Database Solutions with Google Cloud Platform (GCP)

Google Cloud Platform (GCP) is among the most trusted cloud computing services in the modern era, competing with the likes of Microsoft Azure and Amazon Web Services (AWS). It is more than just a platform bearing Google’s name, however; it is also the same cloud service that powers its own services like Google’s search engine, GMail and Drive. Based on the presumed immense volume of these undertakings, organizations can be sure that GCP can manage database needs of any size.  Figuring out where to jump in can be daunting, though, especially for companies that are new to cloud computing, so we’ve assembled this article to provide the basics about using the platform for business. 

Whether part of a hybrid, multi-cloud or all-in strategy Google Cloud Platform (GCP) has world class tools and infrastructure to propel industry out of IT management and into IT enablement. Foghorn has the expertise to guide you on this journey, assisting your team to build, scale, automate and leave potential in rear view mirror.

In this text, we’ll cover:

• Google Cloud Storage
• Cloud SQL
• Cloud BigTable
• Cloud Spanner
• Cloud Memorystore
• Cloud Firestore
• AlloyDB for PostgreSQL

Google Cloud Storage

‘Google Cloud Storage’ is the object storage service offered by Google Cloud, combining the performance and scalability of Google’s cloud with advanced sharing and security capabilities. It deploys in three primary forms:

• Single Cloud – This is the most straightforward way to become cloud-enabled, where the entire workload is migrated from on-site to a virtual database. The database can be moved from its on-site configuration with minimal changes, or created from scratch using raw data that is entered into a new Google Cloud database.
• Hybrid Cloud – This method involves moving a portion of the workload to the cloud, while maintaining its on-site presence. Hybrid clouds are useful for scenarios that require both on-site and digitized data, such as a case where the local data is used for application development and testing, but the cloud database is used for production or the application’s backend.
• Multi-cloud solutions – For organizations that already employ different cloud databases but want to leverage Google Cloud’s features, multi-cloud solutions allow two or more databases to be integrated. GCP provides several cloud migration tools that allow for several cloud platforms to work in sync. A multi-cloud solution would be useful for a company that wants to leverage the analytics of one cloud while maintaining the familiar structure of nother.

Cloud SQL

Cloud SQL combines the fully-managed convenience of SQL with the versatility and features of Google Cloud to provide a Database as a Service. The trustworthy relational blueprints of PostgreSQL, MySQL, and Microsoft’s SQL Server should be familiar to any experienced database user. 

Cloud SQL allows for the infrastructure-as-code necessary to support Foghorn’s DevSecOps for application development which inserts security at each step, while also providing content management capability. The need for on-site management means that Cloud SQL is geared for hybrid cloud infrastructure.

Cloud Bigtable

Bigtable is a NoSQL database that operates on a two-dimensional key-value store rather than the tabular setup of many databases. This allows for management of large-scale data sets–hence the “big” in BigTable–with millions of query requests per second. These attributes work very well with applications that can’t afford downtime to work effectively, such as IoT, finance (fintech), and marketing applications that use artificial intelligence (hyper personalization).

Cloud Spanner

Spanner is a relational, fully-managed database that thrives on near-perfect availability (99.9%), maximum scalability, and optimized performance. These attributes are set up for immense workloads such as systems with millions of users or data sets that are constantly growing. Numerous use cases indicate that Cloud Spanner integrates very well with BigTable to create dependable integrated systems for enormous databases.

Cloud MemoryStore

Memorystore works with Redis and Memcached to provide an in-memory data store that has near-zero latency and 99.9% availability. Contrasting with stores intended for large databases, MemoryStore is only concerned with caching data for instant retrieval, making it deal for real-time operations like gaming, as well as experimentation for artificial intelligence and machine learning.

Cloud Firestore

Firestore is a scalable NoSQL database designed to work with Google’s Firebase, a mobile application development platform. It can sync data across multiple Google Cloud solutions to provide automation and a hierarchical structure, which allows developers to focus on building the actual application instead of data management.

AlloyDB for PostgreSQL

AlloyDB is the evolution of Google’s F1, a scalable distributed database service that has been modified to work perfectly with PostgreSQL. The result is a system that is four times faster for transactional data and a hundred times faster for analytics than standard PostgreSQL. Its high availability SLA makes AlloyDB for PostgreSQL a good choice for enterprise software that depends on consistency.

Need More Help With Google Cloud?

As with most of its services, Google’s cloud offering is built on integration. This includes integration between the solutions in its own cloud platform, but also easy migrations and transfers between different platforms like MySQL and PostgreSQL. As indicated by the ideal uses mentioned in each entry, which one you choose depends on the needs of your company.

Even armed with this information, selecting the right cloud solution for your organization can still be a daunting task for some companies, especially those without an embedded IT department. Foghorn Consulting remains available to provide deeper information about which fits your workloads, as well as the managed IT services required for continued effectiveness.