RAra·Jul 4, 2023
As is snowplow https://github.com/snowplow/snowplow-javascript-tracker
In Companies must stop using Google Analyticssnowplow
snowplow-javascript-tracker
TypeScript2015–2023
snowplow / snowplow-javascript-tracker
snowplow-javascript-tracker
Snowplow event tracker for client-side and server-side JavaScript. Add analytics to your websites, web apps and servers.
6Distinct people
8Mentions
0Explicit recommenders
593GitHub stars
What to know before exploring
What it is
Snowplow event tracker for client-side and server-side JavaScript. Add analytics to your websites, web apps and servers.
GitHub
Where it is used
No documented product use has been verified yet.
What people are saying
No recommendation phrase was found in the indexed comments.
No classified warning is attached to this page. Read the discussions before treating silence as approval.
Also in these discussions
- snowplow/snowplow · linked in 2 of the same discussions
Mentioned in the same Hacker News threads. That is not proof they are substitutes.
This week on Hacker News
Nov 7–Nov 14 UTC · Direct repository links and separately labeled related project stories. Indexed through 11/14/2026, 1:49:46 PM UTC.
No direct repository links were found in the indexed HN discussions over the past seven days. Older discussions are available below.
Mentions over time
HN mentions by year8 dated mentions
Observed mentions: 2015-05-19 22:19:33 UTC to 2023-07-04 10:10:42 UTC.
Counts come from the repository’s dated source evidence. Index cutoff: 2026-11-02 08:16:59 UTC.
View mention counts and date ranges
| Period | Start (UTC) | End (exclusive, UTC) | Mentions | Submissions | Comments |
|---|---|---|---|---|---|
| 2015 | 2015-01-01 00:00:00 UTC | 2016-01-01 00:00:00 UTC | 1 | 0 | 1 |
| 2016 | 2016-01-01 00:00:00 UTC | 2017-01-01 00:00:00 UTC | 0 | 0 | 0 |
| 2017 | 2017-01-01 00:00:00 UTC | 2018-01-01 00:00:00 UTC | 0 | 0 | 0 |
| 2018 | 2018-01-01 00:00:00 UTC | 2019-01-01 00:00:00 UTC | 4 | 0 | 4 |
| 2019 | 2019-01-01 00:00:00 UTC | 2020-01-01 00:00:00 UTC | 2 | 0 | 2 |
| 2020 | 2020-01-01 00:00:00 UTC | 2021-01-01 00:00:00 UTC | 0 | 0 | 0 |
| 2021 | 2021-01-01 00:00:00 UTC | 2022-01-01 00:00:00 UTC | 0 | 0 | 0 |
| 2022 | 2022-01-01 00:00:00 UTC | 2023-01-01 00:00:00 UTC | 0 | 0 | 0 |
| 2023 | 2023-01-01 00:00:00 UTC | 2024-01-01 00:00:00 UTC | 1 | 0 | 1 |
What Hacker News says
8 sources(data engineer here)
Nice post! It's always fun reading about people being creative and challenging the analytics status quo (aka GA). Besides the joy of doing it yourself, you've accomplished a couple other things worth mentioning:
1. You'll never be sampled. GA samples historical data pretty heavily, and you have to pay for 360 to retain unsampled event data (at a tune of $160k+ per year).
2. You have full access to all generated data.
I'd highly recommend using Snowplow's javascript tracker (https://github.com/snowplow/snowplow-javascript-tracker) in a very similar manner to what you've outlined here. You'll get a ton of extra functionality out of the box, which would add yet another level of insight. With snowplow, you get the following for free:
1. Sessionization, which is consistent with google analytics' definition - effectively a
Read the rest
30 minute window of activity.
2. User identification - the tracker drops a persistent cookie (just like GA), so you can see returning visitors.
3. Tools for splitting requests
4. A variety of event types, out of the box: https://github.com/snowplow/snowplow/wiki/2-Specific-event-t...
5. Ability to respect Do Not Track
6. Time on page, browser width/height, etc
7. Ability to make your event tracking 100% first-party
(Disclaimer: I don't work for them, but I've seen the system work very well a number of times.)
