Alternatives to Crashlytics logo

Alternatives to Crashlytics

Sentry, TestFairy, Bugsnag, Google Analytics, and Rollbar are the most popular alternatives and competitors to Crashlytics.
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What is Crashlytics and what are its top alternatives?

Instead of just showing you the stack trace, Crashlytics performs deep analysis of each and every thread. We de-prioritize lines that don't matter while highlighting the interesting ones. This makes reading stack traces easier, faster, and far more useful! Crashlytics' intelligent grouping can take 50,000 crashes, distill them down to 20 unique issues, and then tell you which 3 are the most important to fix.
Crashlytics is a tool in the Mobile Error Monitoring category of a tech stack.

Top Alternatives to Crashlytics

  • Sentry
    Sentry

    Sentry’s Application Monitoring platform helps developers see performance issues, fix errors faster, and optimize their code health. ...

  • TestFairy
    TestFairy

    When testing apps in the crowd, you never know what exactly was done, and what went wrong on the client side. TestFairy shows you a video of the exact test that was done, including CPU, memory, GPS, network and a lot more. ...

  • Bugsnag
    Bugsnag

    Bugsnag captures errors from your web, mobile and back-end applications, providing instant visibility into user impact. Diagnostic data and tools are included to help your team prioritize, debug and fix exceptions fast. ...

  • Google Analytics
    Google Analytics

    Google Analytics lets you measure your advertising ROI as well as track your Flash, video, and social networking sites and applications. ...

  • Rollbar
    Rollbar

    Rollbar is the leading continuous code improvement platform that proactively discovers, predicts, and remediates errors with real-time AI-assisted workflows. With Rollbar, developers continually improve their code and constantly innovate ra ...

  • TestFlight
    TestFlight

    With TestFlight, developers simply upload a build, and the testers can install it directly from their device, over the air. ...

  • New Relic
    New Relic

    The world’s best software and DevOps teams rely on New Relic to move faster, make better decisions and create best-in-class digital experiences. If you run software, you need to run New Relic. More than 50% of the Fortune 100 do too. ...

  • Fabric
    Fabric

    Fabric is a Python (2.5-2.7) library and command-line tool for streamlining the use of SSH for application deployment or systems administration tasks. It provides a basic suite of operations for executing local or remote shell commands (normally or via sudo) and uploading/downloading files, as well as auxiliary functionality such as prompting the running user for input, or aborting execution. ...

Crashlytics alternatives & related posts

Sentry logo

Sentry

14.1K
9.1K
863
See performance issues, fix errors faster, and optimize code health.
14.1K
9.1K
+ 1
863
PROS OF SENTRY
  • 237
    Consolidates similar errors and makes resolution easy
  • 121
    Email Notifications
  • 108
    Open source
  • 84
    Slack integration
  • 71
    Github integration
  • 49
    Easy
  • 44
    User-friendly interface
  • 28
    The most important tool we use in production
  • 18
    Hipchat integration
  • 17
    Heroku Integration
  • 15
    Good documentation
  • 14
    Free tier
  • 11
    Self-hosted
  • 9
    Easy setup
  • 7
    Realiable
  • 6
    Provides context, and great stack trace
  • 4
    Feedback form on error pages
  • 4
    Love it baby
  • 3
    Gitlab integration
  • 3
    Filter by custom tags
  • 3
    Super user friendly
  • 3
    Captures local variables at each frame in backtraces
  • 3
    Easy Integration
  • 1
    Performance measurements
CONS OF SENTRY
  • 12
    Confusing UI
  • 4
    Bundle size

related Sentry posts

Lucas Litton
Founder & CEO at Macombey · | 24 upvotes · 271.3K views

Sentry has been essential to our development approach. Nobody likes errors or apps that crash. We use Sentry heavily during Node.js and React development. Our developers are able to see error reports, crashes, user's browsers, and more, all in one place. Sentry also seamlessly integrates with Asana, Slack, and GitHub.

