ElephantSQL vs Google Cloud SQL for PostgreSQL

Overview

ElephantSQL

Stacks15

Followers86

Votes15

Google Cloud SQL for PostgreSQL

Stacks142

Followers106

Votes0

ElephantSQL vs Google Cloud SQL for PostgreSQL: What are the differences?

Introduction

This Markdown code presents the key differences between ElephantSQL and Google Cloud SQL for PostgreSQL. Both are cloud-based PostgreSQL database services, but they have several differences that set them apart.

1. Pricing Model: ElephantSQL offers a simple and transparent pricing model, with costs based on the size of the database and the resources used. On the other hand, Google Cloud SQL for PostgreSQL has a more complex pricing structure, where costs are determined by factors such as CPU usage, storage, and network egress.

2. Managed Service Offerings: ElephantSQL provides a fully managed service, where the database infrastructure and maintenance tasks are handled by their team. With Google Cloud SQL for PostgreSQL, while it is also a managed service, there is more flexibility and control over the database configuration and management tasks.

3. Scalability: ElephantSQL offers automatic vertical scaling, allowing users to easily increase or decrease the resources allocated to their database. On the contrary, Google Cloud SQL for PostgreSQL supports both vertical and horizontal scaling. This means that users can add more resources to a single instance or distribute the workload across multiple instances.

4. Integration with Other Services: Google Cloud SQL for PostgreSQL has seamless integration with other Google Cloud services such as Google Cloud Storage, BigQuery, and Dataflow. These integrations enable users to leverage the full power of the Google Cloud ecosystem for data storage, analytics, and processing. ElephantSQL, on the other hand, does not provide such integrations and primarily focuses on providing a robust PostgreSQL database service.

5. Backup and Recovery: ElephantSQL offers automatic daily backups and allows users to create manual backups for point-in-time recovery. Google Cloud SQL for PostgreSQL also provides automated backups but offers additional features such as backups encryption and manual backups restoration.

6. Data Centers and Regions: ElephantSQL provides data centers in multiple regions around the world, including Europe, North America, and Asia. However, the selection of specific regions for database deployment may be limited. In contrast, Google Cloud SQL for PostgreSQL allows users to choose from a wide range of data centers and regions, offering more flexibility when it comes to choosing the geographical location for database hosting.

In summary, ElephantSQL and Google Cloud SQL for PostgreSQL differ in their pricing models, managed service offerings, scalability options, integration with other services, backup and recovery features, as well as the availability of data centers and regions for database deployment.

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Advice on ElephantSQL, Google Cloud SQL for PostgreSQL

Jorge

Jan 15, 2020

Needs advice

Considering moving part of our PostgreSQL database infrastructure to the cloud, however, not quite sure between AWS, Heroku, Azure and Google cloud. Things to consider: The main reason is for backing up and centralize all our data in the cloud. With that in mind the main elements are: -Pricing for storage. -Small team. -No need for high throughput. -Support for docker swarm and Kubernetes.

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Detailed Comparison

ElephantSQL	Google Cloud SQL for PostgreSQL
ElephantSQL hosts PostgreSQL on Amazon EC2 in multiple regions and availability zones. The servers are continuously transferring the Write-Ahead-Log (the transaction log) to S3 for maximum reliability.	With Cloud SQL for PostgreSQL, you can spend less time on your database operations and more time on your applications.
Continuous backup to S3;Automatic failover;24/7 monitoring;Extenstions- HStore, Full Text search, Crypto and many more.;Latest version- ElephantSQL always boosts the latest stable version of PostgreSQL.	-
Statistics
Stacks 15	Stacks 142
Followers 86	Followers 106
Votes 15	Votes 0
Pros & Cons
Pros 11 They suck 1 Easy setup 1 Easy backup 1 Monitoring 1 Geospatial support	No community feedback yet
Integrations
SoftLayer Google Compute Engine Amazon EC2 Heroku AppHarbor cloudControl	Google App Engine Google Compute Engine PostgreSQL

What are some alternatives to ElephantSQL, Google Cloud SQL for PostgreSQL?

