Hey, this is kind of offtopic, but figured still appropriate to ask;
How come Google Cloud Storage can be used instead of HDFS? I'm comparing google/amazon/azure right now. Both Amazon and Azure have 2 types of storage options - the regular object storage (S3a and Blobs) and block storage (S3 and Data Lake Store). S3 and DLS can act as the file system for Hadoop themselves (meaning you can let the data sit there and fire up clusters just for processing when needed), but they cannot interface with tools like the regular storage.
Meanwhile, Google's storage is like regular object storage, but you can run map/reduce (dataproc) and Spark on it.
How come Google Cloud Storage can be used instead of HDFS? I'm comparing google/amazon/azure right now. Both Amazon and Azure have 2 types of storage options - the regular object storage (S3a and Blobs) and block storage (S3 and Data Lake Store). S3 and DLS can act as the file system for Hadoop themselves (meaning you can let the data sit there and fire up clusters just for processing when needed), but they cannot interface with tools like the regular storage.
Meanwhile, Google's storage is like regular object storage, but you can run map/reduce (dataproc) and Spark on it.