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Amazon DynamoDB vs Azure Cosmos DB vs Cloud Firestore: What are the differences?
Introduction
This Markdown code provides a comparison between Amazon DynamoDB, Azure Cosmos DB, and Cloud Firestore to highlight their key differences.
Scalability: Amazon DynamoDB and Azure Cosmos DB are both known for their high scalability, allowing users to easily scale up or down their database resources based on demand. Cloud Firestore, on the other hand, offers automatic scaling without the need for manual intervention, making it a more hands-off option for users.
Consistency Models: Azure Cosmos DB offers five different consistency levels, allowing users to choose between strong consistency, Bounded staleness, Session consistency, Strong consistency, and Eventual consistency based on their application's requirements. Amazon DynamoDB and Cloud Firestore, however, have limited options in terms of consistency models, with DynamoDB offering eventual consistency or strong consistency and Cloud Firestore providing strong consistency by default with eventual consistency available as well.
Pricing: Amazon DynamoDB and Azure Cosmos DB have different pricing models based on provisioned throughput and usage, which can make cost estimation challenging. Cloud Firestore, on the other hand, offers a simpler pricing structure based on the number of reads, writes, and deletes, making it easier for users to predict costs.
Data Model: Amazon DynamoDB and Azure Cosmos DB support flexible data models, allowing users to store various types of data including JSON, BLOBs, and tabular data. Cloud Firestore is more focused on document-based data modeling, making it ideal for applications that require structured data storage.
Query Language: Azure Cosmos DB supports SQL-like queries with its SQL API, making it easy for developers familiar with SQL to query data. Amazon DynamoDB and Cloud Firestore, however, have limited querying capabilities, with DynamoDB requiring the use of secondary indexes and Cloud Firestore offering basic query functionalities.
Global Distribution: Azure Cosmos DB offers global distribution out of the box, allowing users to replicate data across multiple regions for low-latency access worldwide. Amazon DynamoDB and Cloud Firestore also support global distribution but may require additional configuration and setup to achieve similar levels of global availability.
In Summary, the key differences between Amazon DynamoDB, Azure Cosmos DB, and Cloud Firestore lie in scalability, consistency models, pricing, data models, query languages, and global distribution capabilities.
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?
Hi, Akash,
I wouldn't make this decision without lots more information. Cloud Firestore has a much richer metamodel (document-oriented) than Dynamo (key-value), and Dynamo seems to be particularly restrictive. That is why it is so fast. There are many needs in most applications to get lightning access to the members of a set, one set at a time. Dynamo DB is a great choice. But, social media applications generally need to be able to make long traverses across a graph. While you can make almost any metamodel act like another one, with your own custom layers on top of it, or just by writing a lot more code, it's a long way around to do that with simple key-value sets. It's hard enough to traverse across networks of collections in a document-oriented database. So, if you are moving, I think a graph-oriented database like Amazon Neptune, or, if you might want built-in reasoning, Allegro or Ontotext, would take the least programming, which is where the most cost and bugs can be avoided. Also, managed systems are also less costly in terms of people's time and system errors. It's easier to measure the costs of managed systems, so they are often seen as more costly.
Pros of Amazon DynamoDB
- Predictable performance and cost62
- Scalable56
- Native JSON Support35
- AWS Free Tier21
- Fast7
- No sql3
- To store data3
- Serverless2
- No Stored procedures is GOOD2
- ORM with DynamoDBMapper1
- Elastic Scalability using on-demand mode1
- Elastic Scalability using autoscaling1
- DynamoDB Stream1
Pros of Azure Cosmos DB
- Best-of-breed NoSQL features28
- High scalability22
- Globally distributed15
- Automatic indexing over flexible json data model14
- Tunable consistency10
- Always on with 99.99% availability sla10
- Javascript language integrated transactions and queries7
- Predictable performance6
- High performance5
- Analytics Store5
- Rapid Development2
- No Sql2
- Auto Indexing2
- Ease of use2
Pros of Cloud Firestore
- Easy to use15
- Cloud Storage15
- Realtime Database12
- Easy setup12
- Super fast9
- Authentication8
- Realtime listeners6
- Could Messaging5
- Hosting5
- Google Analytics integration5
- Performance Monitoring4
- Crash Reporting4
- Sharing App via invites3
- Test Lab for Android3
- Adwords, Admob integration3
- Dynamic Links (Deeplinking support)2
- Robust ALI0
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Cons of Amazon DynamoDB
- Only sequential access for paginate data4
- Scaling1
- Document Limit Size1
Cons of Azure Cosmos DB
- Pricing18
- Poor No SQL query support4
Cons of Cloud Firestore
- Doesn't support FullTextSearch natively8
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What is Amazon DynamoDB?
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