While advantage Google has enjoyed is slimmer, I think it's a fallacy to think that technology has been commoditized.
Slight oversimplification, but Google's had basically S3/GCS and Hadoop since early 2000s, and basically Docker + Kubernetes for the past 10. This translates into real-world edge.
For example, how many big data tools have any one of the 15 characteristics of BigQuery that I described at [0]? Or how many companies have inter-data center networking that gives you a Petabit of bisectional bandwidth, described at [1], or how many cloud providers have live migration, custom VMs, or insane RAM-like local SSD? Or how many PaaS offerings can sustain a behemoth like Snapchat? Or a NoSQL that scales to 56 million qps with just a handful of engineers [2] ??
Edit: To add more color. In days past, Google would release papers (GFS, MapReduce, Bigtable, etc). With Google Cloud Platform we can just externalize these services (with a bit of customer-friendly bits like isolation, pricing, etc). Bigtable, BigQuery (Dremel), PubSub to name a few.
These are good points. Google does offer services that nobody else has. Some that are very easy to use, and competitively advantageous.
Except... Customer service for cloud platforms is terrible. Not only is there an image problem. The fact that there is almost a blog post about Google Cloud Service screwing over a customer and just flat not communicating happens every 2-3 months.
If you have an case ids, where you had terrible service with Google Cloud Platform Support, please send them to me (tsg@google.com) and I will investigate them.
I was (mostly still am) a big fan of Google BigQuery. Especially since GQL supported some Regex, plus native URL parsing. That is one of the coolest services that Google offers that no other service can match.
However, having used Big Query extensively at my startup, getting external data into it via Google Cloud Storage was a royal pain in my balls.
My broader point, is that Google was able to disrupt the Ad industry because it dominated web search by way of having a large number of exceptionally brilliant engineers. In 2016, that is no longer true--many other big (and small) players have invested in hiring their own equally brilliant engineers.
Sorry to hear. We have completely revamped our ingest mechanism lately. Feel free to ping me with specific problem you had.
From my experience, most issues with loading data stem from just data parsing, or trying to make batch load behave like stream load (we have an api for that too).
And, one of the things I mention in my article, unlike any other database, batch ingest into BigQuery is entirely free, as in not competing with query capacity one bit.
Slight oversimplification, but Google's had basically S3/GCS and Hadoop since early 2000s, and basically Docker + Kubernetes for the past 10. This translates into real-world edge.
For example, how many big data tools have any one of the 15 characteristics of BigQuery that I described at [0]? Or how many companies have inter-data center networking that gives you a Petabit of bisectional bandwidth, described at [1], or how many cloud providers have live migration, custom VMs, or insane RAM-like local SSD? Or how many PaaS offerings can sustain a behemoth like Snapchat? Or a NoSQL that scales to 56 million qps with just a handful of engineers [2] ??
Edit: To add more color. In days past, Google would release papers (GFS, MapReduce, Bigtable, etc). With Google Cloud Platform we can just externalize these services (with a bit of customer-friendly bits like isolation, pricing, etc). Bigtable, BigQuery (Dremel), PubSub to name a few.
(clearly biased, since I work at Google)
[0]https://medium.com/p/6654841fa2dc
[1]https://cloudplatform.googleblog.com/2015/06/A-Look-Inside-G...
[2]https://cloudplatform.googleblog.com/2016/03/financial-servi...