An Overview of All the Different Databases in Google Cloud

An Overview of All the Different
Databases in Google Cloud

Google cloud platform (GCP) is a high-performance
infrastructure for cloud computing, data analytics, and
machine learning. Google Cloud runs on the same
infrastructure that Google uses for its end-user products
like Google Search, Gmail, Google Drive, Google Photos,
etc. This blog gives you an insight into the various
databases offered by Google Cloud.

BARE METAL SOLUTION FOR ORACLE

It is a relational database that helps to perform the
migration of Oracle workloads to Google Cloud. Oracle
workloads can be migrated with our preferred methods
such as Oracle Data Guard, Oracle GoldenGate, Oracle
Data Pump, or Oracle RMAN for backups. Bare Metal
solution features define our IP subnets for use in the
environment. We can fit our Bare Metal solution into any
existing IP address schema which the enterprise has.

It can be used for database management, automation of
operational databases, and administration tasks. The
latest technologies leveraged by Bare Metal Solutions
include Cascade Lake servers, Tier 1 NVM storage, and a
100G network. It has a latency of less than 2ms. It offers
the highest core to memory ratio in comparison with other
cloud services.

CLOUD SQL

Cloud SQL is a self-managed, relational database that
serves as an alternative to local MySQL, PostgreSQL, and

SQL server databases. It reduces time invested in
Database Management and improves usability. Cloud SQL
enables us to create and delete databases and database
users, but it is not a database administration tool. It
performs operations like backups, high availability, and
failover, network connectivity, export and import, flagging,
maintenance, updates, monitoring, and logging. System
updates are performed by Cloud SQL whereas
configuration updates are done by the user. It can be used
to build containerized applications, perform data analytics,
build and deploy web apps and manage databases using
Terraform.

Using Cloud SQL, we can add up to 96 processor cores,
more than 624GB RAM, and 30TB storage. We can add
read replicas to handle increasing read traffic. It supports
performance-intensive workloads up to 60,000 IOPS and
no extra costs are incurred for extra IO.

CLOUD SPANNER

Cloud Spanner is a globally distributed, ACID-compliant,
relational database. It helps in creating and scaling a
globally replicated database with ease. Cloud Spanner
optimizes performance by automatically sharding the data

based on request load and size of the data, thus improving
business scaling. It enables Point-In-Time-Recovery
(PITR) which provides continuous protection with the
ability to recover past data to microsecond granularity. It is
purpose-built for external, strong, global transactional
consistency and survives regional failure.

It offers low latency, high security, and reliability. It
supports client libraries in C#, C++, Go, JAVA, Node.js,
PHP, Python, and Ruby. It is also compatible with JDBC
drivers for connecting with third-party tools. Cloud
Spanner can be used in services like retail and financial

services, gaming, media, entertainment, technology,
healthcare, etc.

CLOUD BIGTABLE

It is a fully managed, scalable, wide-column store
database for large analytical and operational workloads
with up to 99.999% availability. It is designed with a
storage engine for machine learning applications, which
enhances predictions. It can be integrated with big data
tools like Hadoop, Dataflow, and Dataproc. It also supports
the open-source HBase API standard.

Bigtable supports high read and write throughput at low
latency, providing quick access to large amounts of data.
With Bigtable, there are no manual steps needed to
ensure consistency, data repair, synchronization of writes,
and deletes, which reduces the workload. Bigtable can be
used in areas of personalization, Ad-tech, Fintech, digital
media, and IoT.

FIRESTORE

Firestore is a serverless, scalable, no-maintenance,
document database. It offers a built-in live synchronization

and offline mode. This makes it easy to build multi-user,
collaborative apps on mobile, web, and IoT devices.
Firestore allows us to run sophisticated ACID transactions
against document data. App development can be done
using Firestore client-side development libraries for web,
iOS, Android, Flutter, C++, and Unity. It also supports
server-side development libraries using Node.js, JAVA,
Go, Ruby and PHP. It enables customizable identity-based
security access controls and data validation using a
configuration language. It supports the Database API
where it retains the application’s same performance
characteristics and pricing in the databases, which will be
upgraded automatically to the Cloud Datastore.

It offers multi-region replication and high consistency,
hence surviving natural disasters. Firestore is used for live
asset tracking, activity tracking, real-time analytics, media
and product catalogs, communications, social user
profiles, and gaming leader boards.

FIREBASE REALTIME DATABASE

It is a No-SQL, cloud-hosted database where data is
stored as JSON. It uses accelerated data synchronization
and provides collaborative and immersive experiences
without thinking about networking code. Firebase supports

responsiveness even when offline as Firebase Realtime
Database SDK persists our data to disk. The changes are
synchronized with the current server state once the
connectivity is re-established. Streamline authentication is
used along with firebase authentication to validate users
across database instances. The access methods can be
defined by the developers by leveraging the language:
Firebase Realtime Database Security Rules. This
language defines how the data should be structured when
data can be read from or written to.

The optimization and functionality vary from that of a
relational database as it supports only quick, executable
operations. It is designed to support the responsiveness
required for a great real-time experience for millions of
users. Hence it is important to structure the data according
to the user’s accessibility. Firebase Realtime Database
can be used in areas like mobile signing-in, personalized
apps, and Ads, in-app chats, etc.

MEMORYSTORE

Memorystore is an in-memory database service that
supports both Redis and Memcached. It is used to build
application caches and to perform the migration of caching
layers to the cloud with zero code change. Memorystore is
protected from the internet using VPC networks and

private IP. It comes with IAM integration which offers data
protection. It automates DevOps practices like
provisioning, replication, failovers, and patching.

Memorystore instances can be monitored via cloud
monitoring, where custom alerts can be set up. It can also
be integrated with OpenCensus to get insights on
client-side metrics. It provides 99.9% availability SLA and
automatic failover for both Redis and Memcached. It is
used in areas like caching gaming applications, social
media chat or news feeds.

MONGODB ATLAS

MongoDB Atlas helps to set up, scale, and operate
MongoDB across Google Cloud. Atlas helps in automating
database operations such as cluster deployment and
modification using automated patches. It features to scale
up, scale-out, or scale down via a simple API call or a
push-button, without affecting our applications. It features
Point-In-Time-Recovery by enabling accelerated querying
of back snapshots. It also restores granular datasets in a
fraction of time.

MongoDB Atlas ensures no single point of failure as each
cluster is distributed across the zones in a Google Cloud
region. The product databases are backed up by a
99.95% uptime SLA. It includes optimized dashboards
which highlight key historical metrics, real-time
performance, and customized alerts with the help of
built-in tools. Atlas can be used in areas of mobile, web,
and IoT applications, gaming apps, content management,
and single view applications.