests is fit rather than raw feature count. Check the plan limits that matter to you, such as seats, usage caps and what happens when a trial ends, before you commit to a paid tier. If the free tier or trial covers your core task, use it for a full week of real work before paying, and keep an eye on renewal terms and cancellation steps. That short test usually tells you more than any feature list, and it keeps the choice grounded in how you actually work day to day.

Ideal for: Review inside GitLab

GitLab merge requests provide review with approval rules, suggested changes and CI integration inside a full DevOps platform. That breadth suits teams wanting code, CI and review in one place. Self-hosting adds effort, and the interface feels dense to newcomers, but the workflow is coherent.
For most readers, the deciding question with GitLab Merge Requests is fit rather than raw feature count. Check the plan limits that matter to you, such as seats, usage caps and what happens when a trial ends, before you commit to a paid tier. If the free tier or trial covers your core task, use it for a full week of real work before paying, and keep an eye on renewal terms and cancellation steps. That short test usually tells you more than any feature list, and it keeps the choice grounded in how you actually work day to day.

Ideal for: Review inside Atlassian

Bitbucket pull requests offer review with Jira integrations and branch permissions, suiting Atlassian teams. That integration ties code changes to tickets cleanly. The ecosystem is smaller than GitHub, and some features need paid plans, so GitHub-first teams gain little by switching.
For most readers, the deciding question with Bitbucket Pull Requests is fit rather than raw feature count. Check the plan limits that matter to you, such as seats, usage caps and what happens when a trial ends, before you commit to a paid tier. If the free tier or trial covers your core task, use it for a full week of real work before paying, and keep an eye on renewal terms and cancellation steps. That short test usually tells you more than any feature list, and it keeps the choice grounded in how you actually work day to day.

Ideal for: Patch-based review for large teams
Gerrit offers patch-based code review with strong access controls, used by large open-source and enterprise projects. That model suits teams needing fine-grained review control at scale. The learning curve is real and the interface feels dated, so smaller teams usually prefer GitHub or GitLab.
For most readers, the deciding question with Gerrit Code Review is fit rather than raw feature count. Check the plan limits that matter to you, such as seats, usage caps and what happens when a trial ends, before you commit to a paid tier. If the free tier or trial covers your core task, use it for a full week of real work before paying, and keep an eye on renewal terms and cancellation steps. That short test usually tells you more than any feature list, and it keeps the choice grounded in how you actually work day to day.

Ideal for: Standalone review tool
Review Board provides standalone code review for pre- and post-commit workflows, with integrations across version control systems. That independence suits teams not standardised on one host. The interface is older and setup takes effort, but the review workflow itself is solid.
For most readers, the deciding question with Review Board is fit rather than raw feature count. Check the plan limits that matter to you, such as seats, usage caps and what happens when a trial ends, before you commit to a paid tier. If the free tier or trial covers your core task, use it for a full week of real work before paying, and keep an eye on renewal terms and cancellation steps. That short test usually tells you more than any feature list, and it keeps the choice grounded in how you actually work day to day.

Ideal for: Atlassian code review
Crucible from Atlassian offers formal code reviews with Jira integration and reporting, suited to teams wanting structured review records. It is an older product in the Atlassian line, and the ecosystem focus means non-Atlassian teams gain less, so check current support status before adopting.
For most readers, the deciding question with Crucible is fit rather than raw feature count. Check the plan limits that matter to you, such as seats, usage caps and what happens when a trial ends, before you commit to a paid tier. If the free tier or trial covers your core task, use it for a full week of real work before paying, and keep an eye on renewal terms and cancellation steps. That short test usually tells you more than any feature list, and it keeps the choice grounded in how you actually work day to day.

Ideal for: AI code review on pull requests
CodeRabbit adds AI review to pull requests, summarising changes, suggesting improvements and learning from reviewer feedback. That AI layer speeds async review, especially for large diffs. Suggestions still need human review, since AI can miss context, and pricing scales with use.
For most readers, the deciding question with CodeRabbit is fit rather than raw feature count. Check the plan limits that matter to you, such as seats, usage caps and what happens when a trial ends, before you commit to a paid tier. If the free tier or trial covers your core task, use it for a full week of real work before paying, and keep an eye on renewal terms and cancellation steps. That short test usually tells you more than any feature list, and it keeps the choice grounded in how you actually work day to day.

Ideal for: Stacked pull requests for speed
Graphite speeds async review with stacked pull requests, letting developers split large changes into small, reviewable pieces. The review inbox and analytics help distributed teams keep reviews moving. It works best for GitHub teams, and stacking takes learning, but the speed gain for large features is real.
For most readers, the deciding question with Graphite is fit rather than raw feature count. Check the plan limits that matter to you, such as seats, usage caps and what happens when a trial ends, before you commit to a paid tier. If the free tier or trial covers your core task, use it for a full week of real work before paying, and keep an eye on renewal terms and cancellation steps. That short test usually tells you more than any feature list, and it keeps the choice grounded in how you actually work day to day.
We compared official feature pages, pricing pages, app store listings, privacy policies and public reviews for each option below. We kept only products that exist and work now, that fit the topic directly, and whose official homepage we could confirm. Where a price was not published clearly, we wrote See website rather than guessing, and we favoured options with a free tier or trial where one exists.
Keep pull requests small. A 200-line change gets thoughtful review, while a 2,000-line change gets a rubber stamp. Split work into stacked or sequential PRs, and describe what changed and why in the description.
Give reviewers context up front. Link the ticket, explain the approach, note risky areas and say what kind of feedback you want. Distributed reviewers cannot tap you on the shoulder, so the PR description does the talking.
Set review expectations explicitly. Agree on response times across time zones, who must approve, and when AI suggestions count as sufficient. Clear expectations prevent reviews stalling while authors wait for someone in another time zone.
GitHub and GitLab suit teams hosting code there, CodeRabbit adds AI review, and Graphite suits stacked PR workflows. The best pick depends on your host and review style.
AI tools such as CodeRabbit summarise pull requests, flag potential issues and suggest improvements. Human reviewers still make final decisions, since AI can miss business context and introduce false positives.
Stacked pull requests split a large change into small, dependent PRs reviewed in order. That approach speeds async review and makes feedback more precise, and Graphite specialises in it.
GitHub, GitLab, Bitbucket, Gerrit and Review Board offer free tiers, while AI tools such as CodeRabbit offer free tiers with paid plans for teams. Check limits for private repositories and team size.
Use small PRs, clear descriptions, agreed response times and async-friendly tools. AI summaries help, but human review, context and consistent standards matter most.