DBMS > Amazon SimpleDB vs. HugeGraph vs. Microsoft Azure Cosmos DB vs. Realm vs. STSdb

System Properties Comparison Amazon SimpleDB vs. HugeGraph vs. Microsoft Azure Cosmos DB vs. Realm vs. STSdb

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

A fast-speed and highly-scalable Graph DBMS

Globally distributed, horizontally scalable, multi-model database service

A DBMS built for use on mobile devices that’s a fast, easy to use alternative to SQLite and Core Data

Key-Value Store with special method for indexing

optimized for high performance using a special indexing method

Primary database model

Key-value store

Graph DBMS

Document store
Graph DBMS
Key-value store
Wide column store

Document store

Key-value store

Secondary database models

Spatial DBMS

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

Score	1.88
Rank	#139	Overall
	#24	Key-value stores

Score	0.15
Rank	#339	Overall
	#33	Graph DBMS

Score	29.85
Rank	#27	Overall
	#4	Document stores
	#2	Graph DBMS
	#3	Key-value stores
	#3	Wide column stores

Score	7.71
Rank	#52	Overall
	#9	Document stores

Score	0.06
Rank	#365	Overall
	#55	Key-value stores

Website

aws.amazon.com/simpledb

github.com/hugegraph
hugegraph.apache.org

azure.microsoft.com/services/cosmos-db

realm.io

github.com/STSSoft/STSdb4

Technical documentation

docs.aws.amazon.com/simpledb

hugegraph.apache.org/docs

learn.microsoft.com/azure/cosmos-db

realm.io/docs

Developer

Amazon

Baidu

Microsoft

Realm, acquired by MongoDB in May 2019

STS Soft SC

Initial release

2007

2018

2014

2011

Current release

0.9

4.0.8, September 2015

License

Commercial or Open Source

commercial

Open Source

Apache Version 2.0

commercial

Open Source

GPLv2, 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

Server operating systems

hosted

Linux
macOS
Unix

hosted

Android
Backend: server-less
iOS
Windows

Windows

Data scheme

schema-free

yes

schema-free

yes

Typing

predefined data types such as float or date

yes

JSON types

yes

primitive types and user defined types (classes)

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.

Secondary indexes

yes

All columns are indexed automatically

yes

also supports composite index and range index

yes

All properties auto-indexed by default

yes

SQL

Support of SQL

SQL-like query language

APIs and other access methods

RESTful HTTP API

Java API
RESTful HTTP API
TinkerPop Gremlin

DocumentDB API
Graph API (Gremlin)
MongoDB API
RESTful HTTP API
Table API

.NET Client API

Supported programming languages

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

Groovy
Java
Python

.Net
C#
Java
JavaScript
JavaScript (Node.js)
MongoDB client drivers written for various programming languages
Python

.Net
Java

with Android only
Objective-C
React Native
Swift

C#
Java

Server-side scripts

Stored procedures

asynchronous Gremlin script jobs

JavaScript

runs within the applications so server-side scripts are unnecessary

Triggers

JavaScript

yes

Change Listeners

Partitioning methods

Methods for storing different data on different nodes

none

Sharding must be implemented in the application

yes

depending on used storage backend, e.g. Cassandra and HBase

Sharding

Implicit feature of the cloud service

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes

depending on used storage backend, e.g. Cassandra and HBase

yes

Implicit feature of the cloud service

none

MapReduce

Offers an API for user-defined Map/Reduce methods

via hugegraph-spark

with Hadoop integration

Integration with Hadoop/HDInsight on Azure*

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency
Immediate Consistency

can be specified for read operations

Eventual Consistency

Bounded Staleness
Consistent Prefix
Eventual Consistency
Immediate Consistency

Consistency level configurable on request level
Session Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

edges in graph

Transaction concepts

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

Concurrent data updates can be detected by the application

ACID

Multi-item ACID transactions with snapshot isolation within a partition

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

In-Memory realm

User concepts

Access control

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

Users, roles and permissions

Access rights can be defined down to the item level

yes

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