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Amazon DynamoDB vs CouchDB: What are the differences?
Introduction
Amazon DynamoDB and CouchDB are both NoSQL databases that offer different features and capabilities. Understanding the key differences between these two databases can help you make an informed decision when choosing the right database for your needs.
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Data Model:
- DynamoDB is a key-value store that organizes data in tables with a primary key. It allows for flexible schemas with each item having a unique identifier and various attributes.
- CouchDB, on the other hand, is a document-based database that stores data in JSON-like documents. It uses a schema-less approach, allowing for more flexible and dynamic data structures.
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Ease of Scalability:
- DynamoDB offers automatic scaling by default, allowing you to increase or decrease the capacity of your table based on demand. It provides horizontal scaling and can handle millions of requests per second.
- CouchDB also supports scaling, but it requires manual setup and configuration. It follows a distributed architecture, where multiple instances of CouchDB can be set up and synced. However, scaling can be more complex in comparison to DynamoDB.
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ACID Compliance:
- DynamoDB guarantees consistency, durability, and isolation in terms of ACID (Atomicity, Consistency, Isolation, Durability) properties for individual items or transactions.
- CouchDB follows a more relaxed approach called eventual consistency. It allows for faster read and write operations but may result in data inconsistencies in certain scenarios.
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Querying and Indexing:
- DynamoDB offers a simple key-value access pattern and allows querying based on the primary key or secondary indexes. It also provides a rich set of querying capabilities with features like global and local secondary indexes, sort keys, filtering, and conditional expressions.
- CouchDB provides a powerful query mechanism called MapReduce. It allows complex queries using JavaScript functions, which can retrieve, filter, and transform documents based on specified criteria.
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Conflict Resolution:
- DynamoDB doesn't handle conflicts implicitly and relies on the application's logic to resolve conflicts that may arise during concurrent updates to the same item.
- CouchDB has built-in conflict resolution mechanisms and handles conflicts automatically. It uses a revision-based approach, where conflicts are tracked and can be resolved based on conflict resolution algorithms.
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Replication:
- DynamoDB offers automatic data replication across multiple Availability Zones within a region to provide high availability and fault tolerance. It also supports global tables for cross-region replication and data locality.
- CouchDB is designed to support offline replication and peer-to-peer synchronization. It allows for bidirectional replication between CouchDB instances, enabling data synchronization across multiple devices or sites.
In summary, the key differences between Amazon DynamoDB and CouchDB lie in their data models, scalability approaches, ACID compliance, querying capabilities, conflict resolution mechanisms, and replication features. These differences should be carefully considered when choosing the appropriate database for your specific requirements.
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.
We implemented our first large scale EPR application from naologic.com using CouchDB .
Very fast, replication works great, doesn't consume much RAM, queries are blazing fast but we found a problem: the queries were very hard to write, it took a long time to figure out the API, we had to go and write our own @nodejs library to make it work properly.
It lost most of its support. Since then, we migrated to Couchbase and the learning curve was steep but all worth it. Memcached indexing out of the box, full text search works great.
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 CouchDB
- JSON43
- Open source30
- Highly available18
- Partition tolerant12
- Eventual consistency11
- Sync7
- REST API5
- Attachments mechanism to docs4
- Multi master replication4
- Changes feed3
- REST interface1
- js- and erlang-views1
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Cons of Amazon DynamoDB
- Only sequential access for paginate data4
- Scaling1
- Document Limit Size1