You are tasked with building an online analytical processing (OLAP) marketing analytics and reporting tool. This requires a relational database that can operate on hundreds of terabytes of data. What is the Google-recommended tool for such applications?
BigQuery is designed for handling large-scale analytical processing of tabular data, which makes it well-suited for OLAP (Online Analytical Processing) workloads. It supports SQL queries and is capable of managing and analyzing petabytes of data. Cloud Spanner and Cloud SQL are more suitable for OLTP (Online Transaction Processing) scenarios and do not efficiently handle the vast data volumes typically associated with OLAP. Cloud Firestore is a NoSQL database designed for real-time synchronization, making it unsuitable for the given requirements. Therefore, BigQuery is the most appropriate choice for building an OLAP marketing analytics and reporting tool.
Agree D
D is ok
What about the relational part? BigQuery uses SQL but it's not relational... I'm not sure its D
BigQuery is relational!
Pls do not confuse - Cloud SQL and BigQuery are RDBMS. Cloud Datastore, Bigtable are NoSQL. Right answer is D - BQ
Yes it is D
D, OLAP=BQ
Well Said
The question asks "This requires a relational database that can operate on hundreds of terabytes of data", but bq doesn't meet this condition?
BigQuery supports relational and query of join tables.
D, for sure. BigQuery for OLAP Google Cloud Spanner for OLTP.
The keyword in this context is OLAP. CloudSQL is Relational SQL for OLTP. Capacity wise, BQ supports for PB+ while CloudSQL only have max capacity of up to ~10TB. Again the questions specifically mention "hundreds of TB of data". So D is the answer.
Guys, this is easy: OLTP - Cloud Spanner & Cloud SQL OLAP - Big Query NoSQL - Filestore and Big Table So answer is D.
The answer is Big Query, D Secret: Analytical, Hundreds of TBTs. Relational. All of this are strictly meet by Big Query, if it had not said Analytical but rather, other keywords like High Availability then Cloud Spanner.
Why is it not CloudSQL? It supports TB data storage and the question is about a relational database, not a data warehouse such as BigQuery.
The keyword in this context is OLAP. CloudSQL is Relational SQL for OLTP. Capacity wise, BQ supports for PB+ while CloudSQL only have max capacity of up to ~10TB. Again the questions specifically mention "hundreds of TB of data". So D is the answer.
Big Query for large analytics , D is right
The words you need to focus "You are tasked with building an online analytical processing (OLAP) marketing analytics and reporting tool" which is BigQuery
https://cloud.google.com/products/databases.
D is ok
D is correct. BigQuery is relational. Cloud SQL is not OLAP; moreover it can not store/process hundreds of TB of data. Max size is 64 TB only.
Cloud SQL/Spanner is OLTP DB but not OLAP. BQ is a well-known OLAP for analytics and also supports RBMS feature too... so I would got with D
D is the right one
D is obvious
4 reasons to choose BQ (Supports Petabytes of data) - OLAP Data - Relational DB (SQL) - 100s of TB data - Analystics and Reporting
Agreed
sql is oltp olap is data cube. lots of data which we try to process somehow. biq query is for that. firestore is for mobile and web apps. not so fast nosql db.