Snowplow VS Apache Superset

We’ve also thought about Ops :-). There’s a backend 'Collector' that stores data in Postgres, for instance to use while developing locally, or if you want to get set up quickly. But there’s also full integration with Snowplow, which works seamlessly with an existing Snowplow setup as well.

Sure thing! Say you run an online store. Your source systems could be the inventory, orders or customer databases. You could also track click/site behavior with something like snowplow. An ERP system is essentially just a combination of what I mentioned previously. Another good example is a CRM such as Salesforce or Zendesk. Hopefully that helps!

There are so many of them in big data, e.g. Kafka, Spark, Flink, Delta, Snowplow, Finagle, Deequ, CMAK, OpenWhisk, Snowflake, TheHive, TVM-VTA, etc.

I added Snowplow Analytics to a site with a lot of traffic. It was a very basic implementation, where data is collected with Snowplow, stored in google big query, and visualized in google data studio. The data is collected from the caching/web server combined with a client-side tracker.

Well if you have to structure and create Schema and manage Data Warehouses, you need a tool to do that, so in the background you see SnowPlow, which helps you do just that. Make the data into some kind of sensible structure so that later on business analysts can come see whats up. Want to do a quarterly report on how you performed, go to the application that goes to the data warehouse and builds your report for you. Want to compare to other similar companies in the portfolio to see how they are performing, same story. Data scientists will build and structure the data and store it and manipulate it and extract the value from it so that the analysts and sales people can then come in and do some selling. Show the customers what they got for their money and guarantee the renewal.

if you want self host, check out https://github.com/snowplow/snowplow

We also have telemetry set up on our Monosi product which is collected through Snowplow,. As with Airbyte, we chose Snowplow because of its open source offering and because of their scalable event ingestion framework. There are other open source options to consider including Jitsu and RudderStack or closed source options like Segment. Since we started building our product with just a CLI offering, we didn’t need a full CDP solution so we chose Snowplow.

https://matomo.org

That's the only full featured open source competitor I am aware of, so it should be mentioned.

https://snowplowanalytics.com/

Somewhat FOSS. There was a story there, but I don't remember the details.

I added Snowplow Analytics to a site with a lot of traffic. It was a very basic implementation, where data is collected with Snowplow, stored in google big query, and visualized in google data studio. The data is collected from the caching/web server combined with a 1st part cookie set in the user's browser.

The first difference is that after pull request 4565 was merged, you can no longer do:

Open-source BI platforms such as Metabase (website, GitHub) and Apache SuperSet (website, GitHub) are easy to deploy without IT involvement. Metabase lets you build dashboards from the data in your warehouse easily, with no SQL, or, if you have data engineering or science know-how, inside more powerful and flexible notebooks or with SQL itself. Similarly, Apache SuperSet helps businesses explore and visualize data from simple line charts to detailed geospatial charts.

Check out Superset. https://github.com/apache/incubator-superset

It’s modern, easy to extend. From the same author of apache airflow.