See more
Johnny Bell

For my portfolio websites and my personal OpenSource projects I had started exclusively using React and JavaScript so I needed a way to track any errors that we're happening for my users that I didn't uncover during my personal UAT.

I had narrowed it down to two tools LogRocket and Sentry (I also tried Bugsnag but it did not make the final two). Before I get into this I want to say that both of these tools are amazing and whichever you choose will suit your needs well.

I firstly decided to go with LogRocket the fact that they had a recorded screen capture of what the user was doing when the bug happened was amazing... I could go back and rewatch what the user did to replicate that error, this was fantastic. It was also very easy to setup and get going. They had options for React and Redux.js so you can track all your Redux.js actions. I had a fairly large Redux.js store, this was ended up being a issue, it killed the processing power on my machine, Chrome ended up using 2-4gb of ram, so I quickly disabled the Redux.js option.

After using LogRocket for a month or so I decided to switch to Sentry. I noticed that Sentry was openSorce and everyone was talking about Sentry so I thought I may as well give it a test drive. Setting it up was so easy, I had everything up and running within seconds. It also gives you the option to wrap an errorBoundry in React so get more specific errors. The simplicity of Sentry was a breath of fresh air, it allowed me find the bug that was shown to the user and fix that very simply. The UI for Sentry is beautiful and just really clean to look at, and their emails are also just perfect.

I have decided to stick with Sentry for the long run, I tested pretty much all the JS error loggers and I find Sentry the best.

See more
TestFairy logo

TestFairy

41
76
29
Painless Beta Testing
41
76
+ 1
29
PROS OF TESTFAIRY
  • 8
    Get video rec of the user on your app
  • 4
    Landing Page
  • 4
    Better design
  • 3
    JIRA Integration
  • 2
    Cross-platform
  • 2
    Supports Enterprise IPA's (TestFlight doesn't/didn't)
  • 2
    GitHub Integration
  • 1
    Application full Log information
  • 1
    In-App Feedback
  • 1
    Single Sign-On
  • 1
    App Distribution
CONS OF TESTFAIRY
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    related TestFairy posts

    Bugsnag logo

    Bugsnag

    1.1K
    618
    267
    Bugsnag provides production error monitoring and management for front-end, mobile and back-end applications
    1.1K
    618
    + 1
    267
    PROS OF BUGSNAG
    • 45
      Lots of 3rd party integrations
    • 42
      Really reliable
    • 37
      Includes a free plan
    • 25
      No usage or rate limits
    • 23
      Design
    • 21
      Slack integration
    • 21
      Responsive support
    • 19
      Free tier
    • 11
      Unlimited
    • 6
      No Rate
    • 5
      Email notifications
    • 3
      Great customer support
    • 3
      React Native
    • 3
      Integrates well with Laravel
    • 3
      Reliable, great UI and insights, used for all our apps
    CONS OF BUGSNAG
    • 2
      Error grouping doesn't always work
    • 2
      Bad billing model

    related Bugsnag posts

    Johnny Bell

    For my portfolio websites and my personal OpenSource projects I had started exclusively using React and JavaScript so I needed a way to track any errors that we're happening for my users that I didn't uncover during my personal UAT.

    I had narrowed it down to two tools LogRocket and Sentry (I also tried Bugsnag but it did not make the final two). Before I get into this I want to say that both of these tools are amazing and whichever you choose will suit your needs well.

    I firstly decided to go with LogRocket the fact that they had a recorded screen capture of what the user was doing when the bug happened was amazing... I could go back and rewatch what the user did to replicate that error, this was fantastic. It was also very easy to setup and get going. They had options for React and Redux.js so you can track all your Redux.js actions. I had a fairly large Redux.js store, this was ended up being a issue, it killed the processing power on my machine, Chrome ended up using 2-4gb of ram, so I quickly disabled the Redux.js option.

    After using LogRocket for a month or so I decided to switch to Sentry. I noticed that Sentry was openSorce and everyone was talking about Sentry so I thought I may as well give it a test drive. Setting it up was so easy, I had everything up and running within seconds. It also gives you the option to wrap an errorBoundry in React so get more specific errors. The simplicity of Sentry was a breath of fresh air, it allowed me find the bug that was shown to the user and fix that very simply. The UI for Sentry is beautiful and just really clean to look at, and their emails are also just perfect.

