What is Countly and what are its top alternatives?
Top Alternatives to Countly
- Apex
Apex is a small tool for deploying and managing AWS Lambda functions. With shims for languages not yet supported by Lambda, you can use Golang out of the box. ...
- Matomo
It is a web analytics platform designed to give you the conclusive insights with our complete range of features. You can also evaluate the full user-experience of your visitor’s behaviour with its Conversion Optimization features, including Heatmaps, Sessions Recordings, Funnels, Goals, Form Analytics and A/B Testing. ...
- Mixpanel
Mixpanel helps companies build better products through data. With our powerful, self-serve product analytics solution, teams can easily analyze how and why people engage, convert, and retain to improve their user experience. ...
- Google Analytics
Google Analytics lets you measure your advertising ROI as well as track your Flash, video, and social networking sites and applications. ...
- Piwik
Matomo (formerly Piwik) is a full-featured PHP MySQL software program that you download and install on your own webserver. At the end of the five-minute installation process, you will be given a JavaScript code. ...
- Firebase
Firebase is a cloud service designed to power real-time, collaborative applications. Simply add the Firebase library to your application to gain access to a shared data structure; any changes you make to that data are automatically synchronized with the Firebase cloud and with other clients within milliseconds. ...
- Heap
Heap automatically captures every user action in your app and lets you measure it all. Clicks, taps, swipes, form submissions, page views, and more. Track events and segment users instantly. No pushing code. No waiting for data to trickle in. ...
- Sentry
Sentry’s Application Monitoring platform helps developers see performance issues, fix errors faster, and optimize their code health. ...
Countly alternatives & related posts
related Apex posts
- Updated regulary1
- Goals tracking1
- Self-hosted1
- Open Source1
- Full data control1
- Free1
related Matomo posts
Mixpanel
- Great visualization ui144
- Easy integration108
- Great funnel funcionality78
- Free58
- A wide range of tools22
- Powerful Graph Search15
- Responsive Customer Support11
- Nice reporting2
- Messaging (notification, email) features are weak2
- Paid plans can get expensive2
- Limited dashboard capabilities1
related Mixpanel posts
Functionally, Amplitude and Mixpanel are incredibly similar. They both offer almost all the same functionality around tracking and visualizing user actions for analytics. You can track A/B test results in both. We ended up going with Amplitude at BaseDash because it has a more generous free tier for our uses (10 million actions per month, versus Mixpanel's 1000 monthly tracked users).
Segment isn't meant to compete with these tools, but instead acts as an API to send actions to them, and other analytics tools. If you're just sending event data to one of these tools, you probably don't need Segment. If you're using other analytics tools like Google Analytics and FullStory, Segment makes it easy to send events to all your tools at once.
Hi there, we are a seed-stage startup in the personal development space. I am looking at building the marketing stack tool to have an accurate view of the user experience from acquisition through to adoption and retention for our upcoming React Native Mobile app. We qualify for the startup program of Segment and Mixpanel, which seems like a good option to get rolling and scale for free to learn how our current 60K free members will interact in the new subscription-based platform. I was considering AppsFlyer for attribution, and I am now looking at an affordable yet scalable Mobile Marketing tool vs. building in-house. Braze looks great, so does Leanplum, but the price points are 30K to start, which we can't do. I looked at OneSignal, but it doesn't have user flow visualization. I am now looking into Urban Airship and Iterable. Any advice would be much appreciated!
- Free1.5K
- Easy setup926
- Data visualization890
- Real-time stats698
- Comprehensive feature set405
- Goals tracking181
- Powerful funnel conversion reporting154
- Customizable reports138
- Custom events try83
- Elastic api53
- Updated regulary14
- Interactive Documentation8
- Google play3
- Industry Standard2
- Walkman music video playlist2
- Advanced ecommerce2
- Medium / Channel data split1
- Easy to integrate1
- Financial Management Challenges -2015h1
- Lifesaver1
- Irina1
- Confusing UX/UI11
- Super complex8
- Very hard to build out funnels6
- Poor web performance metrics4
- Very easy to confuse the user of the analytics3
- Time spent on page isn't accurate out of the box2
related Google Analytics posts
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.
