Software Alternatives, Accelerators & Startups

Codacy VS LakeFS

Compare Codacy VS LakeFS and see what are their differences

Note: These products don't have any matching categories. If you think this is a mistake, please edit the details of one of the products and suggest appropriate categories.

Codacy logo Codacy

Automatically reviews code style, security, duplication, complexity, and coverage on every change while tracking code quality throughout your sprints.

LakeFS logo LakeFS

lakeFS is an open-source tool that transforms your object storage to Git-like repositories. Start managing data the way you manage your code.
  • Codacy Landing page
    Landing page //
    2023-08-27

Codacy automates code reviews and monitors code quality on every commit and pull request reporting back the impact of every commit or pull request, issues concerning code style, best practices, security, and many others. It monitors changes in code coverage, code duplication and code complexity. Saving developers time in code reviews thus efficiently tackling technical debt. JavaScript, Java, Ruby, Scala, PHP, Python, CoffeeScript and CSS are currently supported. Codacy is static analysis without the hassle.

  • LakeFS Landing page
    Landing page //
    2023-08-27

Codacy

Website
codacy.com
$ Details
Release Date
2012 January
Startup details
Country
Portugal
State
Lisboa
City
Lisbon
Founder(s)
Jaime Jorge
Employees
1 - 9

LakeFS

Website
lakefs.io
Pricing URL
-
$ Details
-
Release Date
-

Codacy features and specs

  • Comprehensive Code Analysis
    Codacy offers a wide array of static code analysis tools that can help identify many types of issues such as code complexity, security vulnerabilities, and code duplication.
  • Supports Multiple Languages
    Codacy supports a wide variety of programming languages including Java, JavaScript, Python, Ruby, and more. This makes it suitable for polyglot development teams.
  • Integration with CI/CD Pipelines
    Codacy integrates seamlessly with popular Continuous Integration/Continuous Deployment (CI/CD) tools like Jenkins, CircleCI, and Travis CI, enabling automated code reviews as part of the development workflow.
  • Customizable Analysis
    It allows teams to set custom quality and code style thresholds, ensuring that the code analysis process is tailored to meet the specific requirements of the project.
  • Automated Pull Request Reviews
    Codacy can automatically review pull requests and report issues as comments, helping developers identify problems before merging code changes.
  • Dashboard and Reporting
    It provides an insightful dashboard that offers an overview of code quality metrics and trends over time. This helps in tracking progress and identifying areas that need improvement.

Possible disadvantages of Codacy

  • High Cost for Large Teams
    While Codacy offers a free tier, the pricing can become quite expensive for larger teams and organizations, which could be a limiting factor for widespread adoption.
  • Initial Configuration Complexity
    Setting up Codacy to match specific project requirements can be complex and time-consuming, requiring significant effort to configure all the necessary rules and integrations.
  • Occasional False Positives
    Some users have reported instances of false positives, where Codacy flags code that does not actually have any issues. This can lead to wasted time and potential confusion.
  • Performance Issues
    Codacy can sometimes slow down during code analysis, particularly for large projects, which can impact developer productivity.
  • Learning Curve
    For teams that are new to code analysis tools, there may be a learning curve involved in understanding and effectively utilizing Codacy's comprehensive feature set.

LakeFS features and specs

No features have been listed yet.

Codacy videos

Using Codacy for automated code reviews

More videos:

LakeFS videos

Getting Started With lakeFS

More videos:

  • Review - Get Ready for ML! Level Up Your Data Lake with Delta and lakeFS | Treeverse

Category Popularity

0-100% (relative to Codacy and LakeFS)
Code Coverage
100 100%
0% 0
Cloud Computing
0 0%
100% 100
Code Analysis
100 100%
0% 0
Cloud Storage
0 0%
100% 100

User comments

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Reviews

These are some of the external sources and on-site user reviews we've used to compare Codacy and LakeFS

Codacy Reviews

Top 11 SonarQube Alternatives in 2024
Each of these tools offers unique advantages that make them compelling alternatives to SonarQube, depending on organizational goals, budgets, and technology stacks. Codeant.ai and Codacy provide user-friendly experiences with robust integrations, while tools like Veracode, Checkmarx, and Snyk offer advanced security features. For organizations focused on testing, Code...
Source: www.codeant.ai
8 Best Static Code Analysis Tools For 2024
Codacy is a popular code analysis and quality tool that helps you deliver better software. It continuously reviews your code and monitors its quality from the beginning.
Source: www.qodo.ai
The 5 Best SonarQube Alternatives in 2024
Secondly, while SonarQube offers security analysis, Codacy provides a more holistic approach to security, including features like supply chain security and secret detection out of the box. Added to this are Codacyโ€™s actionable insights. Codacy's AI-suggested fixes and prioritized issue lists help teams act on the information provided rather than just presenting a list of...
Source: blog.codacy.com
Ten Best SonarQube alternatives in 2021
Codacy automates code opinions and monitors code quality on each sprint. The main issues it covers concern code style, best practices, and security. In addition, it monitors adjustments in code insurance, code duplication, and code complexity. She was saving developers time in code opinions, consequently successfully tackling technical debt. JavaScript, Java, Ruby, Scala,...
Source: duecode.io

