Google Cloud Spanner
PostgreSQL
MySQL
Oracle DBaaS
Microsoft SQL
SQLite
MariaDB
Amazon Aurora
Google CLOUD AUTOML
Qubole
BigML
TensorFlow
Scikit-learn
machine-learning in Python
RapidMiner
AWS SageMaker Ground Truth
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Based on our record, Google Cloud Spanner should be more popular than Google CLOUD AUTOML. It has been mentiond 17 times since March 2021. We are tracking product recommendations and mentions on various public social media platforms and blogs. They can help you identify which product is more popular and what people think of it.
Multiregion is possible in Google Cloud using Cloud Spanner, which allows you to replicate the database not only in multiple zones but also in multiple regions as defined in the instance configuration. The replicas allow you to read data with low latency from multiple locations that are close to or within the region in the configuration. - Source: dev.to / 10 months ago
Basically everything I touch is in-house, but a majority of it is available publicly. For instance: https://cloud.google.com/spanner/. Source: over 1 year ago
An application that needs to handle a lot of data can use a distributed database like Cloud Spanner. Unlimited scale and you don't have to split your database into multiple tables. Source: over 1 year ago
Look at the architecture and performance of Google's Cloud Spanner, a CP system with 99.999% availability... https://cloud.google.com/spanner. Source: over 1 year ago
In my opinion, Google has built some fantastic database services like Bigtable and Spanner, which literally changed the industry for good, and I am eager to see how they will build upon this new service. With AlloyDB's disaggregated architecture, the dystopian world where I only pay for SQL databases per query and the stored data on GCP seems closer than ever. - Source: dev.to / over 1 year ago
There are several no-code AI websites that you can use like Amazon SageMaker, Apple CreateML or Google AutoML. Source: about 1 year ago
GCP, on the other hand, offers two top options: Google Cloud AutoML, for beginners, and Google Cloud Machine Learning Engine, for handling tasking projects. GCP also provides Tenserflow and Vertex AI complicated machine learning abilities. - Source: dev.to / over 1 year ago
Just outsource the work to Google or Amazon. Source: over 2 years ago
We can also note the appearance of Machine Learning, creating dynamic processes over data that would have been tedious to analyse, either by hand or through specific code. This enables writing potentially complex behaviours with a few lines of code in some cases. Even then, there is some automation of it to the point where you only have to provide data to get working results. - Source: dev.to / about 3 years ago
You might want to check out automl Google AutoML. Source: almost 3 years ago
PostgreSQL - PostgreSQL is a powerful, open source object-relational database system.
Qubole - Qubole delivers a self-service platform for big aata analytics built on Amazon, Microsoft and Google Clouds.
MySQL - The world's most popular open source database
BigML - BigML's goal is to create a machine learning service extremely easy to use and seamless to integrate.
Oracle DBaaS - See how Oracle Database 12c enables businesses to plug into the cloud and power the real-time enterprise.
TensorFlow - TensorFlow is an open-source machine learning framework designed and published by Google. It tracks data flow graphs over time. Nodes in the data flow graphs represent machine learning algorithms. Read more about TensorFlow.