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
- It's good to have an alternative to google analytics35
- Self-hosted27
- Easy setup10
- Not blocked by Brave2
- Great customs0
- Hard to export data2
related Piwik posts
- Realtime backend made easy371
- Fast and responsive270
- Easy setup242
- Real-time215
- JSON191
- Free134
- Backed by google128
- Angular adaptor83
- Reliable68
- Great customer support36
- Great documentation32
- Real-time synchronization25
- Mobile friendly21
- Rapid prototyping18
- Great security14
- Automatic scaling12
- Freakingly awesome11
- Chat8
- Angularfire is an amazing addition!8
- Super fast development8
- Built in user auth/oauth6
- Firebase hosting6
- Ios adaptor6
- Awesome next-gen backend6
- Speed of light4
- Very easy to use4
- Great3
- It's made development super fast3
- Brilliant for startups3
- Free hosting2
- Cloud functions2
- JS Offline and Sync suport2
- Low battery consumption2
- .net2
- The concurrent updates create a great experience2
- Push notification2
- I can quickly create static web apps with no backend2
- Great all-round functionality2
- Free authentication solution2
- Easy Reactjs integration1
- Google's support1
- Free SSL1
- CDN & cache out of the box1
- Easy to use1
- Large1
- Faster workflow1
- Serverless1
- Good Free Limits1
- Simple and easy1
- Can become expensive31
- No open source, you depend on external company16
- Scalability is not infinite15
- Not Flexible Enough9
- Cant filter queries7
- Very unstable server3
- No Relational Data3
- Too many errors2
- No offline sync2
related Firebase posts
I was building a personal project that I needed to store items in a real time database. I am more comfortable with my Frontend skills than my backend so I didn't want to spend time building out anything in Ruby or Go.
I stumbled on Firebase by #Google, and it was really all I needed. It had realtime data, an area for storing file uploads and best of all for the amount of data I needed it was free!
I built out my application using tools I was familiar with, React for the framework, Redux.js to manage my state across components, and styled-components for the styling.
Now as this was a project I was just working on in my free time for fun I didn't really want to pay for hosting. I did some research and I found Netlify. I had actually seen them at #ReactRally the year before and deployed a Gatsby site to Netlify already.
Netlify was very easy to setup and link to my GitHub account you select a repo and pretty much with very little configuration you have a live site that will deploy every time you push to master.
With the selection of these tools I was able to build out my application, connect it to a realtime database, and deploy to a live environment all with $0 spent.
If you're looking to build out a small app I suggest giving these tools a go as you can get your idea out into the real world for absolutely no cost.
Your tech stack is solid for building a real-time messaging project.
React and React Native are excellent choices for the frontend, especially if you want to have both web and mobile versions of your application share code.
ExpressJS is an unopinionated framework that affords you the flexibility to use it's features at your term, which is a good start. However, I would recommend you explore Sails.js as well. Sails.js is built on top of Express.js and it provides additional features out of the box, especially the Websocket integration that your project requires.
Don't forget to set up Graphql codegen, this would improve your dev experience (Add Typescript, if you can too).
I don't know much about databases but you might want to consider using NO-SQL. I used Firebase real-time db and aws dynamo db on a few of my personal projects and I love they're easy to work with and offer more flexibility for a chat application.
- Automatically capture every user action36
- No code required23
- Free Plan21
- Real-time insights14
- Track custom events11
- Define user segments10
- Define active users7
- Redshift integration2
- Fun to use2
related Heap posts
At Heap, we searched for an existing tool that would allow us to express the full range of analyses we needed, index the event definitions that made up the analyses, and was a mature, natively distributed system.
After coming up empty on this search, we decided to compromise on the “maturity” requirement and build our own distributed system around Citus and sharded PostgreSQL. It was at this point that we also introduced Kafka as a queueing layer between the Node.js application servers and Postgres.
If we could go back in time, we probably would have started using Kafka on day one. One of the biggest benefits in adopting Kafka has been the peace of mind that it brings. In an analytics infrastructure, it’s often possible to make data ingestion idempotent.
In Heap’s case, that means that, if anything downstream from Kafka goes down, we won’t lose any data – it’s just going to take a bit longer to get to its destination. We also learned that you want the path between data hitting your servers and your initial persistence layer (in this case, Kafka) to be as short and simple as possible, since that is the surface area where a failure means you can lose customer data. We learned that it’s a very good fit for an analytics tool, since you can handle a huge number of incoming writes with relatively low latency. Kafka also gives you the ability to “replay” the data flow: it’s like a commit log for your whole infrastructure.
#MessageQueue #Databases #FrameworksFullStack
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.
Sentry
- Consolidates similar errors and makes resolution easy237
- Email Notifications121
- Open source108
- Slack integration84
- Github integration71
- Easy49
- User-friendly interface44
- The most important tool we use in production28
- Hipchat integration18
- Heroku Integration17
- Good documentation15
- Free tier14
- Self-hosted11
- Easy setup9
- Realiable7
- Provides context, and great stack trace6
- Feedback form on error pages4
- Love it baby4
- Gitlab integration3
- Filter by custom tags3
- Super user friendly3
- Captures local variables at each frame in backtraces3
- Easy Integration3
- Performance measurements1
- Confusing UI12
- Bundle size4
related Sentry posts
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.
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.