Amazon SimpleDB vs Google Cloud Datastore

Overview

Amazon SimpleDB

Stacks21

Followers50

Votes0

Google Cloud Datastore

Stacks290

Followers357

Votes12

Amazon SimpleDB vs Google Cloud Datastore: What are the differences?

Introduction

In the world of databases, Amazon SimpleDB and Google Cloud Datastore are two popular choices. Although they serve the same purpose of providing scalable, highly available, and managed NoSQL database solutions, there are several key differences between the two.

Data Model: Amazon SimpleDB is based on a schema-less data model, which allows for flexible data storage and retrieval without predefined table schemas. On the other hand, Google Cloud Datastore uses a structured data model where entities are defined by their kind and properties. This allows for more structured and organized data storage.
Scalability: While both Amazon SimpleDB and Google Cloud Datastore offer scalability, they differ in their approach. SimpleDB automatically scales its underlying infrastructure to handle a high volume of requests, but it may experience higher latency during peak loads. On the contrary, Google Cloud Datastore is designed to handle massive scalability by sharding data across multiple servers, providing low-latency performance even during high traffic.
Querying Capabilities: Amazon SimpleDB supports limited querying capabilities, primarily allowing for simple queries on attribute values. On the other hand, Google Cloud Datastore offers more advanced querying options, including filtering, sorting, and joining multiple entities based on their properties, providing a more powerful and flexible querying experience.
Transactions and Consistency: Google Cloud Datastore has built-in support for transactional operations, allowing multiple operations to be executed atomically. It also provides strong consistency guarantees by default, ensuring that queries always return the most up-to-date data. Amazon SimpleDB, on the other hand, does not offer built-in support for transactions and provides eventual consistency, which means that changes may take some time to propagate through the system.
Associated Services: Both Amazon SimpleDB and Google Cloud Datastore are part of a larger ecosystem of cloud services. However, SimpleDB is tightly integrated with other Amazon Web Services (AWS) offerings, such as Amazon S3 for storing large objects and Amazon EC2 for running applications, providing a seamless experience for building applications within the AWS environment. Google Cloud Datastore, on the other hand, is part of the Google Cloud Platform, which offers a wide range of services, such as BigQuery for data analytics and App Engine for deploying applications.
Pricing Model: The pricing models of Amazon SimpleDB and Google Cloud Datastore differ in terms of their billing units and cost structures. SimpleDB charges based on the amount of data transferred in and out of the service, as well as storage and request costs. Google Cloud Datastore, on the other hand, charges based on the number of entity reads and writes, as well as storage costs. It's important to review the pricing details of each service to determine which aligns better with your application's requirements and usage patterns.

In Summary, Amazon SimpleDB and Google Cloud Datastore differ in their data models, scalability approaches, querying capabilities, transactions and consistency, associated services, and pricing models.

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Detailed Comparison

Amazon SimpleDB	Google Cloud Datastore
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.	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.
<div>Amazon SimpleDB automatically manages infrastructure provisioning, hardware and software maintenance, replication and indexing of data items, and performance tuning.;Amazon SimpleDB automatically creates multiple geographically distributed copies of each data item you store.;You can also choose between consistent or eventually consistent read requests, gaining the flexibility to match read performance (latency and throughput) and consistency requirements to the demands of your application, or even disparate parts within your application.;A table in Amazon SimpleDB has a strict storage limitation of 10 GB and is limited in the request capacity it can achieve (typically under 25 writes/second). It is up to you to manage the partitioning and re-partitioning of your data over additional SimpleDB tables if you need additional scale.</div>	Schemaless access, with SQL-like querying;Managed database;Autoscale with your users;ACID transactions;Built-in redundancy;Local development tools
Statistics
Stacks 21	Stacks 290
Followers 50	Followers 357
Votes 0	Votes 12
Pros & Cons
No community feedback yet	Pros 7 High scalability 2 Serverless 2 Ability to query any property 1 Pay for what you use

What are some alternatives to Amazon SimpleDB, Google Cloud Datastore?

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.

Azure Cosmos DB

Azure DocumentDB is a fully managed NoSQL database service built for fast and predictable performance, high availability, elastic scaling, global distribution, and ease of development.

Cloud Firestore

Cloud Firestore is a NoSQL document database that lets you easily store, sync, and query data for your mobile and web apps - at global scale.

