Databases

Cloud SQL

It is a fully managed service of either MySQL, PostgreSQL or Microsoft SQL server
Patches and updates are automatically applied
We still have to manage and administer users for these databases
Cloud SQL supports many clients:
- gcloud sql
- App Engine, Google Workspace scripts
- Applications and tools:
  - SQL Workbench, Toad
  - External applications using standard MySQL drivers
Cloud SQL high performance and scalability:
- Up to 64 TB of storage
- Up to 60_000 IOPS
- Up to 624 GB or RAM per instance
- Ability to scale out with read replicas
Other Cloud SQL services:
- HA configuration: primary-standby instances with synchronous replications
- Backup service: automated and on-demand backups
- Import/export
- Scaling: up (change machine capacity), out (read replicas)
Connecting to a Cloud SQL instance:
- Same project in the same region: chose private IP connection for most performance and most secure
- Other region, or from outside of GCP:
  - Recommended: use Cloud SQL proxy (offers key rotation)
  - Manual SSL connection
  - Connect from authorized network (if no SSL connection is available)

It is a service built for the cloud to combine the benefits of relational structure with non-relational horizontal scale
Can provide petabyte scale with transactional consistency at global scale
Provides schemas, SQL and automatic replication for high availability
Use cases include financial applications and inventory applications, traditionally served by relational databases
Monthly uptime SLAs:
- Regional: 99.99%
- Multi-regional: 99.999%
Cloud Spanner architecture:
- Cloud Spanner replicates data in N cloud zones (on region or several regions)
- Replication of data is synchronized through Google’s global network
- Uses atomic clocks to ensure atomicity
Recommended when our data outgrown a traditional relational database

It is a fast, fully managed, serverless, NoSQL document database
Simplifies storing, syncing and querying data for mobile, web and IoT data at global scale
Client libraries provide live synchronization and offline support
Supports ACID transactions
With automatic replication, data is safe and available even is case of disaster (multi-region replication)
It offer a powerful querying engine
Firestore is the next generation of Cloud Datastore. Firestore can operate in Datastore mode making it backwards compatible with Datastore
Firestore removes some Datastore limitations such as:
- Queries are no long eventually consistent
- Transactions are no longer limited to 25 entity groups
- Writes per entity are no longer limited to 1 per second
Firestore in Native mode introduces the following features:
- Strongly consistent storage layer
- Collection and document data model
- Real-time updates
- Mobile and web client libraries
General guideline is:
- Use Firestore in Datastore mode for server applications
- Use Firestore in Native mode for mobile and web apps

It is a fully managed NoSQL bit data database with petabyte-scale and very low latency
It seamlessly sells for throughput
Ideal for Ad Tech, Fintech and IoT because supports high read and write throughput with low latency
It a great storage engine for ML applications
It integrates with open source big data tools such as Hadoop, Cloud Dataflow and Cloud Dataproc
Supports the open source HBase API
Cloud Bigtable stores data in massively scalable tables, each of which is sorted key-value map
Table are composed of rows describing a single entity and columns
Each row is indexed with a single row key
Columns which do relate to each other are grouped together in column families
Each column is identified by a combination of column family and column quantifier
Cloud Bigtable tables are sparse
Tables are sharded into blocks of contiguous rows, called tablets
Tablets are similar to HBase regions
Bigtables learns to adjust to certain access patterns