Need advice about which tool to choose?Ask the StackShare community!
Add tool
Google Cloud SQL vs Sequelize: What are the differences?
<Google Cloud SQL and Sequelize are two popular tools used for managing relational databases. In this comparison, we will highlight the key differences between the two.>
1. **Deployment**: Google Cloud SQL is a fully managed database service provided by Google that takes care of deployment, maintenance, and scaling automatically, whereas Sequelize is an ORM for Node.js that requires setting up and managing the database environment manually.
2. **Language Support**: Google Cloud SQL supports multiple languages and frameworks, including Java, Python, and PHP, while Sequelize is specifically designed for Node.js applications, providing a seamless integration with Node.js projects.
3. **Scalability**: Google Cloud SQL offers automatic scaling capabilities allowing the database to handle increased loads efficiently, whereas Sequelize lacks built-in scalability features and may require manual intervention to scale the database.
4. **Cost Structure**: Google Cloud SQL charges users based on usage metrics like storage, CPU, and network traffic, while Sequelize is an open-source library with no direct cost associated with its usage, making it a cost-effective solution for smaller projects.
5. **Data Migration**: Google Cloud SQL provides tools and mechanisms to easily migrate data to and from different databases, simplifying the data migration process, whereas Sequelize may require custom scripts or third-party tools for data migration, adding complexity to the migration process.
In Summary, Google Cloud SQL offers a fully managed database service with automatic scalability and deployment, suitable for multi-language applications, while Sequelize is a Node.js-specific ORM that requires manual database management but provides cost-effective solutions for smaller projects.
Get Advice from developers at your company using StackShare Enterprise. Sign up for StackShare Enterprise.
Learn MorePros of Google Cloud SQL
Pros of Sequelize
Pros of Google Cloud SQL
- Fully managed13
- Backed by Google10
- SQL10
- Flexible4
- Encryption at rest and transit3
- Automatic Software Patching3
- Replication across multiple zone by default3
Pros of Sequelize
- Good ORM for node.js42
- Easy setup31
- Support MySQL & MariaDB, PostgreSQL, MSSQL, Sqlite21
- Open source14
- Free13
- Promise Based12
- Recommend for mongoose users4
- Typescript3
- Atrocious documentation, buggy, issues closed by bots3
Sign up to add or upvote prosMake informed product decisions
Cons of Google Cloud SQL
Cons of Sequelize
Cons of Google Cloud SQL
Be the first to leave a con
Cons of Sequelize
- Docs are awful30
- Relations can be confusing10
Sign up to add or upvote consMake informed product decisions
- No public GitHub repository available -
What is 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.
What is Sequelize?
Sequelize is a promise-based ORM for Node.js and io.js. It supports the dialects PostgreSQL, MySQL,
MariaDB, SQLite and MSSQL and features solid transaction support, relations, read replication and
more.
Need advice about which tool to choose?Ask the StackShare community!
What companies use Google Cloud SQL?
What companies use Sequelize?
See which teams inside your own company are using Google Cloud SQL or Sequelize.
Sign up for StackShare EnterpriseLearn MoreSign up to get full access to all the companiesMake informed product decisions
What tools integrate with Google Cloud SQL?
What tools integrate with Sequelize?
What tools integrate with Google Cloud SQL?
What tools integrate with Sequelize?
Sign up to get full access to all the tool integrationsMake informed product decisions
What are some alternatives to Google Cloud SQL and Sequelize?
MySQL
The MySQL software delivers a very fast, multi-threaded, multi-user, and robust SQL (Structured Query Language) database server. MySQL Server is intended for mission-critical, heavy-load production systems as well as for embedding into mass-deployed software.
Apache Aurora
Apache Aurora is a service scheduler that runs on top of Mesos, enabling you to run long-running services that take advantage of Mesos' scalability, fault-tolerance, and resource isolation.
Google Cloud Datastore
Use a managed, NoSQL, schemaless database for storing non-relational data. Cloud Datastore automatically scales as you need it and supports transactions as well as robust, SQL-like queries.
Google Cloud Spanner
It is a globally distributed database service that gives developers a production-ready storage solution. It provides key features such as global transactions, strongly consistent reads, and automatic multi-site replication and failover.
PostgreSQL
PostgreSQL is an advanced object-relational database management system
that supports an extended subset of the SQL standard, including
transactions, foreign keys, subqueries, triggers, user-defined types
and functions.