Google Data Solutions

Cloud Datastore
Google Cloud DataStore is a cloud-based NoSQL database for web and mobile applications. It’s scalable NoSQL database and can automatically handles sharding and replication. It also supports ACID transaction, SQL-like queries and REST API. Unlike BigTable, Datastore is optimized for "smaller set" of data compared to Big Table. BUT scales

• User profiles
• Websites
• Product catalogs
• Game state

 

Big Table
Google BigTable is Google’s cloud storage solution for low latency data access. It was originally developed in 2004 and was built on Google File System (GFS). There is one paper about BigTable: Bigtable: A Distributed Storage System for Structured Data. Now It is widely used in many Google’s core services like Google Search, Google Maps, and Gmail. It is designed in NoSQL architecture, but can still use row-based data format. With data read/write under 10 milliseconds, it is good for applications that have frequent data ingestion. It can be scaleable to hundreds of petabytes and handle millions of operations per second.

• IoT, finance, adtech
• Personalization, recommendations
• Monitoring
• Geospatial datasets
• Graphs

 

Cloud SQL
If you want to have full relational database in supporting customized table views, stored procedures, tons of indexes and ACID compliance, Cloud SQL is probably your potential choice here. Google Cloud SQL is the database service that support two types of databases: MySQL and PostgreSQL. Both support High Available (HA) and Pay Per Use without Lock-in. It can scale up to 32 processor cores and more than 200GB RAM. Although this option might make your life easier in migrating your data to cloud, it does have all the limitations in MySQL and PostgreSQL, and not scaling well for huge data volume.

• Websites, blogs, and content management systems (CMS)
• Business Intelligence (BI) applications
• ERP, CRM, and eCommerce applications
• Geospatial applications

 

BigQuery
BigQuery is Google’s Cloud-based data warehousing solution. Unlike BigTable, it targets data in big picture and can query huge volume of data in a short time. As the data is stored in columnar data format, it is much faster in scanning large amounts of data compared with BigTable. BigQuery allows you to scale to petabyte and is great enterprise data warehouse for analytics

• Analytical reporting on large data
• Data Science and advanced analyses
• Big Data processing using SQL

 

Cloud Spanner
Cloud Spanner is a globally distributed database and was released in May 2017. It is a versioned key-value store. From this perspective, it is similar to BigTable. However, it support general-purpose transactions and provide SQL-based query language.

Spanner was developed in 2011 and used internally for Google’s advertising backend, which is called F1. F1 was initially based on a MySQL database. As Google grows rapidly in its advertising revenue, so is the F1 MySQL database. The uncompressed dataset is in tens of TB. It’s definitely way beyond the comfort zone for MySQL. Even with tremendous effort in sharding scheme, the management of the database became very complex and costly.

• Adtech
• Financial services
• Global supply chain
• Retail

 

Cloud Firestore
For mobile use with Firebase (MaaS - mobile as a service)

Google Cloud Storage
Goolges version of S3 -file storage.

OTHER...

Cloud DataFlow
BigQuery is Google’s Cloud-based data warehousing solution. Unlike BigTable, it targets data in big picture and can query huge volume of data in a short time. As the data is stored in columnar data format, it is much faster in scanning large amounts of data compared with BigTable. BigQuery allows you to scale to petabyte and is great enterprise data warehouse for analytics

Googles Diagram to Figure out What Service is for YOU