DBMS > EXASOL vs. OpenQM vs. Oracle Berkeley DB vs. SiriDB

System Properties Comparison EXASOL vs. OpenQM vs. Oracle Berkeley DB vs. SiriDB

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Editorial information provided by DB-Engines

Name

Description

High-performance, in-memory, MPP database specifically designed for in-memory analytics.

QpenQM is a high-performance, self-tuning, multi-value DBMS

Widely used in-process key-value store

Open Source Time Series DBMS

Primary database model

Relational DBMS

Multivalue DBMS

Key-value store

supports sorted and unsorted key sets
Native XML DBMS

in the Oracle Berkeley DB XML version

Time Series DBMS

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

Score	1.99
Rank	#124	Overall
	#58	Relational DBMS

Score	0.27
Rank	#298	Overall
	#10	Multivalue DBMS

Score	2.21
Rank	#117	Overall
	#20	Key-value stores
	#3	Native XML DBMS

Score	0.00
Rank	#383	Overall
	#41	Time Series DBMS

Website

www.exasol.com

www.rocketsoftware.com/products/rocket-multivalue-application-development-platform/rocket-open-qm

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

siridb.com

Technical documentation

www.exasol.com/resources

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

docs.siridb.com

Developer

Exasol

Rocket Software, originally Martin Phillips

Oracle

originally developed by Sleepycat, which was acquired by Oracle

Cesbit

Initial release

2000

1993

1994

2017

Current release

3.4-12

18.1.40, May 2020

License

Commercial or Open Source

commercial

Open Source

GPLv2, extended commercial license available

Open Source

commercial license available

Open Source

MIT License

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

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

Server operating systems

AIX
FreeBSD
Linux
macOS
Raspberry Pi
Solaris
Windows

AIX
Android
FreeBSD
iOS
Linux
OS X
Solaris
VxWorks
Windows

Linux

Data scheme

yes

with some exceptions

schema-free

yes

Typing

predefined data types such as float or date

yes

Numeric data

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

APIs and other access methods

.Net
JDBC
ODBC
WebSocket

HTTP API

Supported programming languages

Java
Lua
Python
R

.Net
Basic
C
Java
Objective C
PHP
Python

.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++
Go
Java
JavaScript (Node.js)
PHP
Python
R

Server-side scripts

Stored procedures

user defined functions

yes

Triggers

yes

only for the SQL API

Partitioning methods

Methods for storing different data on different nodes

Sharding

yes

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Source-replica replication

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Hadoop integration

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

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

User concepts

Access control

Access rights for users, groups and roles according to SQL-standard

Access rights can be defined down to the item level

simple rights management via user accounts

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