Amazon DynamoDB vs Amazon SimpleDB

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Amazon DynamoDB vs Amazon SimpleDB: What are the differences?

Introduction

Amazon DynamoDB and Amazon SimpleDB are both NoSQL databases offered by Amazon Web Services (AWS). While they are both designed to handle large volumes of data, there are key differences between these two services that make them suitable for different use cases. This article outlines the main differences between Amazon DynamoDB and Amazon SimpleDB.

  1. Scalability and Performance: One of the main differences between Amazon DynamoDB and Amazon SimpleDB is their scalability and performance capabilities. DynamoDB is designed to handle massive workloads and can scale horizontally across multiple servers to handle high read and write request rates. It also provides predictable performance with low latency, making it suitable for applications that require high throughput. On the other hand, SimpleDB is designed for smaller, less demanding workloads and does not scale as easily as DynamoDB.

  2. Data Model: Another major difference between DynamoDB and SimpleDB is their data model. DynamoDB is a key-value store, where each item in the database is uniquely identified by a primary key. It supports both single-item retrieval and batch retrieval, and also provides secondary indexes for flexible querying. SimpleDB, on the other hand, is a schemaless database that uses attributes to store data. Each item can have multiple attributes, and you can perform queries using the attributes as conditions.

  3. Consistency Model: Amazon DynamoDB and Amazon SimpleDB have different consistency models. DynamoDB offers both eventually consistent reads and strongly consistent reads. Eventually consistent reads are faster but may not always reflect the latest write operations. Strongly consistent reads ensure that you get the latest data, but may have higher latency. SimpleDB, on the other hand, only supports eventual consistency, so there may be a slight delay in getting the most up-to-date data.

  4. Size Limitations: While DynamoDB can handle large datasets, it has certain limitations on the size of individual items and the total amount of data you can store. Each item in DynamoDB can be up to 400 KB in size, and the maximum total size of all items in a table is 10 GB. In comparison, SimpleDB has a more restrictive limit of 1.1 MB for each item.

  5. Cost: The pricing structure for DynamoDB and SimpleDB also differs. DynamoDB charges for provisioned throughput, storage, and additional features like global tables. SimpleDB, on the other hand, charges based on the amount of data stored and the number of requests made. For smaller workloads, SimpleDB may be more cost-effective, while DynamoDB is better suited for high-scale applications where performance and scalability are critical.

  6. Query Capabilities: DynamoDB and SimpleDB have different query capabilities. DynamoDB supports rich query operations, including both primary key and secondary index queries, as well as conditional queries. It also provides a flexible Query API that allows you to specify filtering conditions. SimpleDB, on the other hand, has a simpler query model that supports basic querying using attributes as conditions.

In summary, Amazon DynamoDB is a highly scalable, performance-oriented NoSQL database that is suitable for large workloads and high throughput applications. It offers strong consistency, rich querying capabilities, and provides flexibility in data modeling. Amazon SimpleDB, on the other hand, is a more lightweight and cost-effective solution that is suitable for smaller workloads and simpler querying needs. It has limitations on scalability and performance, but offers eventual consistency and a simpler data model.

Advice on Amazon DynamoDB and Amazon SimpleDB

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 · 108.1K 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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Decisions about Amazon DynamoDB and Amazon SimpleDB
Eduardo Fernandez
Software Engineer at Parrot Software, Inc. · | 5 upvotes · 12K views

CouchDB has proven us to be a reliable multi-master NoSQL JSON database built natively for the web.

We decided to use it over alternatives such as Firebase due topology, costs and frontend architecture.

Thanks to CouchDB we are now a frontend first CRM platform. We are capable of delivering and leveraging our frontend code to build most of our new functionalities directly within the frontend which we enrich through backend sidecars connected to each Parrot and each CouchDB.

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Pros of Amazon DynamoDB
Pros of Amazon SimpleDB
  • 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
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    Cons of Amazon DynamoDB
    Cons of Amazon SimpleDB
    • 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 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.

      Need advice about which tool to choose?Ask the StackShare community!

      What companies use Amazon DynamoDB?
      What companies use Amazon SimpleDB?
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      What tools integrate with Amazon DynamoDB?
      What tools integrate with Amazon SimpleDB?
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        What are some alternatives to Amazon DynamoDB and Amazon SimpleDB?
        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.
        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
        Amazon Redshift
        It is optimized for data sets ranging from a few hundred gigabytes to a petabyte or more and costs less than $1,000 per terabyte per year, a tenth the cost of most traditional data warehousing solutions.
        See all alternatives