What is Cloud DB for Mysql and what are its top alternatives?
Cloud DB for MySQL is a cloud-based database service that allows users to store, manage, and access their MySQL databases on the cloud. It provides features such as automatic backups, high availability, scalability, and security. However, some limitations of Cloud DB for MySQL include potential vendor lock-in, limited control over the underlying infrastructure, and potential performance issues due to shared resources in the cloud environment.
- Amazon RDS: Amazon RDS is a managed database service that supports MySQL along with other database engines. It offers features such as automated backups, monitoring, and replication. Pros: Scalability, automatic backups, monitoring. Cons: Limited control over underlying infrastructure.
- Google Cloud SQL: Google Cloud SQL is a fully managed MySQL database service on Google Cloud Platform. It provides features like automated backups, monitoring, and replication. Pros: Integration with Google Cloud Platform, automatic failover. Cons: Limited control over the underlying infrastructure.
- Microsoft Azure Database for MySQL: Microsoft Azure Database for MySQL is a fully managed MySQL database service on Azure. It offers features like automated backups, monitoring, and scalability. Pros: Integration with Azure ecosystem, high availability. Cons: Limited control over underlying infrastructure.
- DigitalOcean Managed Databases: DigitalOcean Managed Databases offer managed MySQL databases with features such as automated backups, monitoring, and scaling. Pros: Simplified management, cost-effective pricing. Cons: Limited scalability options.
- Heroku Postgres: Heroku Postgres is a managed PostgreSQL database service that also supports MySQL via add-ons. It provides features like dataclips, monitoring, and automatic backups. Pros: Easy integration with Heroku platform, built-in data protection. Cons: Limited support for MySQL compared to PostgreSQL.
- Cloud SQL by ScaleGrid: Cloud SQL by ScaleGrid is a fully managed MySQL database service that offers features like performance optimization, backup automation, and monitoring. Pros: Performance optimization options, customizable backup schedules. Cons: Limited availability compared to major cloud providers.
- Aiven: Aiven is a managed cloud database service that supports MySQL along with other databases. It offers features like automatic scaling, monitoring, and backups. Pros: Multi-cloud support, easy integration with popular platforms. Cons: Limited customization options.
- Alibaba Cloud ApsaraDB for RDS: Alibaba Cloud ApsaraDB for RDS is a managed database service that supports MySQL among other database engines. It provides features like automatic monitoring, backups, and disaster recovery. Pros: Integration with Alibaba Cloud ecosystem, high availability. Cons: Limited international presence.
- Oracle MySQL Database Service: Oracle MySQL Database Service is a managed MySQL database service on Oracle Cloud. It offers features like automated backups, monitoring, and high availability. Pros: Integration with Oracle Cloud ecosystem, high performance. Cons: Limited support for non-Oracle technologies.
- Vultr High-Performance Managed MySQL: Vultr offers a high-performance managed MySQL database service with features like automatic backups, monitoring, and scalability. Pros: High-performance infrastructure, cost-effective pricing. Cons: Limited additional features compared to major cloud providers.
Top Alternatives to Cloud DB for Mysql
- Amazon RDS
Amazon RDS gives you access to the capabilities of a familiar MySQL, Oracle or Microsoft SQL Server database engine. This means that the code, applications, and tools you already use today with your existing databases can be used with Amazon RDS. Amazon RDS automatically patches the database software and backs up your database, storing the backups for a user-defined retention period and enabling point-in-time recovery. You benefit from the flexibility of being able to scale the compute resources or storage capacity associated with your Database Instance (DB Instance) via a single API call. ...
- Amazon Aurora
Amazon Aurora is a MySQL-compatible, relational database engine that combines the speed and availability of high-end commercial databases with the simplicity and cost-effectiveness of open source databases. Amazon Aurora provides up to five times better performance than MySQL at a price point one tenth that of a commercial database while delivering similar performance and availability. ...
- Google Cloud SQL
Run the same relational databases you know with their rich extension collections, configuration flags and developer ecosystem, but without the hassle of self management. ...
- Azure SQL Database
It is the intelligent, scalable, cloud database service that provides the broadest SQL Server engine compatibility and up to a 212% return on investment. It is a database service that can quickly and efficiently scale to meet demand, is automatically highly available, and supports a variety of third party software. ...