LakeFS Reviews

4 Must-Have Open Source Solutions for Object Storage
LakeFS allows you to create a development environment where you can perform experiments and document them in a reproducible manner. Like Git, you can create commits and branches, making it possible for you to move along the timeline of your application development and try out new features in isolation. Amazingly, lakeFS performs all this without duplicating any data โ€”...

Social recommendations and mentions

Based on our record, LakeFS should be more popular than Codacy. It has been mentiond 6 times since March 2021. We are tracking product recommendations and mentions on various public social media platforms and blogs. They can help you identify which product is more popular and what people think of it.

Codacy mentions (4)

  • What is the best way to set a cookie (without setcookie?)
    I'm trying to use Codacy to review my code. One of the issues is regarding the use of the "setcookie" function. Source: over 4 years ago
  • Converting vstest coverage files in github actions?
    Does anyone have an example on how to get this conversion done on github actions where I can convert the *.coverage file into a *.xml file for uploading to codacy.com. Source: about 5 years ago
  • PHP Static Analysis Tools Review
    Online analysisFinally, if you want a simple way to analyze your code without having to manually configure everything locally, you can use an online code review service such as Codacy (shameless plug here). We already integrate some of the mentioned detection tools in this article and we are working every day to improve the service. The other main benefit of using automated code review tools is to allow you to... - Source: dev.to / over 5 years ago
  • Top 10 ways to perform fast code reviews
    Because you care and because you always want to be better, automation is a great way to optimize your review workflow process. Go ahead and do a quick search on Google for automated code reviews and see who better fits your workflow. You'll find Codacy on your Google search and we hope you like what we do. - Source: dev.to / over 5 years ago

LakeFS mentions (6)

  • Ask HN: AWS S3, Cloudflare R2, GCS, Wasabi, or B2?
    I would add https://github.com/gaul/s3proxy to your list. - Source: Hacker News / over 2 years ago
  • Dev / Stage / Prod is the wrong pattern for data pipelines
    * data state - this is contents of both your data and metadata at a given point in time. if your data doesn't fit into a single database, this can be difficult to manage. We use this technology to help us: https://lakefs.io/. - Source: Hacker News / almost 3 years ago
  • Dev / Stage / Prod is the wrong pattern for data pipelines
    Saltcured, find these comments super insightful! > Yeah, there's a lot of hidden magic/assumptions in having a "writable snapshot of a specific version" of production data. That's absolutely a huge assumption. This technology has been a game changer for us: https://lakefs.io/ > It becomes a headache when there is too much contention to use these sandboxes, or too much manual effort to reset them to a desired... - Source: Hacker News / almost 3 years ago
  • Using git to version control experimental data (not code)?
    You should not store your data in git itself, but rather use git to version your data sets. The currently best option for that is (IMHO) https://lakefs.io though there are a few others in various states of usability/maturity. Source: over 3 years ago
  • How are you incrementally testing your data pipelines as you develop them?
    I mean if you're ready to adopt a new framework into your ecosystem this is one of the major usecases for LakeFS. Source: over 3 years ago
View more

What are some alternatives?

When comparing Codacy and LakeFS, you can also consider the following products

SonarQube - SonarQube, a core component of the Sonar solution, is an open source, self-managed tool that systematically helps developers and organizations deliver Clean Code.

DVC - Diablo Valley College consists of two campuses serving more than 22,000 students in Contra Costa County each semester with a wide variety of program options.

CodeClimate - Code Climate provides automated code review for your apps, letting you fix quality and security issues before they hit production. We check every commit, branch and pull request for changes in quality and potential vulnerabilities.

Monte Carlo Data - Monte Carloโ€™s Data Observability platform increases trust in data by eliminating data downtime, so engineers innovate more and fix less.

CodeFactor.io - Automated Code Review for GitHub & BitBucket

Git Large File Storage - Git Large File Storage (LFS) replaces large files such as audio samples, videos, datasets, and graphics with text pointers.