    I have decided to stick with Sentry for the long run, I tested pretty much all the JS error loggers and I find Sentry the best.

    See more
    Jason Barry
    Cofounder at FeaturePeek · | 7 upvotes · 165.7K views

    Segment has made it a no-brainer to integrate with third-party scripts and services, and has saved us from doing pointless redeploys just to change the It gives you the granularity to toggle services on different environments without having to make any code changes.

    It's also a great platform for discovering SaaS products that you could add to your own – just by browsing their catalog, I've discovered tools we now currently use to augment our main product. Here are a few:

    • Heap: We use Heap for our product analytics. Heap's philosophy is to gather events from multiple sources, and then organize and graph segments to form your own business insights. They have a few starter graphs like DAU and retention to help you get started.
    • Hotjar: If a picture's worth a thousand words, than a video is worth 1000 * 30fps = 30k words per second. Hotjar gives us videos of user sessions so we can pinpoint problems that aren't necessarily JS exceptions – say, logical errors in a UX flow – that we'd otherwise miss.
    • Bugsnag: Bugsnag has been a big help in catching run-time errors that our users encounter. Their Slack integration pings us when something goes wrong (which we can control if we want to notified on all bugs or just new bugs), and their source map uploader means that we don't have to debug minified code.
    See more
    Google Analytics logo

    Google Analytics

    126K
    48.4K
    5K
    Enterprise-class web analytics.
    126K
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    + 1
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    PROS OF GOOGLE ANALYTICS
    • 1.5K
      Free
    • 926
      Easy setup
    • 890
      Data visualization
    • 698
      Real-time stats
    • 405
      Comprehensive feature set
    • 181
      Goals tracking
    • 154
      Powerful funnel conversion reporting
    • 138
      Customizable reports
    • 83
      Custom events try
    • 53
      Elastic api
    • 14
      Updated regulary
    • 8
      Interactive Documentation
    • 3
      Google play
    • 2
      Industry Standard
    • 2
      Walkman music video playlist
    • 2
      Advanced ecommerce
    • 1
      Medium / Channel data split
    • 1
      Easy to integrate
    • 1
      Financial Management Challenges -2015h
    • 1
      Lifesaver
    • 1
      Irina
    CONS OF GOOGLE ANALYTICS
    • 11
      Confusing UX/UI
    • 8
      Super complex
    • 6
      Very hard to build out funnels
    • 4
      Poor web performance metrics
    • 3
      Very easy to confuse the user of the analytics
    • 2
      Time spent on page isn't accurate out of the box

    related Google Analytics posts

    Alex Step

    We used to use Google Analytics to get audience insights while running a startup and we are constantly doing experiments to lear our users. We are a small team and we have a lack of time to keep up with trends. Here is the list of problems we are experiencing: - Analytics takes too much time - We have enough time to regularly monitor analytics - Google Analytics interface is too advanced and complicated - It's difficult to detect anomalies and trends in GA

    We considered other solutions on a market, but found 2 main issues: - The solution created for analytic experts - The solution is pretty expensive and non-automated

    After learning this fact we decided to create AI-powered Slack bot to analyze Google Analytics and share trends. The bot is currently working and highlights trends for us.

    We are thinking about publishing this solution as a SaaS. If you are interested in automating Google Analytics analysis, drop a comment and you'll get an early access.

    We will implement this solution only if we have 20+ early adaptors. Leave a message with your thought. I appreciate any feedback.

    See more
    Tim Specht
    ‎Co-Founder and CTO at Dubsmash · | 14 upvotes · 948.5K views

    In order to accurately measure & track user behaviour on our platform we moved over quickly from the initial solution using Google Analytics to a custom-built one due to resource & pricing concerns we had.

