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> Some of the Old LookML syntax is an exact copy. I met the online Looker demo a few years ago when I was looking for a business intelligence tool for another

> Some of the Old LookML syntax is an exact copy. I met the online Looker demo a few years ago when I was looking for a business intelligence tool for another project. Looker has a closed source code, so I did not see what algorithm is used to build queries. I kept those LookML features that I understood and liked. However, in some places LookML is confusing (for example - references and aliases). I made them differently. Later Looker quit using YAML. > Very few BI products have actually surpassed 100 users at target installations. And beyond 1,000 is a real challenge that only few, and even then with a lot of assistance, can support: Tableau, Looker, Microstrategy, maybe Birst, maybe Domo. Scaling that size is not a top priority right now. > Also, a combination of BI with LookML is a complicated product. You should have told me this a couple of years ago. It seemed pretty simple. > So with all that, the question is, is it really worth the struggle? Yes, If people will use it. > What's the end vision for supporting this? In future - maybe "skinny" or "thin" option mentioned here - https://medium.com/open-consensus/2-open-core-definition-examples-tradeoffs-e4d0c044da7c https://medium.com/open-consensus/2-open-core-definition-exa... >Why should someone who implements BI for a living bet on this product? If you can not afford Looker (like me) and want to use similar product.

endlessvoid94 8y ago
I used Looker for years and have always wanted a product priced less for the enterprise and more for developers. I even prototyped a similar tool myself. Congratulations on the launch. I will be using mprove and will give you feedback along the way. EDIT: I would love to get in touch with you and learn more about what your plans are. Possibly collaborate if you'd be open to that. I'm dpaola2@gmail.com -- I couldn't find your contact info anywhere!
- akalitenya 8y ago
  Thank you, I sent you an email. I am open to any suggestions - akalitenya@mprove.io.
__coaxialcabal 8y ago
> Very few BI products have actually surpassed 100 users at target installations. And beyond 1,000 is a real challenge that only few, and even then with a lot of assistance, can support: Tableau, Looker, Microstrategy, maybe Birst, maybe Domo. At one point Looker was essentially a web application with a query service that could be scaled by adding more servers behind a load balancer. Each end user is essentially working in a shared nothing environment and the query engine is driven by metadata stored in a git repository. Looker itself did not manage cache or analytical processes. All of the real effort to scale was in the database backend.
- segah 8y ago
  "scale" meant adoption, not performance. Scaling performance can generally be solved with hardware. Adoption, not so much.
zackt 8y ago
Looker is easy to cr*ck (terrible security) and you can deploy it everywhere for your BI needs. So we dont need similar product.

endlessvoid94 8y ago

I used Looker for years and have always wanted a product priced less for the enterprise and more for developers. I even prototyped a similar tool myself. Congratulations on the launch. I will be using mprove and will give you feedback along the way. EDIT: I would love to get in touch with you and learn more about what your plans are. Possibly collaborate if you'd be open to that. I'm dpaola2@gmail.com -- I couldn't find your contact info anywhere!

akalitenya 8y ago
Thank you, I sent you an email. I am open to any suggestions - akalitenya@mprove.io.

__coaxialcabal 8y ago

> Very few BI products have actually surpassed 100 users at target installations. And beyond 1,000 is a real challenge that only few, and even then with a lot of assistance, can support: Tableau, Looker, Microstrategy, maybe Birst, maybe Domo. At one point Looker was essentially a web application with a query service that could be scaled by adding more servers behind a load balancer. Each end user is essentially working in a shared nothing environment and the query engine is driven by metadata stored in a git repository. Looker itself did not manage cache or analytical processes. All of the real effort to scale was in the database backend.

segah 8y ago
"scale" meant adoption, not performance. Scaling performance can generally be solved with hardware. Adoption, not so much.

zackt 8y ago

Looker is easy to cr*ck (terrible security) and you can deploy it everywhere for your BI needs. So we dont need similar product.