Google Cloud Platform offers a robust set of database services, catering to a wide spectrum of application and workload requirements. These database services within GCP are designed to provide scalable, high-performance, and fully managed solutions for storing, managing, and retrieving data.
Vast Edge delivers GCP Database services through a strategic and client-centric approach, combining expertise, best practices, and a commitment to meeting the specific data management needs of organizations.

GCP Database Offerings

These services cover a range of database and data processing needs, from traditional relational databases to NoSQL databases, in-memory data stores, data warehousing, and more. The choice of the database service depends on factors such as data structure, volume, performance requirements, and application architecture.

Fundamental Elements of Vast Edge's Approach

Assessment and Requirement Analysis

Vast Edge commences with a comprehensive assessment to understand the client's specific data management needs. This involves a detailed analysis of data types, scalability requirements, and the unique use cases that GCP Database services can effectively address.

Strategic Planning

Based on the assessment findings, Vast Edge formulates a strategic plan that serves as a blueprint for the optimal utilization of GCP Database services. This plan is intricately designed to align with the client's business objectives, ensuring a robust and tailored data management strategy.

Database Selection and Configuration

Vast Edge assists clients in selecting the most suitable GCP Database service for their requirements. Whether it involves relational databases through Cloud SQL, NoSQL solutions with Cloud Firestore, or other offerings, Vast Edge ensures the precise match for the client's data management needs.

Implementation and Migration

Vast Edge oversees the seamless implementation and migration process to GCP Database services. This includes deploying databases, configuring settings, and executing meticulous data migration strategies to ensure a smooth transition with minimal disruption.

Performance Optimization

Vast Edge prioritizes the optimization of GCP Database service performance. This entails fine-tuning configurations, ensuring efficient resource utilization, and implementing industry best practices to enhance overall database responsiveness.

Security and Compliance

The security and compliance aspects of GCP Database services are paramount for Vast Edge. This involves implementing robust security measures, encryption protocols, and access controls to align with industry compliance standards and protect the integrity of client data.

Monitoring and Maintenance:

Vast Edge provides continuous monitoring and maintenance services for GCP databases. This proactive approach involves real-time performance monitoring, early issue detection, and the timely application of updates to uphold a secure and optimized database environment.

Backup and Disaster Recovery

Vast Edge implements resilient backup and disaster recovery strategies for GCP databases. This ensures data integrity and provides the capability for swift recovery in the event of unforeseen disruptions.

Google Cloud SQL

Google Cloud SQL is a fully managed relational database service provided by Google Cloud Platform (GCP). It enables users to deploy, manage, and scale relational databases in the cloud without the need to handle the administrative tasks associated with database management.

Your Vision, Our Expertise

Elevating Your Software Product Engineering Journey with Vast Edge

Key Aspects of GCP Cloud SQL:

GCP Cloud SQL is suitable for a wide range of applications that require a relational database, and its managed nature simplifies database administration tasks, allowing developers to focus on building and scaling applications.

AlloyDB

AlloyDB for PostgreSQL is a fully managed, PostgreSQL-compatible database service that's designed for your most demanding workloads, including hybrid transactional and analytical processing. AlloyDB pairs a Google-built database engine with a cloud-based, multi-node architecture to deliver enterprise-grade performance, reliability, and availability.

How AlloyDB works

An application connects to AlloyDB instances using standard PostgreSQL protocols and techniques. The application then uses PostgreSQL query syntax to work with the database.
Under the surface, AlloyDB utilizes a cloud-based hierarchy of components and features that are designed to maximize the availability of your data and optimize query performance and throughput. Google Cloud administrative tools let you monitor the health of your AlloyDB deployment, adjusting its scale and size to best fit the changing demands of your workload.

AlloyDB Nodes and instances

A cluster contains several nodes, which are virtual machine instances that are dedicated to running the PostgreSQL-compatible database engine that applications use to query your cluster's data. AlloyDB organizes nodes into instances, each of which has a private, static IP address in your VPC. In practice, your applications connect to instances at these IP addresses using PostgreSQL protocols. The instances then pass SQL queries to their nodes

AlloyDB has two kinds of instances:

AlloyDB Key Features

GCP Spanner

Google Cloud Spanner is a globally distributed, horizontally scalable, and strongly consistent database service provided by Google Cloud Platform (GCP). It is designed to seamlessly integrate the best features of traditional relational databases with the benefits of cloud-native NoSQL databases.

Key Aspects of Google Cloud Spanner:

Google Cloud Spanner is a powerful and versatile database service that is well-suited for applications requiring global distribution, strong consistency, and seamless scalability. It's commonly used in scenarios where traditional databases may face challenges in meeting the demands of a global and distributed architecture.

GCP BigTable & Big Query

Google Cloud Platform (GCP) offers two distinct services for handling large-scale data processing and analytics: Bigtable and BigQuery. Both services are designed to manage and analyze massive datasets, but they have different use cases and characteristics.

	Big Table	Big Query
Type	NoSQL big data database service.	Fully managed serverless data warehouse and analytics platform.
Use Case	Ideal for handling large amounts of data with high read and write throughput.	Ideal for running ad-hoc SQL queries on large datasets for analytics and business intelligence.
Data Model	Wide-column store (NoSQL).	SQL-based (relational).
Scalability	Horizontally scalable for both storage and throughput.	Automatically scales to handle large datasets and complex queries.
Performance	Designed for low-latency data access with high throughput.	Provides high-speed SQL queries using a massively parallel processing (MPP) architecture.
Integration	Integrates well with other Google Cloud services like Apache, HBase, Apache Beam, and more.	Easily integrates with various BI tools, data preparation tools, and data connectors.
Query Language	Bigtable doesn't use SQL; instead, it provides APIs for data access.	BigQuery uses SQL for querying.
When to Choose	when you need real-time, low-latency access to large amounts of operational data.	when you need to perform complex analytics and queries on large datasets.

Firestore

Firestore is a fully managed, NoSQL document database service provided by Google Cloud Platform (GCP). It is designed to store and synchronize data for web, mobile, and server applications in real-time. Firestore is part of the Firebase suite of products, but it is also available as a standalone service on GCP.

Key Features of Firestore

Firestore is suitable for a wide range of applications, including mobile and web apps, where real-time synchronization and scalability are crucial. It is often used for scenarios like user profiles, chat applications, collaborative editing, and more. Firestore's ease of use and real-time capabilities make it a popular choice for developers building modern, responsive applications.

Recovery Point Objective (RPO) & Recovery Time Objective (RTO)

Google Cloud Platform (GCP) provides a range of services and features that can contribute to achieving specific Recovery Point Objective (RPO) and Recovery Time Objective (RTO) goals in the context of disaster recovery and business continuity. The actual RPO and RTO values will depend on the specific configurations and strategies implemented by the organization.

Here are some considerations related to RPO and RTO in the context of GCP:

It's important for organizations to work closely with their IT and operations teams to assess specific RPO and RTO requirements based on business needs and risk tolerance. Additionally, regular testing and simulation of disaster recovery scenarios are crucial to ensure that the defined objectives can be met in practice

GCP DBs: BigQuery, Spanner, Atlas, Alloy, Cloud SQL, Firebase, BigTable