    While this does sound complicated, it’s as easy as clients sending JSON blobs of events to Amazon Kinesis from where we use AWS Lambda & Amazon SQS to batch and process incoming events and then ingest them into Google BigQuery. Once events are stored in BigQuery (which usually only takes a second from the time the client sends the data until it’s available), we can use almost-standard-SQL to simply query for data while Google makes sure that, even with terabytes of data being scanned, query times stay in the range of seconds rather than hours. Before ingesting their data into the pipeline, our mobile clients are aggregating events internally and, once a certain threshold is reached or the app is going to the background, sending the events as a JSON blob into the stream.

    In the past we had workers running that continuously read from the stream and would validate and post-process the data and then enqueue them for other workers to write them to BigQuery. We went ahead and implemented the Lambda-based approach in such a way that Lambda functions would automatically be triggered for incoming records, pre-aggregate events, and write them back to SQS, from which we then read them, and persist the events to BigQuery. While this approach had a couple of bumps on the road, like re-triggering functions asynchronously to keep up with the stream and proper batch sizes, we finally managed to get it running in a reliable way and are very happy with this solution today.

    #ServerlessTaskProcessing #GeneralAnalytics #RealTimeDataProcessing #BigDataAsAService

    See more
    Rollbar logo

    Rollbar

    1.6K
    1.1K
    531
    Proactively discover, predict, and remediate errors.
    1.6K
    1.1K
    + 1
    531
    PROS OF ROLLBAR
    • 74
      Consolidates similar errors by impact
    • 64
      Centralize error management
    • 63
      Slack integration
    • 58
      Github integration
    • 47
      Usage based pricing
    • 32
      Insane customer support
    • 23
      Instant search
    • 21
      Heroku integration
    • 18
      Consolidate errors by OS
    • 15
      Great Free Plan
    • 15
      Trello integration
    • 13
      Flexible logging (not just exceptions)
    • 11
      Simple yet powerful error tracking tool
    • 9
      Multiple Language Support
    • 7
      Consolidate errors by browser
    • 6
      Easy setup
    • 6
      Query errors with RQL
    • 5
      Best rails exception handler
    • 5
      Deployment tracking is a nice free bonus
    • 5
      Awesome service
    • 5
      Simple and fast integration
    • 4
      Easy setup, friendly ui, demo, lots of integrations
    • 3
      Beat your users to the error report
    • 3
      Server-side + client-side
    • 3
      Errors Analysis
    • 3
      Clear and concise information.
    • 3
      Powerful
    • 2
      Mailgun integration
    • 2
      Easy integration with sails.js
    • 2
      Bitbucket integration
    • 1
      Clear errors on deploy or push
    • 1
      Easy Set up familiar UI that doesn't make you look dumb
    • 1
      Teams
    • 1
      Gitlab integration
    CONS OF ROLLBAR
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      related Rollbar posts

      Robert Zuber

      Our primary source of monitoring and alerting is Datadog. We’ve got prebuilt dashboards for every scenario and integration with PagerDuty to manage routing any alerts. We’ve definitely scaled past the point where managing dashboards is easy, but we haven’t had time to invest in using features like Anomaly Detection. We’ve started using Honeycomb for some targeted debugging of complex production issues and we are liking what we’ve seen. We capture any unhandled exceptions with Rollbar and, if we realize one will keep happening, we quickly convert the metrics to point back to Datadog, to keep Rollbar as clean as possible.

      We use Segment to consolidate all of our trackers, the most important of which goes to Amplitude to analyze user patterns. However, if we need a more consolidated view, we push all of our data to our own data warehouse running PostgreSQL; this is available for analytics and dashboard creation through Looker.

      See more
      Kirill Shirinkin
      Cloud and DevOps Consultant at mkdev · | 12 upvotes · 681K views

      As a small startup we are very conscious about picking up the tools we use to run the project. After suffering with a mess of using at the same time Trello , Slack , Telegram and what not, we arrived at a small set of tools that cover all our current needs. For product management, file sharing, team communication etc we chose Basecamp and couldn't be more happy about it. For Customer Support and Sales Intercom works amazingly well. We are using MailChimp for email marketing since over 4 years and it still covers all our needs. Then on payment side combination of Stripe and Octobat helps us to process all the payments and generate compliant invoices. On techie side we use Rollbar and GitLab (for both code and CI). For corporate email we picked G Suite. That all costs us in total around 300$ a month, which is quite okay.

