I work very closely with the Google Cloud team as a technology partner. With the recent hire of Thomas Kurian he has to make a big splash at Google while good will is forthcoming and I expect he will continue to authorize significant acquisitions to help build out their cloud to compete with Azure/AWS. The next piece of the puzzle will be an integration platform to help bring it all together.
Would love to collaborate, do you want to join our Zoom call https://gitlab.zoom.us/j/542273985? (Anyone else who wants to join in is welcome, the link is open)
We have launched a new open source project to work on the spec and collaborators are welcome
When users connect to their Segment warehouse, we automatically install this recipe, they can fork our Segment recipe to build their models on top of our base recipe. Thanks to DBT, we support some advanced features such as incremental materialization and since our focus is on product data, we have embedded features such as funnel & retention & segmentation.
Our product is not feature-complete compared to Looker but we're implementing features & working on stability for the last few months. One of our team members is working on automatic LookML converter to Rakam Recipe so that we can have more coverage of LookML. We will definitely focus more on Looker use-cases after this acquisition. :) Would love to talk if anyone is interested! (email is in my bio)
I've found something like a LookML syntax backed by SQLAlchemy Core has allowed me to implement something like Looker (but tied to my own visualization stack)
That's probably the major reason of the acquisition.
1. “When will Google deprecate this feature/product/service?”
2. “None of Google’s acquisitions have done well”.
And Android, Youtube, Doubleclick, etc.
upgrading to new releases? nah
consistent look and feel? not on my watch!
it just works? madness...
That's it.
https://arstechnica.com/information-technology/2019/06/googl...
https://www.forbes.com/sites/gordonkelly/2019/01/29/apple-io...
Except for the super distracting Ads that cover half the screen while you're using it every time your car comes to a stop, the sponsored landmark-Ads that put a huge marker over every Dunkin Donuts location while driving, etc.
(in my country, waze is the go to app for navigation for everyone)
We are a Looker customer and are concerned. It seems Google is one of the only companies that can buy a SAAS enterprise product that people are paying a lot of money for, and eventually drop enterprise customers for the free* model. Hundreds of millions or even low billions of revenue isn't interesting to them it seems.
When a Cloud company acquired a product/service for integration into their platform, I would hope that that includes transitioning to a Cloud friendly consumption based model. If that means including a free tier, or paying peanuts for low usage, that’s a good thing!
Finally, Google’s (GCP’s really) enterprise SaaS (mostly) acquisitions that I can think of are - StackDriver, Firebase, Apigee, Velostrata, Alooma and Cask. The venerable ones like StackDriver and Firebase are IMHO well integrated into the platform. The others are too relatively new? Curious which ones you had in mind that dropped enterprise customers?
And despite Google’s other product demises in the consumer space, GCP has had a decent track record thus far.
1. When Google acquired Alooma, they slowed down the development and dropped the support for other destinations such as Redshift and Hive. Even though Alooma is a data pipeline tool which makes it similar to Looker's case, the deal was $150M (compared to $2.6B) so I'm not sure the comparison makes sense.
2. Looker's sale team is so aggressive and their support team is great. In fact, that's why Looker became so big in the last few years. Google is not famous in terms of support.
3. Google is serious on BigQuery and I'm almost sure it will make Looker part of the Google Cloud. Since most of Looker customers are enterprise companies, Google will probably chase them to switch to BigQuery. On the other hand, Google has tons of BI tools (Data Studio, BigQuery BI Engine, etc.) so I'm not sure if Google makes Looker part of their analytics stack.
P.S: We're big fans of the LookML and we have developed a LookML alternative based on Jsonnet (https://jsonnet.org/) and the great data pipeline tool DBT. (https://github.com/fishtown-analytics/dbt). Here is how it looks like: https://github.com/rakam-io/segment-recipe/blob/master/event...