DBMS > Amazon SimpleDB vs. Google Cloud Datastore vs. Stardog vs. STSdb vs. WakandaDB

System Properties Comparison Amazon SimpleDB vs. Google Cloud Datastore vs. Stardog vs. STSdb vs. WakandaDB

Editorial information provided by DB-Engines

Name

Description

Hosted simple database service by Amazon, with the data stored in the Amazon Cloud.

There is an unrelated product called SimpleDB developed by Edward Sciore

Automatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud Platform

Enterprise Knowledge Graph platform and graph DBMS with high availability, high performance reasoning, and virtualization

Key-Value Store with special method for indexing

optimized for high performance using a special indexing method

WakandaDB is embedded in a server that provides a REST API and a server-side javascript engine to access data

Primary database model

DB-Engines Ranking measures the popularity of database management systems
Trend Chart

Score	1.85
Rank	#138	Overall
	#24	Key-value stores

Score	4.47
Rank	#76	Overall
	#12	Document stores

Score	2.02
Rank	#123	Overall
	#11	Graph DBMS
	#6	RDF stores

Score	0.04
Rank	#360	Overall
	#52	Key-value stores

Score	0.03
Rank	#364	Overall
	#17	Object oriented DBMS

Website

aws.amazon.com/simpledb

cloud.google.com/datastore

www.stardog.com

github.com/STSSoft/STSdb4

wakanda.github.io

Technical documentation

docs.aws.amazon.com/simpledb

cloud.google.com/datastore/docs

docs.stardog.com

wakanda.github.io/doc

Developer

Amazon

Google

Stardog-Union

STS Soft SC

Wakanda SAS

Initial release

2007

2008

2010

2011

2012

Current release

7.3.0, May 2020

4.0.8, September 2015

2.7.0 (April 29, 2019), April 2019

License

Commercial or Open Source

commercial

60-day fully-featured trial license; 1-year fully-featured non-commercial use license for academics/students

Open Source

GPLv2, commercial license available

Open Source

AGPLv3, extended commercial license available

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

Java

C++, JavaScript

Server operating systems

hosted

Linux
macOS
Windows

Windows

Linux
OS X
Windows

Data scheme

schema-free

schema-free and OWL/RDFS-schema support

yes

Typing

predefined data types such as float or date

yes, details here

yes

primitive types and user defined types (classes)

yes

XML support

Some form of processing data in XML format, e.g. support for XML data structures, and/or support for XPath, XQuery or XSLT.

Import/export of XML data possible

Secondary indexes

yes

All columns are indexed automatically

yes

supports real-time indexing in full-text and geospatial

SQL

Support of SQL

SQL-like query language (GQL)

Yes, compatible with all major SQL variants through dedicated BI/SQL Server

APIs and other access methods

RESTful HTTP API

gRPC (using protocol buffers) API
RESTful HTTP/JSON API

GraphQL query language
HTTP API
Jena RDF API
OWL
RDF4J API
Sesame REST HTTP Protocol
SNARL
SPARQL
Spring Data
Stardog Studio
TinkerPop 3

.NET Client API

RESTful HTTP API

Supported programming languages

.Net
C
C++
Erlang
Java
PHP
Python
Ruby
Scala

.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby

.Net
Clojure
Groovy
Java
JavaScript
Python
Ruby

C#
Java

JavaScript

Server-side scripts

Stored procedures

using Google App Engine

user defined functions and aggregates, HTTP Server extensions in Java

yes

Triggers

Callbacks using the Google Apps Engine

yes

via event handlers

yes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding must be implemented in the application

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Multi-source replication using Paxos

Multi-source replication in HA-Cluster

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

using Google Cloud Dataflow

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency
Immediate Consistency

can be specified for read operations

Immediate Consistency or Eventual Consistency depending on type of query and configuration

Strong Consistency is default for entity lookups and queries within an Entity Group (but can instead be made eventually consistent). Other queries are always eventual consistent.

Immediate Consistency in HA-Cluster

Immediate Consistency

Foreign keys

Referential integrity

yes

via ReferenceProperties or Ancestor paths

yes

relationships in graphs

Transaction concepts

Support to ensure data integrity after non-atomic manipulations of data

Concurrent data updates can be detected by the application

ACID

Serializable Isolation within Transactions, Read Committed outside of Transactions

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

yes

User concepts

Access control

Access rights for users and roles can be defined via the AWS Identity and Access Management (IAM)

Access rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)

Access rights for users and roles

yes

More information provided by the system vendor

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Related products and services

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More resources

DB-Engines blog posts

The popularity of cloud-based DBMSs has increased tenfold in four years
7 February 2017, Matthias Gelbmann

Amazon - the rising star in the DBMS market
3 August 2015, Matthias Gelbmann

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Recent citations in the news

A Place for Everything – Amazon SimpleDB
14 December 2007, AWS Blog

Amazon DynamoDB Serves Trillions Of Requests Per Month While Counterpart SimpleDB Is No Longer A Listed ...
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Amazon SimpleDB Management in Eclipse
22 July 2009, AWS Blog

An Overview of Amazon Web Services - Cloud Application Architectures [Book]
22 September 2018, oreilly.com

Amazon Goes Back to the Future With 'NoSQL' Database
19 January 2012, WIRED

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