      See more
      TestFlight logo

      TestFlight

      1.1K
      701
      163
      iOS beta testing on the fly.
      1.1K
      701
      + 1
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      PROS OF TESTFLIGHT
      • 62
        Must have for ios development
      • 49
        Beta testing
      • 20
        Easy setup
      • 10
        Easy way to push out updates for internal testers
      • 7
        In-App Updates
      • 5
        Crash Logging
      • 4
        Checkpoints
      • 3
        Multiple platforms
      • 2
        Remote Logging
      • 1
        Sessions
      CONS OF TESTFLIGHT
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        Utkarsh Mehta
        Senior Blockchain Developer · | 1 upvote · 4.8K views

        I created microservices with Kafka for message queue, Meteor for app development with JavaScript & TestFlight for iOS app development, Elasticsearch for logging SendGrid for automated mails. Git & GitHub for SCM.

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        New Relic logo

        New Relic

        20.7K
        8.5K
        1.9K
        New Relic is the industry’s largest and most comprehensive cloud-based observability platform.
        20.7K
        8.5K
        + 1
        1.9K
        PROS OF NEW RELIC
        • 415
          Easy setup
        • 344
          Really powerful
        • 244
          Awesome visualization
        • 194
          Ease of use
        • 151
          Great ui
        • 107
          Free tier
        • 80
          Great tool for insights
        • 66
          Heroku Integration
        • 55
          Market leader
        • 49
          Peace of mind
        • 21
          Push notifications
        • 20
          Email notifications
        • 17
          Heroku Add-on
        • 16
          Error Detection and Alerting
        • 13
          Multiple language support
        • 11
          Server Resources Monitoring
        • 11
          SQL Analysis
        • 9
          Transaction Tracing
        • 8
          Azure Add-on
        • 8
          Apdex Scores
        • 7
          Detailed reports
        • 7
          Analysis of CPU, Disk, Memory, and Network
        • 6
          Application Response Times
        • 6
          Performance of External Services
        • 6
          Application Availability Monitoring and Alerting
        • 6
          Error Analysis
        • 5
          JVM Performance Analyzer (Java)
        • 5
          Most Time Consuming Transactions
        • 4
          Top Database Operations
        • 4
          Easy to use
        • 4
          Browser Transaction Tracing
        • 3
          Application Map
        • 3
          Weekly Performance Email
        • 3
          Custom Dashboards
        • 3
          Pagoda Box integration
        • 2
          App Speed Index
        • 2
          Easy to setup
        • 2
          Background Jobs Transaction Analysis
        • 1
          Time Comparisons
        • 1
          Access to Performance Data API
        • 1
          Super Expensive
        • 1
          Team Collaboration Tools
        • 1
          Metric Data Retention
        • 1
          Metric Data Resolution
        • 1
          Worst Transactions by User Dissatisfaction
        • 1
          Real User Monitoring Overview
        • 1
          Real User Monitoring Analysis and Breakdown
        • 1
          Free
        • 1
          Best of the best, what more can you ask for
        • 1
          Best monitoring on the market
        • 1
          Rails integration
        • 1
          Incident Detection and Alerting
        • 0
          Cost
        • 0
          Exceptions
        • 0
          Price
        • 0
          Proce
        CONS OF NEW RELIC
        • 20
          Pricing model doesn't suit microservices
        • 10
          UI isn't great
        • 7
          Expensive
        • 7
          Visualizations aren't very helpful
        • 5
          Hard to understand why things in your app are breaking

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        Cooper Marcus
        Director of Ecosystem at Kong Inc. · | 17 upvotes · 110.6K views
        Shared insights
        on
        New RelicNew RelicGitHubGitHubZapierZapier
        at

        I've used more and more of New Relic Insights here in my work at Kong. New Relic Insights is a "time series event database as a service" with a super-easy API for inserting custom events, and a flexible query language for building visualization widgets and dashboards.