- PlanetScaleDB
It is a fully managed cloud native database-as-a-service built on Vitess and Kubernetes. A MySQL compatible highly scalable database. Effortlessly deploy, manage, and monitor your databases in multiple regions and across cloud providers. ...
- DigitalOcean Managed Databases
Build apps and store data in minutes with easy access to one or more databases and sleep better knowing your data is backed up and optimized. ...
- Azure Database for MySQL
Azure Database for MySQL provides a managed database service for app development and deployment that allows you to stand up a MySQL database in minutes and scale on the fly – on the cloud you trust most. ...
- Books
It is an immutable double-entry accounting database service. It supports many clients and businesses at global scale, leaning on Google Cloud Spanner and Google Kubernetes Engine to make that possible. ...
Cloud DB for Mysql alternatives & related posts
Amazon RDS
- Reliable failovers165
- Automated backups156
- Backed by amazon130
- Db snapshots92
- Multi-availability87
- Control iops, fast restore to point of time30
- Security28
- Elastic24
- Push-button scaling20
- Automatic software patching20
- Replication4
- Reliable3
- Isolation2
related Amazon RDS posts
I'm planning to create a web application and also a mobile application to provide a very good shopping experience to the end customers. Shortly, my application will be aggregate the product details from difference sources and giving a clear picture to the user that when and where to buy that product with best in Quality and cost.
I have planned to develop this in many milestones for adding N number of features and I have picked my first part to complete the core part (aggregate the product details from different sources).
As per my work experience and knowledge, I have chosen the followings stacks to this mission.
UI: I would like to develop this application using React, React Router and React Native since I'm a little bit familiar on this and also most importantly these will help on developing both web and mobile apps. In addition, I'm gonna use the stacks JavaScript, jQuery, jQuery UI, jQuery Mobile, Bootstrap wherever required.
Service: I have planned to use Java as the main business layer language as I have 7+ years of experience on this I believe I can do better work using Java than other languages. In addition, I'm thinking to use the stacks Node.js.
Database and ORM: I'm gonna pick MySQL as DB and Hibernate as ORM since I have a piece of good knowledge and also work experience on this combination.
Search Engine: I need to deal with a large amount of product data and it's in-detailed info to provide enough details to end user at the same time I need to focus on the performance area too. so I have decided to use Solr as a search engine for product search and suggestions. In addition, I'm thinking to replace Solr by Elasticsearch once explored/reviewed enough about Elasticsearch.
Host: As of now, my plan to complete the application with decent features first and deploy it in a free hosting environment like Docker and Heroku and then once it is stable then I have planned to use the AWS products Amazon S3, EC2, Amazon RDS and Amazon Route 53. I'm not sure about Microsoft Azure that what is the specialty in it than Heroku and Amazon EC2 Container Service. Anyhow, I will do explore these once again and pick the best suite one for my requirement once I reached this level.
Build and Repositories: I have decided to choose Apache Maven and Git as these are my favorites and also so popular on respectively build and repositories.
Additional Utilities :) - I would like to choose Codacy for code review as their Startup plan will be very helpful to this application. I'm already experienced with Google CheckStyle and SonarQube even I'm looking something on Codacy.
Happy Coding! Suggestions are welcome! :)
Thanks, Ganesa
As we've evolved or added additional infrastructure to our stack, we've biased towards managed services. Most new backing stores are Amazon RDS instances now. We do use self-managed PostgreSQL with TimescaleDB for time-series data—this is made HA with the use of Patroni and Consul.
We also use managed Amazon ElastiCache instances instead of spinning up Amazon EC2 instances to run Redis workloads, as well as shifting to Amazon Kinesis instead of Kafka.
Amazon Aurora
- MySQL compatibility14
- Better performance12
- Easy read scalability10
- Speed9
- Low latency read replica7
- High IOPS cost2
- Good cost performance1
- Vendor locking2
- Rigid schema1
related Amazon Aurora posts
Back in 2014, I was given an opportunity to re-architect SmartZip Analytics platform, and flagship product: SmartTargeting. This is a SaaS software helping real estate professionals keeping up with their prospects and leads in a given neighborhood/territory, finding out (thanks to predictive analytics) who's the most likely to list/sell their home, and running cross-channel marketing automation against them: direct mail, online ads, email... The company also does provide Data APIs to Enterprise customers.
