DBMS > Amazon SimpleDB vs. Ehcache vs. Lovefield vs. Oracle Berkeley DB vs. RDF4J

System Properties Comparison Amazon SimpleDB vs. Ehcache vs. Lovefield vs. Oracle Berkeley DB vs. RDF4J

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 widely adopted Java cache with tiered storage options

Embeddable relational database for web apps written in pure JavaScript

Widely used in-process key-value store

RDF4J is a Java framework for processing RDF data, supporting both memory-based and a disk-based storage.

Primary database model

Key-value store

Relational DBMS

Key-value store

supports sorted and unsorted key sets
Native XML DBMS

in the Oracle Berkeley DB XML version

RDF store

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

Score	1.88
Rank	#133	Overall
	#23	Key-value stores

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

Score	0.33
Rank	#286	Overall
	#131	Relational DBMS

Score	2.01
Rank	#126	Overall
	#21	Key-value stores
	#3	Native XML DBMS

Score	0.74
Rank	#222	Overall
	#9	RDF stores

Website

aws.amazon.com/simpledb

www.ehcache.org

google.github.io/lovefield

www.oracle.com/database/technologies/related/berkeleydb.html

rdf4j.org

Technical documentation

docs.aws.amazon.com/simpledb

www.ehcache.org/documentation

github.com/google/lovefield/blob/master/docs/spec_index.md

docs.oracle.com/cd/E17076_05/html/index.html

rdf4j.org/documentation

Developer

Amazon

Terracotta Inc, owned by Software AG

Google

Oracle

originally developed by Sleepycat, which was acquired by Oracle

Since 2016 officially forked into an Eclipse project, former developer was Aduna Software.

Initial release

2007

2009

2014

1994

2004

Current release

3.10.0, March 2022

2.1.12, February 2017

18.1.40, May 2020

License

Commercial or Open Source

commercial

Open Source

Apache Version 2; commercial licenses available

Open Source

Apache 2.0

Open Source

commercial license available

Open Source

Eclipse Distribution License (EDL), v1.0.

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

JavaScript

C, Java, C++ (depending on the Berkeley DB edition)

Java

Server operating systems

hosted

All OS with a Java VM

server-less, requires a JavaScript environment (browser, Node.js)

tested with Chrome, Firefox, IE, Safari

AIX
Android
FreeBSD
iOS
Linux
OS X
Solaris
VxWorks
Windows

Linux
OS X
Unix
Windows

Data scheme

schema-free

yes

schema-free

yes

RDF Schemas

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.

yes

only with the Berkeley DB XML edition

Secondary indexes

yes

All columns are indexed automatically

yes

SQL

Support of SQL

SQL-like query language

via JavaScript builder pattern

yes

SQL interfaced based on SQLite is available

APIs and other access methods

RESTful HTTP API

JCache

Java API
RIO

RDF Input/Output
Sail API
SeRQL

Sesame RDF Query Language
Sesame REST HTTP Protocol
SPARQL

Supported programming languages

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

Java

JavaScript

.Net

Figaro is a .Net framework assembly that extends Berkeley DB XML into an embeddable database engine for .NET
others

Third-party libraries to manipulate Berkeley DB files are available for many languages
C
C#
C++
Java
JavaScript (Node.js)

3rd party binding
Perl
Python
Tcl

Java
PHP
Python

Server-side scripts

Stored procedures

yes

Triggers

yes

Cache Event Listeners

Using read-only observers

yes

only for the SQL API

yes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding must be implemented in the application

Sharding

by using Terracotta Server

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes

by using Terracotta Server

none

Source-replica replication

none

MapReduce

Offers an API for user-defined Map/Reduce methods

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)

Foreign keys

Referential integrity

yes

Transaction concepts

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

Concurrent data updates can be detected by the application

yes

supports JTA and can work as an XA resource

ACID

Isolation support depends on the API used

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

using a tiered cache-storage approach

yes, by using IndexedDB or the cloud service Firebase Realtime Database

yes

in-memory storage is supported as well

In-memory capabilities

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

yes

using MemoryDB

yes

User concepts

Access control

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

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More resources

DB-Engines blog posts

The popularity of cloud-based DBMSs has increased tenfold in four years
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