        I'm a big fan of New Relic Insights when I have data I know I need to analyze, but perhaps I'm not exactly sure how I want to analyze it in the future. For example, at Kong we recently wanted to get some understanding of our open source community's activity on our GitHub repos. I was able to quickly configure GitHub to send webhooks to Zapier , which in turn posted the JSON to New Relic Insights.

        Insights is schema-less and configuration-less - just start posting JSON key value pairs, then start querying your data.

        Within minutes, data was flowing from GitHub to Insights, and I was building widgets on my Insights dashboard to help my colleagues visualize the activity of our open source community.

        #GitHubAnalytics #OpenSourceCommunityAnalytics #CommunityAnalytics #RepoAnalytics

        See more
        Julien DeFrance
        Principal Software Engineer at Tophatter · | 16 upvotes · 3.1M views

        Back in 2014, I was given an opportunity to re-architect SmartZip Analytics platform, and flagship product: SmartTargeting. This is a SaaS software helping real estate professionals keeping up with their prospects and leads in a given neighborhood/territory, finding out (thanks to predictive analytics) who's the most likely to list/sell their home, and running cross-channel marketing automation against them: direct mail, online ads, email... The company also does provide Data APIs to Enterprise customers.

        I had inherited years and years of technical debt and I knew things had to change radically. The first enabler to this was to make use of the cloud and go with AWS, so we would stop re-inventing the wheel, and build around managed/scalable services.

        For the SaaS product, we kept on working with Rails as this was what my team had the most knowledge in. We've however broken up the monolith and decoupled the front-end application from the backend thanks to the use of Rails API so we'd get independently scalable micro-services from now on.

        Our various applications could now be deployed using AWS Elastic Beanstalk so we wouldn't waste any more efforts writing time-consuming Capistrano deployment scripts for instance. Combined with Docker so our application would run within its own container, independently from the underlying host configuration.

        Storage-wise, we went with Amazon S3 and ditched any pre-existing local or network storage people used to deal with in our legacy systems. On the database side: Amazon RDS / MySQL initially. Ultimately migrated to Amazon RDS for Aurora / MySQL when it got released. Once again, here you need a managed service your cloud provider handles for you.

        Future improvements / technology decisions included:

        Caching: Amazon ElastiCache / Memcached CDN: Amazon CloudFront Systems Integration: Segment / Zapier Data-warehousing: Amazon Redshift BI: Amazon Quicksight / Superset Search: Elasticsearch / Amazon Elasticsearch Service / Algolia Monitoring: New Relic

        As our usage grows, patterns changed, and/or our business needs evolved, my role as Engineering Manager then Director of Engineering was also to ensure my team kept on learning and innovating, while delivering on business value.

        One of these innovations was to get ourselves into Serverless : Adopting AWS Lambda was a big step forward. At the time, only available for Node.js (Not Ruby ) but a great way to handle cost efficiency, unpredictable traffic, sudden bursts of traffic... Ultimately you want the whole chain of services involved in a call to be serverless, and that's when we've started leveraging Amazon DynamoDB on these projects so they'd be fully scalable.

        See more
        Fabric logo

        Fabric

        452
        306
        75
        Simple, Pythonic remote execution and deployment
        452
        306
        + 1
        75
        PROS OF FABRIC
        • 23
          Python
        • 21
          Simple
        • 5
          Low learning curve, from bash script to Python power
        • 5
          Installation feedback for Twitter App Cards
        • 3
          Easy on maintainance
        • 3
          Single config file
        • 3
          Installation? pip install fabric... Boom
        • 3
          Easy to add any type of job
        • 3
          Agentless
        • 2
          Easily automate any set system automation
        • 1
          Flexible
        • 1
          Crash Analytics
        • 1
          Backward compatibility
        • 1
          Remote sudo execution
        CONS OF FABRIC
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          related Fabric posts