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

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

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Editorial information provided by DB-Engines

Name

Description

A widely adopted Java cache with tiered storage options

Scalable Time Series DBMS based on HBase

Widely used in-process key-value store

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

Time Series DBMS

Key-value store

supports sorted and unsorted key sets
Native XML DBMS

in the Oracle Berkeley DB XML version

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	1.59
Rank	#140	Overall
	#12	Time Series DBMS

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

Score	1.26
Rank	#164	Overall
	#75	Relational DBMS

Website

www.ehcache.org

opentsdb.net

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

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

Technical documentation

www.ehcache.org/documentation

opentsdb.net/docs/build/html/index.html

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

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

Developer

Terracotta Inc, owned by Software AG

currently maintained by Yahoo and other contributors

Oracle

originally developed by Sleepycat, which was acquired by Oracle

Oracle

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

Initial release

2009

2011

1994

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

LGPL

Open Source

commercial license available

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

Linux
Windows

AIX
Android
FreeBSD
iOS
Linux
OS X
Solaris
VxWorks
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

numeric data for metrics, strings for tags

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

SQL

Support of SQL

yes

SQL interfaced based on SQLite is available

yes

APIs and other access methods

JCache

HTTP API
Telnet API

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

Supported programming languages

Java

Erlang
Go
Java
Python
R
Ruby

.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

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

Server-side scripts

Stored procedures

PL/SQL

Triggers

yes

Cache Event Listeners

yes

only for the SQL API

Partitioning methods

Methods for storing different data on different nodes

Sharding

by using Terracotta Server

Sharding

based on HBase

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes

by using Terracotta Server

selectable replication factor

based on HBase

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

based on HBase

Immediate Consistency or Eventual Consistency depending on configuration

Foreign keys

Referential integrity

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

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

fine grained access rights according to SQL-standard

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