DBMS > Bangdb vs. eXtremeDB vs. OpenQM vs. TimesTen

System Properties Comparison Bangdb vs. eXtremeDB vs. OpenQM vs. TimesTen

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Editorial information provided by DB-Engines

Name

Description

Converged and high performance database for device data, events, time series, document and graph

Natively in-memory DBMS with options for persistency, high-availability and clustering

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

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

Document store
Graph DBMS
Time Series DBMS

Relational DBMS
Time Series DBMS

Multivalue DBMS

Relational DBMS

Secondary database models

Spatial DBMS

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

Score	0.07
Rank	#346	Overall
	#47	Document stores
	#35	Graph DBMS
	#32	Time Series DBMS

Score	0.79
Rank	#212	Overall
	#100	Relational DBMS
	#18	Time Series DBMS

Score	0.28
Rank	#291	Overall
	#10	Multivalue DBMS

Score	1.26
Rank	#164	Overall
	#75	Relational DBMS

Website

bangdb.com

www.mcobject.com

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

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

Technical documentation

docs.bangdb.com

www.mcobject.com/docs/extremedb.htm

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

Developer

Sachin Sinha, BangDB

McObject

Rocket Software, originally Martin Phillips

Oracle

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

Initial release

2012

2001

1993

1998

Current release

BangDB 2.0, October 2021

8.2, 2021

3.4-12

Release 22.1

License

Commercial or Open Source

Open Source

BSD 3

commercial

Open Source

GPLv2, extended 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

C, C++

C and C++

Server operating systems

Linux

AIX
HP-UX
Linux
macOS
Solaris
Windows

AIX
FreeBSD
Linux
macOS
Raspberry Pi
Solaris
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

with some exceptions

yes

Typing

predefined data types such as float or date

yes: string, long, double, int, geospatial, stream, events

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.

support of XML interfaces available

yes

Secondary indexes

yes

secondary, composite, nested, reverse, geospatial

yes

SQL

Support of SQL

SQL like support with command line tool

yes

with the option: eXtremeSQL

yes

APIs and other access methods

Proprietary protocol
RESTful HTTP API

.NET Client API
JDBC
JNI
ODBC
Proprietary protocol
RESTful HTTP API

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

Supported programming languages

C
C#
C++
Java
Python

.Net
C
C#
C++
Java
Lua
Python
Scala

.Net
Basic
C
Java
Objective C
PHP
Python

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

Server-side scripts

Stored procedures

yes

PL/SQL

Triggers

yes, Notifications (with Streaming only)

yes

by defining events

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding (enterprise version only). P2P based virtual network overlay with consistent hashing and chord algorithm

horizontal partitioning / sharding

yes

none

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor, Knob for CAP (enterprise version only)

Active Replication Fabric™ for IoT
Multi-source replication

by means of eXtremeDB Cluster option
Source-replica replication

by means of eXtremeDB High Availability option

yes

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, set CAP knob accordingly

Immediate Consistency

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

ACID

Concurrency

Support for concurrent manipulation of data

yes, optimistic concurrency control

yes

Optimistic (MVCC) and pessimistic (locking) strategies available

yes

Durability

Support for making data persistent

yes, implements WAL (Write ahead log) as well

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, run db with in-memory only mode

yes

User concepts

Access control

yes (enterprise version only)

Access rights can be defined down to the item level

fine grained access rights according to SQL-standard

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