WP_Cloud Analytics - Mapping Requirements to Technology

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10.1.2.5 BigQuery
BigQuery is Google’s fully managed, petabyte scale, low cost enterprise data warehouse for large-scale data
analytics. BigQuery is the public implementation of Dremel, Google’s internal columnar store, massively parallel,
scalable query service for read-only datasets of nested data. BigQuery is server-less. There is no infrastructure to
manage and no database administrator is needed, so developers can focus on analyzing data to find meaningful
insights using familiar SQL. Its engine can scan 1 TB data in seconds and 1 PB in minutes by parallelizing queries
and running them on tens of thousands of servers without using indexes. Developers can load data from Google
Cloud Storage or Google Cloud Datastore, or stream it into BigQuery to enable real-time data analysis. BigQuery
can easily scale databases from GBs to PBs. It automatically encrypts and replicates customer’s data to ensure
security, availability and durability. BigQuery can further protect data with strong role-based ACLs that GCP
configures and controls using the customer’s Google Cloud Identity & Access Management system.
References
10.1.2.6 Cloud SQL
Google Cloud SQL is a fully-managed database service that makes it easy to set up, maintain, manage,
and administer relational MySQL databases in the cloud. Google Cloud SQL Second Generation offers high
performance, scalability, and convenience with up to 10TB of storage capacity, 25,000 IOPS, and 208GB of RAM
per instance. Hosted on GCP, Cloud SQL provides a database infrastructure for applications running anywhere.
It automates all customer’s backups, replication, patches, and updates - while ensuring greater than 99.95%
availability, anywhere in the world. It encrypts the customer’s data when store on Google’s internal networks and
in database tables, temporary files, and backups. Every Cloud SQL instance includes a network firewall, allowing
customers to control network access to their database instance by granting access.
References
10.1.2.7 Cloud Bigtable
Cloud Bigtable is Google’s NoSQL Big Data database service. It is the same database that powers many
core Google services, including Search, Analytics, Maps, and Gmail. Bigtable is designed to handle massive
workloads at consistent low latency and high throughput, so it’s a great choice for both operational and analytical
applications, including IoT, user analytics, and financial data analysis. Bigtable provisions and scales to hundreds
of petabytes automatically, and can smoothly handle millions of operations per second.
Bigtable can integrate with Big Data tools like Hadoop, Hbase as well as GCP products like Cloud Dataflow and
Dataproc.
References
10.1.2.8 Cloud Storage
Google Cloud Storage is unified object storage for developers and enterprises, from live data serving to data
analytics/Machine Learning to data archiving. It allows to store data world-wide and retrieve of any amount of
data at any time. It can be used for multiple scenarios, including serving website content, storing data for archival
and disaster recovery, or distributing large data objects to users via direct download. It provides four storage
classes listed below; all storage classes offer the same throughput, low latency (time to first byte, typically tens of
milliseconds), and high durability. The classes differ by their availability, minimum storage durations, and pricing
for storage and access.
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