Snowplow VS typebox

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 documentation can be found here.

So far I like the commonly used approach in the Typescript community best:

1. Create your Schema using https://zod.dev or https://github.com/sinclairzx81/typebox

2. Generate your Types from the schema. It's very simple to create partial or composite types, e.g. UpdateModel, InsertModels, Arrays of them, etc.

3. Most modern Frameworks have first class support for validation, like is a great example Fastify (with typebox). Just reuse your schema definition.

That is very easy, obvious and effective.

There's a ton of schema validators out there and most devs have their personal favorite. Mine was zod and is now typebox + ajv.

If you're willing to document your API with an OpenAPI schema, then it should be possible to generate TypeScript types based on the OpenAPI schema with something like openapi-typescript. Also, Typebox can generate JSON schemas, maybe it can be used to generate something that the front-end can also use?

Well, I do provide extensibility for those bullet points you've listed to varying degrees (both schema and type representation), as well as offering a reference implementation for expressing a entirely different schema specification under the type system (specifically RFC8927 / JSON Type Definition). Reference implementation here. As for JSDoc, It's supported in code hints.

In setting out to build this service, we wanted to use gRPC for its APIs. We’ve been reaching for REST when building APIs so far, primarily out of necessity, i.e., our public APIs needed auto-generated client SDKs and docs for developers working with them. We built those APIs with Fastify and Typebox but felt burned by a code-first approach to generating an OpenAPI spec. I’ll spare you the details and save that experience/learning for another article. Suffice it to say we love gRPC’s schema-first approach. This blog post summarizes our feelings well