Software Alternatives, Accelerators & Startups

MongoDB VS Google Cloud SQL

Compare MongoDB VS Google Cloud SQL and see what are their differences

MongoDB logo MongoDB

MongoDB (from "humongous") is a scalable, high-performance NoSQL database.

Google Cloud SQL logo Google Cloud SQL

Google Cloud SQL is a fully-managed database service that makes it easy to set-up, maintain, manage and administer your MySQL database.
  • MongoDB Landing page
    Landing page //
    2023-10-21
  • Google Cloud SQL Landing page
    Landing page //
    2023-09-18

MongoDB features and specs

  • Scalability
    MongoDB offers horizontal scaling through sharding, allowing it to handle large volumes of data and enabling distributed computing.
  • Flexible Schema
    It allows for a flexible schema design using BSON (Binary JSON), making it easier to iterate and change application data models.
  • High Performance
    MongoDB is optimized for read and write throughput, making it suitable for real-time applications.
  • Rich Query Language
    Supports a rich and expressive query language that allows for efficient querying and analytics.
  • Built-in Replication
    Provides robust replication mechanisms for high availability and redundancy.
  • Geospatial Indexing
    Offers powerful geospatial indexing capabilities, useful for location-based applications.
  • Aggregation Framework
    Enables complex data manipulations and transformations using the aggregation pipeline framework.
  • Cross-Platform
    Works on multiple operating systems, enhancing its versatility and deployment options.

Possible disadvantages of MongoDB

  • Memory Usage
    MongoDB can consume a large amount of memory due to its use of memory-mapped files, which may be a concern for some applications.
  • Complex Transactions
    While MongoDB supports ACID transactions, they can be more complex to implement and less efficient compared to traditional relational databases.
  • Data Redundancy
    The flexible schema design can lead to data redundancy and increased storage costs if not managed carefully.
  • Limited Joins
    Joins are supported but can be less efficient and more limited compared to relational databases, affecting complex relational data querying.
  • Indexing Overhead
    Extensive indexing can introduce overhead and impact performance, especially during write operations.
  • Learning Curve
    Requires a different mindset and understanding compared to traditional relational databases, which can present a learning curve for new users.
  • Lacks Mature Analytical Tools
    The ecosystem for analytical tools around MongoDB is not as mature as those for traditional relational databases, which might limit advanced analytics capabilities.
  • Cost
    The cost of using MongoDB's cloud services (MongoDB Atlas) can be high, especially for large-scale deployments.

Google Cloud SQL features and specs

  • Fully Managed Service
    Google Cloud SQL handles maintenance, backups, and updates, allowing developers to focus on application development rather than database management tasks.
  • Scalability
    Easily scale vertically by upgrading to more powerful machine types or horizontally to handle increased workload without manual intervention.
  • High Availability
    Google Cloud SQL offers automatic failover, replication, and backup, ensuring minimal downtime and data preservation in case of failures.
  • Security
    Provides multiple layers of security including encryption at rest and in transit, along with built-in firewall rules and IAM policies for robust access control.
  • Integration
    Seamlessly integrates with other Google Cloud services like BigQuery, Compute Engine, and Google Kubernetes Engine, supporting complex architectures and workflows.

Possible disadvantages of Google Cloud SQL

  • Cost
    It can be more expensive than self-managed solutions, especially as the need for additional resources and scaling arises.
  • Vendor Lock-in
    Relying on Google Cloud SQL could create dependency on the Google Cloud ecosystem, which might complicate future migration to other platforms.
  • Customization Limitations
    Being a managed service, it has constraints on certain configurations and customizations that might be essential for specific use cases.
  • Latency
    There might be increased latency compared to on-premises solutions, particularly for applications requiring very low-latency data access.
  • Compliance
    While Google Cloud SQL complies with many regulatory standards, some industries with highly specific requirements may find it unsuitable.

