Azure Cosmos DB vs Cloud Firestore

Overview

Azure Cosmos DB

Stacks594

Followers1.1K

Votes130

Cloud Firestore

Stacks751

Followers900

Votes112

Azure Cosmos DB vs Cloud Firestore: What are the differences?

Introduction

Azure Cosmos DB and Cloud Firestore are both NoSQL databases offered by Microsoft Azure and Google Cloud Platform respectively. While they share some similarities in their functionality and purpose, there are several key differences that set them apart.

Query Language: Azure Cosmos DB uses SQL-like query language, which allows users to write queries in a familiar and structured manner. On the other hand, Cloud Firestore uses a more flexible and scalable querying approach, enabling users to fetch data using specialized methods or through composite queries.
Scalability: Azure Cosmos DB offers global scalability with its multi-region replication and elastic scaling capabilities. It allows you to distribute your data across multiple regions for high availability and offers flexible scaling options based on your workload requirements. Cloud Firestore, on the other hand, provides native support for automatic scaling, allowing your database to handle large amounts of data and traffic without manual configuration.
Pricing Model: Azure Cosmos DB follows a throughput-based pricing model, where you pay for the throughput capacity provisioned. This model allows you to allocate resources precisely for your workload requirements. Cloud Firestore, on the other hand, uses a usage-based pricing model, where you pay for the amount of data stored, network egress, and operations performed. This model provides more flexibility in terms of cost management, as you pay only for what you use.
Data Structure: Azure Cosmos DB offers a more flexible data model, supporting multiple data models like documents, graphs, key-value pairs, and columnar. It provides the ability to work with structured, semi-structured, and unstructured data efficiently. Cloud Firestore, on the other hand, is a document-based database, which means it is focused on storing and retrieving JSON-like documents.
Real-time Updates: Cloud Firestore provides real-time updates using the Firestore Realtime Database, enabling developers to build real-time applications easily. It offers real-time synchronization for data changes across multiple devices in milliseconds. Azure Cosmos DB, on the other hand, does not provide a built-in real-time synchronization feature, but it can be integrated with Azure SignalR or other real-time messaging services to achieve similar functionality.
Integration with Platform Services: Azure Cosmos DB integrates well with other Azure services, such as Azure Functions, Azure Event Grid, and Azure Data Factory, allowing easy and seamless data processing and integration across the Azure ecosystem. Cloud Firestore, on the other hand, integrates well with other Google Cloud Platform services, such as Firebase Authentication, Cloud Functions, and Cloud Storage, providing a comprehensive ecosystem for application development.

In summary, Azure Cosmos DB and Cloud Firestore differ in terms of query language, scalability options, pricing model, data structure, real-time updates, and integration with platform services. These differences make them suitable for different use cases and allow users to choose the database that best fits their requirements.

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Advice on Azure Cosmos DB, Cloud Firestore

akash

Aug 27, 2020

Needs adviceon

Cloud Firestore

Firebase Realtime Database

Amazon DynamoDB

We are building a social media app, where users will post images, like their post, and make friends based on their interest. We are currently using Cloud Firestore and Firebase Realtime Database. We are looking for another database like Amazon DynamoDB; how much this decision can be efficient in terms of pricing and overhead?