I'm running a similar setup on my blog, and it costs well under $1 per month: https://bostata.com/client-side-instrumentation-for-under-on.... I'm doing the same exact thing with Cloudfront log forwarding and have several lambdas that process the files in S3. From there, I visualize traffic stats with AWS Athena (but retain a ton of flexibility, since they are all structured log files).
(Data engineer here)
Nice article! I did something very similar to this for my blog but used Snowplow's javascript tracker (https://github.com/snowplow/snowplow-javascript-tracker), a cloudfront distribution with s3 log forwarding, a couple lambda functions (with s3 "put" triggers), S3 as the post-processed storage layer, and AWS athena as the query layer. The system costs under $1 per month, is very scalable, and is producing amazingly good/structured data with mid-level latency. I've written about it here:
https://bostata.com/post/client-side-instrumentation-for-und...
By using the snowplow javascript tracker, you get a ton of functionality out of the box when it comes to respecting "do not track", structured event formatting, additional browser contexts, etc. If you want to see how the blog site is functionally instrumented, filter net
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work requests by "stm" (sent time) and you'll see what's being collected.
I've found (after setting similar systems for 15+ companies of varying scale) that where a system like this breaks down is when you want to warehouse event data and tie it to other critical business metrics (stripe, salesforce, database tables that underpin the application, etc). Another point it starts to break down is when you need low-latency data access. At that point it makes more and more sense to run data into a stream (kinesis/kafka/etc) and have "low latency" (couple hundred ms or less) and "high latency" (minutes/hours/etc) points of centralization.
Using multi-az/replicated stream-based infrastructure (like snowplow's scala stuff) has been completely transformational to numerous companies I've set it up at. A single source of truth when it comes to both low-latency and med/high-latency client side event data is absolutely massive. Secondly, being able to tie many sources of data together (via warehousing into redshift or snowflake) is eye-opening every single time. I've recently been running ~300k+ requests/minute through snowplow's stream-based infrastructure and it's rock-solid.
Again, nice post! It's awesome to see people doing similar things. :)
Snowplow[1] is an alternative to this. While they have a managed solution, their backend is open source and can be self-hosted. And they have a forked version of the Piwik client side library designed ot work with Snowplow[2].
Snowplow is a bit more generalized than just Piwik, and it shows in Piwik having a more robust featureset for website analytics specific. But Snowplow has a lot more usefulness if you're having to merge a bunch of data sources together to get a picture of what's happening.
[1] https://snowplowanalytics.com/
[2] https://github.com/snowplow/snowplow-javascript-tracker
In Microsoft Clarity – a product to visualize user interactionsI've heard Snowplow is good. I think it's self-hosted so it's likely more complicated to setup than a complete solution like Google Analytics. But then Google doesn't get the data.
https://github.com/snowplow/snowplow
https://github.com/snowplow/snowplow-javascript-tracker
In Ask HN: What are the best alternatives to Google Analytics?The event producer in this case is one of our Snowplow trackers (https://github.com/snowplow/snowplow-javascript-tracker) - and these tracking SDKs do indeed attach a UUID as a unique event ID at event creation time.
However, this event ID is not enough to identify and then dedupe all types of duplicate events. This blog post provides more information:
https://snowplowanalytics.com/blog/2015/08/19/dealing-with-d...
Big thanks to pragmacoders for putting this tutorial together! It's awesome seeing what you are doing with the Snowplow platform :-)
In Analytics data integrity is toughThis is known for a while and used to cause huge problems for our tracking: https://github.com/snowplow/snowplow-javascript-tracker/issu...
In Googlebot’s JavaScript random() function is deterministicCool post! After a fair bit of trial and error, we've got a pretty robust JSON Schema for the PerformanceTiming API here:
https://github.com/snowplow/iglu-central/blob/master/schemas...
We send that in as a custom context in the Snowplow JavaScript Tracker:
https://github.com/snowplow/snowplow-javascript-tracker/blob...
In Browser Monitoring for GitHub.com