MongoDB videos

MySQL vs MongoDB

More videos:

  • Review - The Good and Bad of MongoDB
  • Review - what is mongoDB

Google Cloud SQL videos

GCP | Google Cloud SQL | Cloud SQL Features , Read Replicas & High Availability | DEMO

Category Popularity

0-100% (relative to MongoDB and Google Cloud SQL)
Databases
92 92%
8% 8
NoSQL Databases
96 96%
4% 4
Relational Databases
91 91%
9% 9
Graph Databases
100 100%
0% 0

User comments

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Reviews

These are some of the external sources and on-site user reviews we've used to compare MongoDB and Google Cloud SQL

MongoDB Reviews

10 Top Firebase Alternatives to Ignite Your Development in 2024
MongoDB’s superpower lies in its flexibility. Its document-based model lets you store data in a free-form, schema-less way, making it adaptable to evolving application needs. Need to add a new field or change the structure of your data? No problem, MongoDB handles it with ease.
Source: genezio.com
Top 7 Firebase Alternatives for App Development in 2024
MongoDB Realm provides a robust alternative to Firebase, especially for apps requiring a flexible data model. Key features include:
Source: signoz.io
Announcing FerretDB 1.0 GA - a truly Open Source MongoDB alternative
MongoDB is no longer open source. We want to bring MongoDB database workloads back to its open source roots. We are enabling PostgreSQL and other database backends to run MongoDB workloads, retaining the opportunities provided by the existing ecosystem around MongoDB.
16 Top Big Data Analytics Tools You Should Know About
The database added a new feature to its list of attributes called MongoDB Atlas. It is a global cloud database technology that allows to deploy a fully managed MongoDB across AWS, Google Cloud, and Azure with its built-in automation for resource, workload optimization and to reduce the time required to handle the database.
9 Best MongoDB alternatives in 2019
MongoDB is an open source NoSQL DBMS which uses a document-oriented database model. It supports various forms of data. However, in MongoDB data consumption is high due to de-normalization.
Source: www.guru99.com

Google Cloud SQL Reviews

We have no reviews of Google Cloud SQL yet.
Be the first one to post

Social recommendations and mentions

Google Cloud SQL might be a bit more popular than MongoDB. We know about 18 links to it since March 2021 and only 18 links to MongoDB. We are tracking product recommendations and mentions on various public social media platforms and blogs. They can help you identify which product is more popular and what people think of it.

MongoDB mentions (18)

  • Creating AI Memories using Rig & MongoDB
    In this article, we’ll build a CLI tool using the Rig AI framework and MongoDB for retrieval-augmented generation (RAG). This tool will store summarized conversations in a database and retrieve them when needed, enabling the AI to maintain context over time. - Source: dev.to / about 2 months ago
  • The Adventures of Blink S2e2: Database, Contained
    Have a Mongo database holding the various phrases we're going to use and potentially configuration data for the frontend as well. - Source: dev.to / 9 months ago
  • Introducing Perseid: The Product-oriented JS framework
    It's also worth mentioning that Perseid provides out-of-the-box support for React, VueJS, Svelte, MongoDB, MySQL, PostgreSQL, Express and Fastify. - Source: dev.to / 8 months ago
  • DocumentDB Elastic Cluster Pricing
    Does anyone know if the most basic Elastic Cluster instance of DocumentDB carries any monthly fixed cost or is it just on-demand cost? Another words if I run like 10,000 queries against the DB per month, what kind of bill would I expect? This is for a super small app. I am currently using mongodb free tier , but want to migrate everything to AWS. Can't seem to find a straight answer to the pricing question. Source: over 2 years ago
  • I wrote some scripts for converting the UTZOO Usenet archive to a Mongo Database
    You can use either MongoDB.com's dashboard (if you host a remote database) or Mongo Compass to run queries on the data or you can modify the express middleware with your own queries. I'm still working on the API, so it's not very robust yet. I will update this when it is. Source: over 2 years ago
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Google Cloud SQL mentions (18)

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What are some alternatives?

When comparing MongoDB and Google Cloud SQL, you can also consider the following products

Redis - Redis is an open source in-memory data structure project implementing a distributed, in-memory key-value database with optional durability.

PostgreSQL - PostgreSQL is a powerful, open source object-relational database system.

MySQL - The world's most popular open source database

Oracle DBaaS - See how Oracle Database 12c enables businesses to plug into the cloud and power the real-time enterprise.

ArangoDB - A distributed open-source database with a flexible data model for documents, graphs, and key-values.

Amazon Aurora - MySQL and PostgreSQL-compatible relational database built for the cloud. Performance and availability of commercial-grade databases at 1/10th the cost.