DBMS > Ehcache vs. Oracle Berkeley DB vs. OrigoDB vs. TimesTen

System Properties Comparison Ehcache vs. Oracle Berkeley DB vs. OrigoDB vs. TimesTen

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Editorial information provided by DB-Engines

Name

Description

A widely adopted Java cache with tiered storage options

Widely used in-process key-value store

A fully ACID in-memory object graph database

An in-memory SQL relational database that delivers microsecond response and high throughput for OLTP applications. TimesTen can be deployed as a standalone database or as a cache to a backend Oracle database.

Primary database model

Key-value store

supports sorted and unsorted key sets
Native XML DBMS

in the Oracle Berkeley DB XML version

Document store
Object oriented DBMS

Relational DBMS

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

Score	4.79
Rank	#66	Overall
	#8	Key-value stores

Score	1.88
Rank	#130	Overall
	#23	Key-value stores
	#3	Native XML DBMS

Score	0.00
Rank	#385	Overall
	#54	Document stores
	#21	Object oriented DBMS

Score	1.26
Rank	#164	Overall
	#75	Relational DBMS

Website

www.ehcache.org

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

origodb.com

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

Technical documentation

www.ehcache.org/documentation

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

origodb.com/docs

docs.oracle.com/en/database/other-databases/timesten/index.html

Developer

Terracotta Inc, owned by Software AG

Oracle

originally developed by Sleepycat, which was acquired by Oracle

Robert Friberg et al

Oracle

originally founded in HP Labs it was acquired by Oracle in 2005

Initial release

2009

1994

2009

under the name LiveDB

1998

Current release

3.10.0, March 2022

18.1.40, May 2020

Release 22.1

License

Commercial or Open Source

Open Source

Apache Version 2; commercial licenses available

Open Source

commercial license available

Open Source

commercial

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

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

Implementation language

Java

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

Server operating systems

All OS with a Java VM

AIX
Android
FreeBSD
iOS
Linux
OS X
Solaris
VxWorks
Windows

Linux
Windows

IBM AIX Power PC 64-bit
Linux arm64
Linux x86-64
Solaris SPARC 64
Solaris SPARC/x86
Solaris x86-64

Data scheme

schema-free

yes

Typing

predefined data types such as float or date

yes

User defined using .NET types and collections

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

can be achieved using .NET

Secondary indexes

yes

SQL

Support of SQL

yes

SQL interfaced based on SQLite is available

yes

APIs and other access methods

JCache

.NET Client API
HTTP API
LINQ

ODBC
ODP.NET
Oracle Call Interface (OCI)
Pro*C/C++ programming interfaces
SQL and PL/SQL via JDBC

Supported programming languages

Java

.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

.Net

C
C++
Java
Node.js
PL/SQL
Python

Server-side scripts

Stored procedures

yes

PL/SQL

Triggers

yes

Cache Event Listeners

yes

only for the SQL API

yes

Domain Events

Partitioning methods

Methods for storing different data on different nodes

Sharding

by using Terracotta Server

none

horizontal partitioning

client side managed; servers are not synchronized

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes

by using Terracotta Server

Source-replica replication

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Tunable Consistency (Strong, Eventual, Weak)

Immediate Consistency or Eventual Consistency depending on configuration

Foreign keys

Referential integrity

depending on model

yes

Transaction concepts

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

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

Write ahead log

yes

by means of logfiles and checkpoints

In-memory capabilities

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

yes

User concepts

Access control

Role based authorization

fine grained access rights according to SQL-standard

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