Hey all, as a potential competitor of Looker, I'm not sure how I should feel about this news. :) Here are some of the facts:
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.
Don't worry about it. It's undoubtedly an aquihire. If there is one thing that Google demonstrates consistently is a complete disregard for relationships with external parties. This product will die once Google stops communicating with external companies. This is your opportunity to reassure your partners you're not going away and to reach out to Looker's companies to see if you can help stay in-front of this. Just don't be a dick about it: "Hey, just saying that Google is known for letting products die. If you're concerned about this, we'd love to know how to help you with those concerns."
Honestly I wouldn't worry about it, if anything Google Cloud just raised the profile of every BI product out there.
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.
Do you have the Meltano models in a repository? It looks similar to LookML so the use-case is similar. I would love to hear more and see some of your example Meltano models, could you please send an email to emre [at] rakam.io?
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 actually developed this feature (we call it recipe) 2 weeks ago and we're working on the documentation at the moment. Since we focus on product data, the first recipe is written for Segment Warehouse.
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)
That's correct but we're not an ETL engine. We use DBT for the data transformation and you basically define what the measures/dimensions/filters are in this template so that your non-technical people run ad-hoc queries without any need to write SQL queries.
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)
How does it work with parameterized filtering, time intelligence, etc ? Does the user have to modify the script or can they do it through point and click UI.
It's not quite point and click, although I've implemented Tableau like frontends on Qt/javascript which construct a pivot description, and then get compiled using SQLAlchemy core into a sql query that drives the DB. Still working out the best UX to expose to the user, but I think I'll go the approach of Mode since our users are sophisticated enough to write analytic SQL.
> When Google acquired Alooma, they slowed down the development and dropped the support for other destinations such as Redshift and Hive.
Do you have a source for that? As far as I can see on their website [1] they still support it
> 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.
That's probably the major reason of the acquisition.
i think these are fair game and in the long term are going to be an issue for google. once their core business stops working and/or gets serious competition they’re going to be in trouble.
android is both a success and a failure. i used to be a huge android fannoi before switching to iphone. even for a highly technical person, maintaining an android phone is too much.
> singular focus in improving the driving experience
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.
Lots of it is integrated into Maps: a good portion of the traffic/accident alerts have a "reported by Waze" line at the bottom. I wouldn't be surprised if they start sunsetting Waze once they're fully integrated and finished experimenting on it.
I'm pretty sure its because it allows them to experiment with delivering advertisements that they wouldn't be able to shove into GMaps without protest (Waze has ads that cover half the screen with a banner ad every time your car slows down/stops for example).
Even I am surprised too but I guess since Google started working on self-driving cars and then after seeing the advent of ride-hailing apps, they may have thought to keep Waze so one day Google can convert it into a ride-hailing + navigation app. Maybe that's the plan who knows!
i still don't get that argument. target audience of Waze is people who have cars and drive it around. people don't open up waze to get a taxi, they open it up to start driving.
Yes mostly related to advertising in some way which is their core business (besides 510). I think OP wasn't remarking about the financial success of the company as a part of Google, but the absorbing by Google of former SAAS companies and finally dropping their original paying customers.
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?
It’s interesting that Thomas Kurian (who heads GCP) announced the purchase. He’s ex-Oracle and really understands the enterprise and enterprise software.
And despite Google’s other product demises in the consumer space, GCP has had a decent track record thus far.
you need to put things in perspective. I could argue that the above are not successful and I would also like to see how many acquisitions total were made and what percentage actually end up not straight-up dying.
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...