Cloudant

Cloudant’s distributed database as a service (DBaaS) allows developers of fast-growing web and mobile apps to focus on building and improving their products, instead of worrying about scaling and managing databases on their own.

Google Cloud Bigtable

Google Cloud Bigtable offers you a fast, fully managed, massively scalable NoSQL database service that's ideal for web, mobile, and Internet of Things applications requiring terabytes to petabytes of data. Unlike comparable market offerings, Cloud Bigtable doesn't require you to sacrifice speed, scale, or cost efficiency when your applications grow. Cloud Bigtable has been battle-tested at Google for more than 10 years—it's the database driving major applications such as Google Analytics and Gmail.

CloudBoost

CloudBoost.io is a database service for the “next web” - that not only does data-storage, but also search, real-time and a whole lot more which enables developers to build much richer apps with 50% less time saving them a ton of cost and helping them go to market much faster.

Firebase Realtime Database

It is a cloud-hosted NoSQL database that lets you store and sync data between your users in realtime. Data is synced across all clients in realtime, and remains available when your app goes offline.

restdb.io

RestDB is a NoSql document oriented database cloud service. Data is accessed as JSON objects via HTTPS. This gives great flexibility, easy system integration and future compatibility.

Amazon DocumentDB

Amazon DocumentDB is a non-relational database service designed from the ground-up to give you the performance, scalability, and availability you need when operating mission-critical MongoDB workloads at scale. In Amazon DocumentDB, the storage and compute are decoupled, allowing each to scale independently, and you can increase the read capacity to millions of requests per second by adding up to 15 low latency read replicas in minutes, regardless of the size of your data.

Datomic Cloud

A transactional database with a flexible data model, elastic scaling, and rich queries. Datomic is designed from the ground up to run on AWS. Datomic leverages AWS technology, including DynamoDB, S3, EFS, and CloudFormation to provide a fully integrated solution.

Related Comparisons

Amazon SimpleDB vs Google Cloud Datastore: What are the differences?

Introduction

Data Model: Amazon SimpleDB is based on a schema-less data model, which allows for flexible data storage and retrieval without predefined table schemas. On the other hand, Google Cloud Datastore uses a structured data model where entities are defined by their kind and properties. This allows for more structured and organized data storage.
Scalability: While both Amazon SimpleDB and Google Cloud Datastore offer scalability, they differ in their approach. SimpleDB automatically scales its underlying infrastructure to handle a high volume of requests, but it may experience higher latency during peak loads. On the contrary, Google Cloud Datastore is designed to handle massive scalability by sharding data across multiple servers, providing low-latency performance even during high traffic.
Querying Capabilities: Amazon SimpleDB supports limited querying capabilities, primarily allowing for simple queries on attribute values. On the other hand, Google Cloud Datastore offers more advanced querying options, including filtering, sorting, and joining multiple entities based on their properties, providing a more powerful and flexible querying experience.
Transactions and Consistency: Google Cloud Datastore has built-in support for transactional operations, allowing multiple operations to be executed atomically. It also provides strong consistency guarantees by default, ensuring that queries always return the most up-to-date data. Amazon SimpleDB, on the other hand, does not offer built-in support for transactions and provides eventual consistency, which means that changes may take some time to propagate through the system.
Associated Services: Both Amazon SimpleDB and Google Cloud Datastore are part of a larger ecosystem of cloud services. However, SimpleDB is tightly integrated with other Amazon Web Services (AWS) offerings, such as Amazon S3 for storing large objects and Amazon EC2 for running applications, providing a seamless experience for building applications within the AWS environment. Google Cloud Datastore, on the other hand, is part of the Google Cloud Platform, which offers a wide range of services, such as BigQuery for data analytics and App Engine for deploying applications.
Pricing Model: The pricing models of Amazon SimpleDB and Google Cloud Datastore differ in terms of their billing units and cost structures. SimpleDB charges based on the amount of data transferred in and out of the service, as well as storage and request costs. Google Cloud Datastore, on the other hand, charges based on the number of entity reads and writes, as well as storage costs. It's important to review the pricing details of each service to determine which aligns better with your application's requirements and usage patterns.

Amazon SimpleDB vs Google Cloud Datastore

Overview