Google Cloud SQL Features

Functions when integrated with multiple forms of external applications.

Allows admisistrators to manage and organize storage, networks, and datacenters.

Monitors performance and statistics related to memory, caches and connections.

Alerts users when unauthorized parties or malware is detected allowing administrators to remedy the issue.

Secures data at rest and in transit from unauthorized access.

Allows administrators to organize components of the database to maintain instance efficiency.

Allows the creating and relinquishing of database access credentials.

Documents access and alterations of the database for analytics and reporting.

Expands functionality while maintaining balanced loads. Serves growing demand without reducing functionality.

The abillity to restore files to its original loacation or alternative sources on-demand.

Stores historical records of information for reverting or reference.

Helps users navigate databases by labeling and organizing datasets.

Data masking provides an additional layer of access control that can be applied to tables and views.

Verifies identity of database users.

Allows users to gain statistically valid insights from their data while protecting the privacy of individuals.

Encrypts and transforms data at the database from a readable state into a ciphertext of unreadable characters.

Allows restricted user acess to modify depending on the access level.

Prevents other users and applications from accessing data while it is being updated to avoid data loss or update.

Allows permissions to be granted or revoked in the database, schema or table levels.

Built-in native encryption with enterprise key management.

Provides multi-factor authentication with certificates.

Helps in improving the availability of data.

Uses machine learning algorithms to gain actionable insights.

Allows data movement from one database to another.

Provides data backup and recovery functionality to protect and restore a database.

Allows users to access and work on data concurrently, supporting several views of the data.

Stores the database metadata, that is the definitions of data elements, types, relationships etc.

Creates a copy of the database to maintain consistency and integrity.

Allows users to create, update and retrieve data in a database.

Defines the logical design of the data before building the schemas.

Monitors and analyzes critical database attributes like query performance, user sessions, dead lock detail, system errors etc and visualize them on a custom dashboard.

Provides support for international character sets and full text search.

Supports multiple data types like primitive, structured, document etc.

Supports multiple procedural programming languages like PL/PGSQL, Perl, Python etc.

Available on multiple operating systems like Linux, Windows, MacOS etc.

Provides data recovery functionality to protect and restore data in a database.

Allows multi-version concurrency control.

Handles workloads, from single machines to data warehouses or web services with many concurrent users.

Allows users to quickly retrieve data through various types of indexing like B-tree, hash table etc.

Helps interpret SQL queries and determine the fastest method of execution.

Data is organized as a set of tables with columns and rows like a table structure.

Allows users to create, update and retrieve data in a database.

Adheres to ACID (atomicity, consistency, isolation, durability), a set of database transaction properties.

Provides log-based or/and trigger-based replication.