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Amazon DynamoDB vs Cloud Firestore: What are the differences?
Differences between Amazon DynamoDB and Cloud Firestore
Amazon DynamoDB and Cloud Firestore are two popular NoSQL databases that are widely used for building modern, scalable web applications. While they share some similarities, there are several key differences between these two platforms. The following paragraphs highlight six important distinctions that set them apart.
Data Model: Amazon DynamoDB is a key-value store that provides fast and predictable performance with the ability to scale horizontally. It is schema-less and allows flexible data modeling. On the other hand, Cloud Firestore is a document-based database that organizes data into documents and collections. It supports more complex data structures with nested fields and arrays, making it easier to represent hierarchical data.
Scalability: Both DynamoDB and Cloud Firestore are designed to handle scale, but they have different scaling approaches. In DynamoDB, scaling is done based on read and write capacity units, providing fine-grained control over resource allocation. Cloud Firestore, on the other hand, automatically scales to handle read and write traffic, making it easier to handle sudden spikes in workloads without manual capacity planning.
Pricing Model: DynamoDB uses a provisioned capacity model, where users need to provision and pay for the read and write capacity units they require. This provides cost predictability but can lead to over or under-provisioning. Cloud Firestore, on the other hand, uses a pay-as-you-go model, where users are billed based on the number of document reads, writes, and storage used. This gives more flexibility in terms of cost management.
Real-time Updates: Cloud Firestore has built-in real-time data synchronization, allowing clients to receive updates in real-time. It uses web sockets and provides real-time listeners that notify clients whenever a document changes. DynamoDB, on the other hand, does not have built-in real-time capabilities and requires the use of additional services like AWS Lambda or Amazon Kinesis to achieve similar functionality.
Query Capabilities: DynamoDB provides powerful and flexible querying options through its Query and Scan operations. It allows filtering based on various attributes and supports secondary indexes for better query performance. Cloud Firestore also offers querying capabilities, but its querying model is more limited compared to DynamoDB. Queries rely on simple equality and range comparisons and do not support complex filtering or secondary indexes.
Integration with Ecosystem: DynamoDB is part of the Amazon Web Services (AWS) ecosystem, which provides a broad range of complementary services like AWS Lambda, AWS CloudFormation, and Amazon S3. This tight integration allows developers to build end-to-end solutions using multiple AWS services. Cloud Firestore, on the other hand, is part of the Google Cloud ecosystem and integrates well with other Google Cloud Platform services like Cloud Functions, Firebase Authentication, and Cloud Storage.
In summary, Amazon DynamoDB and Cloud Firestore differ in their data models, scalability approaches, pricing models, real-time capabilities, query capabilities, and integration with their respective ecosystems. Each platform has its strengths and weaknesses, and the choice between them depends on the specific requirements of the project and the preferences of the development team.
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 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 Cloud Firestore
- Doesn't support FullTextSearch natively8