Another option is to use map-reduce against your datastore tables for aggregation of truly 'big' data sets. It's nowhere near as flexible as some of the other options mentioned here, but if your requirements are fairly static it works great and will allow you to keep your data in one place.
On Thursday, January 26, 2017 at 2:52:06 PM UTC-6, George (Cloud Platform Support) wrote: > > How large can your sales invoice data get in the end? The solutions > recommended above may work well for relatively small volumes. If you need > to process terabytes of data in the end, Cloud Bigtable > <https://cloud.google.com/bigtable/docs/overview> might prove speedier > and cost less overall. > -- You received this message because you are subscribed to the Google Groups "Google App Engine" group. To unsubscribe from this group and stop receiving emails from it, send an email to [email protected]. To post to this group, send email to [email protected]. Visit this group at https://groups.google.com/group/google-appengine. To view this discussion on the web visit https://groups.google.com/d/msgid/google-appengine/9fe3d5f5-1995-461b-85cf-1006877f3dad%40googlegroups.com. For more options, visit https://groups.google.com/d/optout.
