[HN Gopher] Show HN: Product analytics on your data warehouse
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       Show HN: Product analytics on your data warehouse
        
       Author : n_f
       Score  : 10 points
       Date   : 2023-01-09 19:57 UTC (3 hours ago)
        
 (HTM) web link (github.com)
 (TXT) w3m dump (github.com)
        
       | Rodeoclash wrote:
       | It would be good to get a breakdown of this vs existing products.
       | For example, I use Metabase quite heavily but I'm having trouble
       | comparing what your product gives me in comparison to it.
       | 
       | Congrats on launching!
        
       | XCSme wrote:
       | Is it similar to https://chartbrew.com ?
        
         | n_f wrote:
         | Fabra is built for the modern data stack, meaning our customers
         | already send all of their data to a central data warehouse as
         | their single source of truth.
         | 
         | It looks like Chartbrew connects to various third-party tools
         | directly, which can lead to silos/discrepancies in our
         | experience.
        
           | XCSme wrote:
           | But allowing for integration with multiple data sources
           | doesn't mean you can't use only one if you prefer so. Does
           | Fabra also store the data, or only connects to an external
           | data warehouse?
        
             | n_f wrote:
             | Exactly! We don't store any data and natively connect to
             | external data warehouses. This means we're way cheaper-- no
             | need to move data or store a copy.
        
               | XCSme wrote:
               | I understand, then what's the advantage compared to
               | ChartBrew? Not having the multi-data-source feature
               | doesn't sound like an advantage.
        
       | heresjohnny wrote:
       | Hey, congrats on the launch. This may be clear for others, but
       | personally I'm missing a bit more details. What precisely is
       | "product analytics on [a] data warehouse"? Are you an Amplitude
       | competitor? Or more of a DIY scripting alternative?
       | 
       | I like that you kept things brief but some screenshots and use
       | cases would be a nice improvement for the landing page.
        
         | n_f wrote:
         | That's right, we're an Amplitude competitor-- but run the
         | queries directly in our customer's own data warehouse.
         | 
         | Appreciate the feedback, will be uploading more screenshots
         | shortly.
        
       | n_f wrote:
       | Hi everyone! I wanted to share Fabra-- product analytics for the
       | modern data stack. Fabra runs directly on your data warehouse,
       | meaning we don't add another data silo or need you to setup
       | costly ETLs.
       | 
       | In addition to self-hosting our open source product, we also
       | offer a hosted version which is WAY cheaper than other tools
       | since we don't store any data.
       | 
       | Let us know if you have any feedback, you can always reach me at
       | nick@fabra.io
        
       | endlessvoid94 wrote:
       | How do you build a data warehouse without ETL?
        
         | n_f wrote:
         | We aren't a data warehouse, just the query-building and
         | visualization layer. We let product teams easily do things like
         | build funnels, measure trends, and more with the data they've
         | already collected.
        
           | endlessvoid94 wrote:
           | From your tagline:
           | 
           | > Build funnels and measure trends directly on your data
           | warehouse, without paying for costly ETL and duplicate
           | storage in outdated analytics tools.
           | 
           | Not being snarky, I just don't understand. The output of an
           | ETL is data in your data warehouse. Then you build reports on
           | top of the DW.
           | 
           | How does Fabra prevent me from needing an ETL?
        
       | Simon_O_Rourke wrote:
       | Cool, I'll give it a spin tomorrow on a fairly hefty dataset and
       | see how it goes.
        
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       (page generated 2023-01-09 23:03 UTC)