DBMS > Amazon DynamoDB vs. Ehcache vs. Hawkular Metrics vs. MonetDB vs. SiteWhere

System Properties Comparison Amazon DynamoDB vs. Ehcache vs. Hawkular Metrics vs. MonetDB vs. SiteWhere

Editorial information provided by DB-Engines

Name

Description

Hosted, scalable database service by Amazon with the data stored in Amazons cloud

A widely adopted Java cache with tiered storage options

Hawkular metrics is the metric storage of the Red Hat sponsored Hawkular monitoring system. It is based on Cassandra.

A relational database management system that stores data in columns

M2M integration platform for persisting/querying time series data

Primary database model

Document store
Key-value store

Secondary database models

Document store
Spatial DBMS

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

Score	74.45
Rank	#17	Overall
	#3	Document stores
	#2	Key-value stores

Score	4.64
Rank	#68	Overall
	#8	Key-value stores

Score	0.08
Rank	#366	Overall
	#39	Time Series DBMS

Score	1.72
Rank	#141	Overall
	#64	Relational DBMS

Score	0.06
Rank	#383	Overall
	#43	Time Series DBMS

Website

aws.amazon.com/dynamodb

www.ehcache.org

www.hawkular.org

www.monetdb.org

github.com/sitewhere/sitewhere

Technical documentation

docs.aws.amazon.com/dynamodb

www.ehcache.org/documentation

www.hawkular.org/hawkular-metrics/docs/user-guide

www.monetdb.org/Documentation

sitewhere1.sitewhere.io/index.html

Developer

Amazon

Terracotta Inc, owned by Software AG

Community supported by Red Hat

MonetDB BV

SiteWhere

Initial release

2012

2009

2014

2004

2010

Current release

3.10.0, March 2022

Dec2023 (11.49), December 2023

License

Commercial or Open Source

commercial

free tier for a limited amount of database operations

Open Source

Apache Version 2; commercial licenses available

Open Source

Apache 2.0

Open Source

Mozilla Public License 2.0

Open Source

Common Public Attribution License Version 1.0

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

All OS with a Java VM

Linux
OS X
Windows

FreeBSD
Linux
OS X
Solaris
Windows

Linux
OS X
Windows

Data scheme

schema-free

yes

predefined scheme

Typing

predefined data types such as float or date

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.

Secondary indexes

yes

SQL

Support of SQL

yes

SQL 2003 with some extensions

APIs and other access methods

RESTful HTTP API

JCache

HTTP REST

JDBC
native C library

MAPI library (MonetDB application programming interface)
ODBC

HTTP REST

Supported programming languages

.Net
ColdFusion
Erlang
Groovy
Java
JavaScript
Perl
PHP
Python
Ruby

Java

Go
Java
Python
Ruby

C
C++
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Ruby

Server-side scripts

Stored procedures

yes, in SQL, C, R

Triggers

yes

by integration with AWS Lambda

yes

Cache Event Listeners

yes

via Hawkular Alerting

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

by using Terracotta Server

Sharding

based on Cassandra

Sharding via remote tables

Sharding

based on HBase

Replication methods

Methods for redundantly storing data on multiple nodes

yes

by using Terracotta Server

selectable replication factor

based on Cassandra

none

Source-replica replication available in experimental status

selectable replication factor

based on HBase

MapReduce

Offers an API for user-defined Map/Reduce methods

may be implemented via Amazon Elastic MapReduce (Amazon EMR)

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency
Immediate Consistency

can be specified for read operations

Tunable Consistency (Strong, Eventual, Weak)

Eventual Consistency

based on Cassandra
Immediate Consistency

based on Cassandra

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

ACID across one or more tables within a single AWS account and region

yes

supports JTA and can work as an XA resource

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

using a tiered cache-storage approach

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)

fine grained access rights according to SQL-standard

Users with fine-grained authorization concept

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