Amazon RDS for PostgreSQL

Amazon RDS manages complex and time-consuming administrative tasks such as PostgreSQL software installation and upgrades, storage management, replication for high availability and back-ups for disaster recovery. With just a few clicks in the AWS Management Console, you can deploy a PostgreSQL database with automatically configured database parameters for optimal performance. Amazon RDS for PostgreSQL database instances can be provisioned with either standard storage or Provisioned IOPS storage. Once provisioned, you can scale from 10GB to 3TB of storage and from 1,000 IOPS to 30,000 IOPS.

Heroku Postgres

Heroku Postgres provides a SQL database-as-a-service that lets you focus on building your application instead of messing around with database management.

Database Labs

We manage an optimized Postgres image. You focus on your core app, not on becoming a database administrator.

Azure Database for PostgreSQL

Azure Database for PostgreSQL provides a managed database service for app development and deployment that allows you to stand up a PostgreSQL database in minutes and scale on the fly – on the cloud you trust most.

Neon Database

It is a fully managed serverless PostgreSQL. Neon separates storage and compute to offer modern developer features such as serverless, branching, bottomless storage, and more.

Amazon Aurora PostgreSQL

It is a fully managed, PostgreSQL–compatible, and ACID–compliant relational database engine that combines the speed, reliability, and manageability of Amazon Aurora with the simplicity and cost-effectiveness of open-source databases.

Crunchy Bridge

It is a fully-managed database as a service. It takes care of backups, high availability, monitoring. Additionally, it is multi-cloud supporting AWS and Azure and comes with PL/Python3u and PL/R for more powerful work.

Vercel Postgres

It enables you to create scalable, secure PostgreSQL databases. You should use Vercel Postgres if you need to manage customer profiles, user-generated content, financial transaction processing, or other complex data.

PaaS DB PostgreSQL

A simple product to get an operational database without any pain about server management, security settings and upgrading. We provide resources to instanciate your database (PostgreSQL 9.4). Our goal is to propose this service with an hourly billing.

Related Comparisons

ElephantSQL vs Google Cloud SQL for PostgreSQL: What are the differences?

Introduction

1. Pricing Model: ElephantSQL offers a simple and transparent pricing model, with costs based on the size of the database and the resources used. On the other hand, Google Cloud SQL for PostgreSQL has a more complex pricing structure, where costs are determined by factors such as CPU usage, storage, and network egress.

2. Managed Service Offerings: ElephantSQL provides a fully managed service, where the database infrastructure and maintenance tasks are handled by their team. With Google Cloud SQL for PostgreSQL, while it is also a managed service, there is more flexibility and control over the database configuration and management tasks.

3. Scalability: ElephantSQL offers automatic vertical scaling, allowing users to easily increase or decrease the resources allocated to their database. On the contrary, Google Cloud SQL for PostgreSQL supports both vertical and horizontal scaling. This means that users can add more resources to a single instance or distribute the workload across multiple instances.

4. Integration with Other Services: Google Cloud SQL for PostgreSQL has seamless integration with other Google Cloud services such as Google Cloud Storage, BigQuery, and Dataflow. These integrations enable users to leverage the full power of the Google Cloud ecosystem for data storage, analytics, and processing. ElephantSQL, on the other hand, does not provide such integrations and primarily focuses on providing a robust PostgreSQL database service.

5. Backup and Recovery: ElephantSQL offers automatic daily backups and allows users to create manual backups for point-in-time recovery. Google Cloud SQL for PostgreSQL also provides automated backups but offers additional features such as backups encryption and manual backups restoration.

6. Data Centers and Regions: ElephantSQL provides data centers in multiple regions around the world, including Europe, North America, and Asia. However, the selection of specific regions for database deployment may be limited. In contrast, Google Cloud SQL for PostgreSQL allows users to choose from a wide range of data centers and regions, offering more flexibility when it comes to choosing the geographical location for database hosting.

In summary, ElephantSQL and Google Cloud SQL for PostgreSQL differ in their pricing models, managed service offerings, scalability options, integration with other services, backup and recovery features, as well as the availability of data centers and regions for database deployment.

ElephantSQL vs Google Cloud SQL for PostgreSQL

Overview

ElephantSQL vs Google Cloud SQL for PostgreSQL: What are the differences?

Introduction

5. Backup and Recovery: ElephantSQL offers automatic daily backups and allows users to create manual backups for point-in-time recovery. Google Cloud SQL for PostgreSQL also provides automated backups but offers additional features such as backups encryption and manual backups restoration.