I had inherited years and years of technical debt and I knew things had to change radically. The first enabler to this was to make use of the cloud and go with AWS, so we would stop re-inventing the wheel, and build around managed/scalable services.
For the SaaS product, we kept on working with Rails as this was what my team had the most knowledge in. We've however broken up the monolith and decoupled the front-end application from the backend thanks to the use of Rails API so we'd get independently scalable micro-services from now on.
Our various applications could now be deployed using AWS Elastic Beanstalk so we wouldn't waste any more efforts writing time-consuming Capistrano deployment scripts for instance. Combined with Docker so our application would run within its own container, independently from the underlying host configuration.
Storage-wise, we went with Amazon S3 and ditched any pre-existing local or network storage people used to deal with in our legacy systems. On the database side: Amazon RDS / MySQL initially. Ultimately migrated to Amazon RDS for Aurora / MySQL when it got released. Once again, here you need a managed service your cloud provider handles for you.
Future improvements / technology decisions included:
Caching: Amazon ElastiCache / Memcached CDN: Amazon CloudFront Systems Integration: Segment / Zapier Data-warehousing: Amazon Redshift BI: Amazon Quicksight / Superset Search: Elasticsearch / Amazon Elasticsearch Service / Algolia Monitoring: New Relic
As our usage grows, patterns changed, and/or our business needs evolved, my role as Engineering Manager then Director of Engineering was also to ensure my team kept on learning and innovating, while delivering on business value.
One of these innovations was to get ourselves into Serverless : Adopting AWS Lambda was a big step forward. At the time, only available for Node.js (Not Ruby ) but a great way to handle cost efficiency, unpredictable traffic, sudden bursts of traffic... Ultimately you want the whole chain of services involved in a call to be serverless, and that's when we've started leveraging Amazon DynamoDB on these projects so they'd be fully scalable.
Over the years we have added a wide variety of different storages to our stack including PostgreSQL (some hosted by Heroku, some by Amazon RDS) for storing relational data, Amazon DynamoDB to store non-relational data like recommendations & user connections, or Redis to hold pre-aggregated data to speed up API endpoints.
Since we started running Postgres ourselves on RDS instead of only using the managed offerings of Heroku, we've gained additional flexibility in scaling our application while reducing costs at the same time.
We are also heavily testing Amazon RDS for Aurora in its Postgres-compatible version and will also give the new release of Aurora Serverless a try!
#SqlDatabaseAsAService #NosqlDatabaseAsAService #Databases #PlatformAsAService
Google Cloud SQL
- Fully managed13
- Backed by Google10
- SQL10
- Flexible4
- Encryption at rest and transit3
- Automatic Software Patching3
- Replication across multiple zone by default3
related Google Cloud SQL posts
We use Go for the first-off due to our knowledge of it. Second off, it's highly performant and optimized for scalability. We run it using dockerized containers for our backend REST APIs.
For Frontend, we use React with Next.js at vercel. We use NextJS here mostly due to our need for Server Side Rendering and easier route management.
For Database, we use MySQL as it is first-off free and always has been in use with us. We use Google Cloud SQL from GCP that manages its storage and versions along with HA.
All stacks are free to use and get the best juice out of the system. We also use Redis for caching for enterprise-grade apps where data retrieval latency matters the most.
As far as the backend goes, we first had to decide which database will power most of Daily services. Considering relational databases vs document datbases, we decided that the relational model is a better fit for Daily as we have a lot of connections between the different entities. At the time MySQL was the only service available on Google Cloud SQL so this was out choice. In terms of #backend development Node.js powers most of our services, thanks to its amazing ecosystem there are a lot of modules publicly available to shorten the development time. Go is for the light services which are all about performance and delivering quickly the response, such as our redirector service.
- Managed6
- Secure4
- Scalable3
related Azure SQL Database posts
Hi, I am trying to build a billing system for utilities. It will have a web app and a mobile app too. The USP of this system would be that the mobile application would support offline syncing, basically, let's say while doing the payment the internet goes down then when it's back the payment goes through. Basically, some features could work offline. So I am confused as to which DB to go for. A relational one like Azure SQL Database or a non-relational one like MongoDB?