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Amazon DynamoDB vs Doctrine 2: What are the differences?

# Introduction:
This comparison outlines key differences between Amazon DynamoDB and Doctrine 2 for website development purposes.

1. **Data Model**: Amazon DynamoDB is a NoSQL database that uses key-value pairs for data representation, while Doctrine 2 is an Object-Relational Mapping (ORM) that maps objects to relational database tables.
2. **Scalability**: DynamoDB offers seamless scalability with automatic partitioning and replication of data across multiple servers, providing high throughput and storage capabilities. In contrast, Doctrine 2's scalability relies on the underlying relational database management system and its configuration settings.
3. **Performance**: DynamoDB provides predictable and low-latency performance for read and write operations due to its distributed nature and optimized storage engine. On the other hand, Doctrine 2's performance can vary depending on the complexity of the queries and the efficiency of the underlying database design.
4. **Schema Design**: DynamoDB requires upfront schema design and optimization to leverage its full potential, including defining primary keys and secondary indexes. In contrast, Doctrine 2 abstracts the database schema through entity mapping and annotations, allowing for more flexibility in object-oriented design.
5. **Cost Structure**: DynamoDB charges based on provisioned throughput capacity, data storage, and additional features, making it suitable for applications with varying workloads. Doctrine 2 has no direct cost associated with its usage, as it is a library that integrates with existing relational databases, thereby inheriting their cost structures.
6. **Consistency Model**: DynamoDB offers users the choice between strong and eventual consistency for read operations, providing flexibility based on application requirements. Doctrine 2 follows the consistency model of the underlying relational database system, which may vary but typically provides strong consistency for transactions.

In Summary, the key differences between Amazon DynamoDB and Doctrine 2 lie in their data models, scalability, performance, schema design, cost structure, and consistency models.

Advice on Amazon DynamoDB and Doctrine 2

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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Replies (1)
William Frank
Data Science and Engineering at GeistM · | 2 upvotes · 114.6K views
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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.

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Pros of Amazon DynamoDB
Pros of Doctrine 2
  • 62
    Predictable performance and cost
  • 56
    Scalable
  • 35
    Native JSON Support
  • 21
    AWS Free Tier
  • 7
    Fast
  • 3
    No sql
  • 3
    To store data
  • 2
    Serverless
  • 2
    No Stored procedures is GOOD
  • 1
    ORM with DynamoDBMapper
  • 1
    Elastic Scalability using on-demand mode
  • 1
    Elastic Scalability using autoscaling
  • 1
    DynamoDB Stream
  • 14
    Great abstraction, easy to use, good docs
  • 10
    Object-Oriented
  • 7
    Easy setup

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Cons of Amazon DynamoDB
Cons of Doctrine 2
  • 4
    Only sequential access for paginate data
  • 1
    Scaling
  • 1
    Document Limit Size
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    What is 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.

    What is Doctrine 2?

    Doctrine 2 sits on top of a powerful database abstraction layer (DBAL). One of its key features is the option to write database queries in a proprietary object oriented SQL dialect called Doctrine Query Language (DQL), inspired by Hibernates HQL.

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    What companies use Amazon DynamoDB?
    What companies use Doctrine 2?
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    What tools integrate with Amazon DynamoDB?
    What tools integrate with Doctrine 2?

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    What are some alternatives to Amazon DynamoDB and Doctrine 2?
    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.
    MongoDB
    MongoDB stores data in JSON-like documents that can vary in structure, offering a dynamic, flexible schema. MongoDB was also designed for high availability and scalability, with built-in replication and auto-sharding.
    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.
    MySQL
    The MySQL software delivers a very fast, multi-threaded, multi-user, and robust SQL (Structured Query Language) database server. MySQL Server is intended for mission-critical, heavy-load production systems as well as for embedding into mass-deployed software.
    Amazon S3
    Amazon Simple Storage Service provides a fully redundant data storage infrastructure for storing and retrieving any amount of data, at any time, from anywhere on the web
    See all alternatives