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  1. Stackups
  2. Application & Data
  3. Databases
  4. Odm
  5. Google Cloud Datastore vs Mongoose

Google Cloud Datastore vs Mongoose

OverviewComparisonAlternatives

Overview

Mongoose
Mongoose
Stacks2.4K
Followers1.4K
Votes56
Google Cloud Datastore
Google Cloud Datastore
Stacks290
Followers357
Votes12

Google Cloud Datastore vs Mongoose: What are the differences?

# Introduction

Google Cloud Datastore and Mongoose are popular databases used for data storage in web applications. Despite serving the same purpose, there are key differences between the two that are essential to consider when choosing the right database solution for a project.

## 1. Scalability:
Google Cloud Datastore is a fully managed NoSQL database service that automatically scales horizontally to accommodate varying workloads. In contrast, Mongoose is an ORM (Object-Relational Mapping) library for MongoDB, which requires manual setup and configuration for scalability.

## 2. Data Model:
Google Cloud Datastore uses a schemaless data model, allowing for flexible data structures without predefined schemas. On the other hand, Mongoose requires defining schemas in advance to enforce data consistency and structure.

## 3. Querying:
Google Cloud Datastore offers a more limited querying capability compared to Mongoose, as it uses Google's proprietary query language called GQL. Mongoose, based on MongoDB, provides a rich querying API with support for complex queries and aggregation pipelines.

## 4. Transactions:
Google Cloud Datastore supports multi-entity transactions for ACID compliance, ensuring data integrity across multiple entities in a single operation. In contrast, Mongoose lacks built-in support for transactions, requiring developers to implement custom logic for maintaining data consistency.

## 5. Indexing:
Google Cloud Datastore automatically indexes all properties by default, simplifying query performance optimization for developers. Mongoose, on the other hand, requires manual indexing configuration to improve query efficiency, which can be more complex and error-prone.

## 6. Pricing:
Google Cloud Datastore follows a pay-as-you-go pricing model based on data storage and read/write operations. Mongoose, being an open-source library, does not incur direct costs but requires deployment and maintenance of a MongoDB database, which may involve associated expenses.

In Summary, Google Cloud Datastore and Mongoose differ in scalability, data model, querying capabilities, transactions, indexing, and pricing, making them suitable for different use cases based on specific project requirements.

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Detailed Comparison

Mongoose
Mongoose
Google Cloud Datastore
Google Cloud Datastore

Let's face it, writing MongoDB validation, casting and business logic boilerplate is a drag. That's why we wrote Mongoose. Mongoose provides a straight-forward, schema-based solution to modeling your application data and includes built-in type casting, validation, query building, business logic hooks and more, out of the box.

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.

-
Schemaless access, with SQL-like querying;Managed database;Autoscale with your users;ACID transactions;Built-in redundancy;Local development tools
Statistics
Stacks
2.4K
Stacks
290
Followers
1.4K
Followers
357
Votes
56
Votes
12
Pros & Cons
Pros
  • 17
    Several bad ideas mixed together
  • 17
    Well documented
  • 10
    JSON
  • 8
    Actually terrible documentation
  • 2
    Recommended and used by Valve. See steamworks docs
Cons
  • 3
    Model middleware/hooks are not user friendly
Pros
  • 7
    High scalability
  • 2
    Ability to query any property
  • 2
    Serverless
  • 1
    Pay for what you use
Integrations
Node.js
Node.js
MongoDB
MongoDB
No integrations available

What are some alternatives to Mongoose, Google Cloud Datastore?

Amazon DynamoDB

Amazon DynamoDB

With it , you can offload the administrative burden of operating and scaling a highly available distributed database cluster, while paying a low price for only what you use.

Azure Cosmos DB

Azure Cosmos DB

Azure DocumentDB is a fully managed NoSQL database service built for fast and predictable performance, high availability, elastic scaling, global distribution, and ease of development.

Cloud Firestore

Cloud Firestore

Cloud Firestore is a NoSQL document database that lets you easily store, sync, and query data for your mobile and web apps - at global scale.

Cloudant

Cloudant

Cloudant’s distributed database as a service (DBaaS) allows developers of fast-growing web and mobile apps to focus on building and improving their products, instead of worrying about scaling and managing databases on their own.

Google Cloud Bigtable

Google Cloud Bigtable

Google Cloud Bigtable offers you a fast, fully managed, massively scalable NoSQL database service that's ideal for web, mobile, and Internet of Things applications requiring terabytes to petabytes of data. Unlike comparable market offerings, Cloud Bigtable doesn't require you to sacrifice speed, scale, or cost efficiency when your applications grow. Cloud Bigtable has been battle-tested at Google for more than 10 years—it's the database driving major applications such as Google Analytics and Gmail.

CloudBoost

CloudBoost

CloudBoost.io is a database service for the “next web” - that not only does data-storage, but also search, real-time and a whole lot more which enables developers to build much richer apps with 50% less time saving them a ton of cost and helping them go to market much faster.

Firebase Realtime Database

Firebase Realtime Database

It is a cloud-hosted NoSQL database that lets you store and sync data between your users in realtime. Data is synced across all clients in realtime, and remains available when your app goes offline.

Mongoid

Mongoid

The philosophy of Mongoid is to provide a familiar API to Ruby developers who have been using Active Record or Data Mapper, while leveraging the power of MongoDB's schemaless and performant document-based design, dynamic queries, and atomic modifier operations.

restdb.io

restdb.io

RestDB is a NoSql document oriented database cloud service. Data is accessed as JSON objects via HTTPS. This gives great flexibility, easy system integration and future compatibility.

Amazon DocumentDB

Amazon DocumentDB

Amazon DocumentDB is a non-relational database service designed from the ground-up to give you the performance, scalability, and availability you need when operating mission-critical MongoDB workloads at scale. In Amazon DocumentDB, the storage and compute are decoupled, allowing each to scale independently, and you can increase the read capacity to millions of requests per second by adding up to 15 low latency read replicas in minutes, regardless of the size of your data.

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