Google TensorFlow and DeepMind, Microsoft WSL2, Meta AI, etc. Also worth mentioning the many quiet efforts to get quantum computing off the ground.
Looks like I was mistaken. It uses some parts of postgres 8, but it is heavily modified. I agree Redshift isn’t that great though and it is super expensive for what you get. In the past when I have used Redshift I have not been that impressed.
Although one nice feature of Redshift is how well it works with other AWS services (COPY command from S3, firehouse can dump data into it, etc.)
Kubernetes is not a Google product. But it is "a" product, and it was successfully launched as a commoditize-your-complement / cannibalize-yourself kind of thing.
GKE meanwhile is a Google product, and is successful, and wouldn't exist if it wasn't for Kubernetes.
Something I can insert money into, which solves a more expensive problem.
Kubernetes and TensorFlow are extraordinary technologies - and very important to the work I do daily. I don't think they're products though, certainly not successful products.
Right. I would argue that "public cloud infrastructure" is such a product; GCP/AWS/Azure specifically. (See below also) Kubernetes enabled the existence of EKS/AKS/GKE all of which I believe are considered successful.
Separately, TensorFlow enabled Azure Machine Learning, TensorFlow on AWS and Google Cloud TensorFlow Enterprise, and generally expanded (IMO) the market for IaaS.
Kubernetes and TensorFlow should count, and are successful.
AlloyDB is IMO most likely to be successful (especially since AWS Aurora already proved the market): https://cloud.google.com/alloydb
Since this question seems to be much more about the consumer side, I think both Google Home and YouTube TV are independently considered successful though I have no doubt many people will chime in to note how much they hate either or both of those things.