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Detailed Comparison

Azure Cosmos DB	Cloud Firestore
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 is a NoSQL document database that lets you easily store, sync, and query data for your mobile and web apps - at global scale.
Fully managed with 99.99% Availability SLA;Elastically and highly scalable (both throughput and storage);Predictable low latency: <10ms @ P99 reads and <15ms @ P99 fully-indexed writes;Globally distributed with multi-region replication;Rich SQL queries over schema-agnostic automatic indexing;JavaScript language integrated multi-record ACID transactions with snapshot isolation;Well-defined tunable consistency models: Strong, Bounded Staleness, Session, and Eventual	Documents and collections with powerful querying;iOS, Android, and Web SDKs with offline data access;Real-time data synchronization;Automatic, multi-region data replication with strong consistency;Node, Python, Go, and Java server SDKs
Statistics
Stacks 594	Stacks 751
Followers 1.1K	Followers 900
Votes 130	Votes 112
Pros & Cons
Pros 28 Best-of-breed NoSQL features 22 High scalability 15 Globally distributed 14 Automatic indexing over flexible json data model 10 Tunable consistency Cons 18 Pricing 4 Poor No SQL query support	Pros 15 Cloud Storage 15 Easy to use 12 Easy setup 12 Realtime Database 9 Super fast Cons 8 Doesn't support FullTextSearch natively
Integrations
Azure Machine Learning MongoDB Hadoop Java Azure Functions Azure Container Service Azure Storage Azure Websites Apache Spark Python	Golang Node.js Java Python Firebase Cloud Functions for Firebase Google Cloud Functions

What are some alternatives to Azure Cosmos DB, Cloud Firestore?

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.

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 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.

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.

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

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.

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 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.

Amazon SimpleDB

Developers simply store and query data items via web services requests and Amazon SimpleDB does the rest. Behind the scenes, Amazon SimpleDB creates and manages multiple geographically distributed replicas of your data automatically to enable high availability and data durability. Amazon SimpleDB provides a simple web services interface to create and store multiple data sets, query your data easily, and return the results. Your data is automatically indexed, making it easy to quickly find the information that you need. There is no need to pre-define a schema or change a schema if new data is added later. And scale-out is as simple as creating new domains, rather than building out new servers.

Datomic Cloud

A transactional database with a flexible data model, elastic scaling, and rich queries. Datomic is designed from the ground up to run on AWS. Datomic leverages AWS technology, including DynamoDB, S3, EFS, and CloudFormation to provide a fully integrated solution.

Related Comparisons

Azure Cosmos DB vs Cloud Firestore: What are the differences?

Introduction

Query Language: Azure Cosmos DB uses SQL-like query language, which allows users to write queries in a familiar and structured manner. On the other hand, Cloud Firestore uses a more flexible and scalable querying approach, enabling users to fetch data using specialized methods or through composite queries.
Scalability: Azure Cosmos DB offers global scalability with its multi-region replication and elastic scaling capabilities. It allows you to distribute your data across multiple regions for high availability and offers flexible scaling options based on your workload requirements. Cloud Firestore, on the other hand, provides native support for automatic scaling, allowing your database to handle large amounts of data and traffic without manual configuration.
Pricing Model: Azure Cosmos DB follows a throughput-based pricing model, where you pay for the throughput capacity provisioned. This model allows you to allocate resources precisely for your workload requirements. Cloud Firestore, on the other hand, uses a usage-based pricing model, where you pay for the amount of data stored, network egress, and operations performed. This model provides more flexibility in terms of cost management, as you pay only for what you use.
Data Structure: Azure Cosmos DB offers a more flexible data model, supporting multiple data models like documents, graphs, key-value pairs, and columnar. It provides the ability to work with structured, semi-structured, and unstructured data efficiently. Cloud Firestore, on the other hand, is a document-based database, which means it is focused on storing and retrieving JSON-like documents.
Real-time Updates: Cloud Firestore provides real-time updates using the Firestore Realtime Database, enabling developers to build real-time applications easily. It offers real-time synchronization for data changes across multiple devices in milliseconds. Azure Cosmos DB, on the other hand, does not provide a built-in real-time synchronization feature, but it can be integrated with Azure SignalR or other real-time messaging services to achieve similar functionality.
Integration with Platform Services: Azure Cosmos DB integrates well with other Azure services, such as Azure Functions, Azure Event Grid, and Azure Data Factory, allowing easy and seamless data processing and integration across the Azure ecosystem. Cloud Firestore, on the other hand, integrates well with other Google Cloud Platform services, such as Firebase Authentication, Cloud Functions, and Cloud Storage, providing a comprehensive ecosystem for application development.

Azure Cosmos DB vs Cloud Firestore

Overview

Azure Cosmos DB vs Cloud Firestore: What are the differences?