DBMS > Bangdb vs. eXtremeDB vs. HarperDB vs. TerminusDB

System Properties Comparison Bangdb vs. eXtremeDB vs. HarperDB vs. TerminusDB

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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

Ultra-low latency distributed database with an intuitive REST API supporting NoSQL and SQL (including joins). Deployment of functions and databases simultaneously with a consolidated node-level architecture.

Scalable Graph Database platform making enterprise data available by exploiting inferred entities and relationships

Primary database model

Document store
Graph DBMS
Time Series DBMS

Relational DBMS
Time Series DBMS

Document store

Graph DBMS

Secondary database models

Spatial DBMS

Document store
RDF store

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

Score	0.16
Rank	#338	Overall
	#47	Document stores
	#32	Graph DBMS
	#31	Time Series DBMS

Score	0.80
Rank	#214	Overall
	#99	Relational DBMS
	#18	Time Series DBMS

Score	0.60
Rank	#244	Overall
	#38	Document stores

Score	0.23
Rank	#316	Overall
	#27	Graph DBMS

Website

Technical documentation

docs.bangdb.com

www.mcobject.com/docs/extremedb.htm

docs.harperdb.io/docs

terminusdb.github.io/terminusdb/#

Developer

Sachin Sinha, BangDB

McObject

HarperDB

DataChemist Ltd.

Initial release

2012

2001

2017

2018

Current release

BangDB 2.0, October 2021

8.2, 2021

3.1, August 2021

11.0.0, January 2023

License

Commercial or Open Source

Open Source

BSD 3

commercial

free community edition available

Open Source

GPL V3

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++

Node.js

Prolog, Rust

Server operating systems

Linux

AIX
HP-UX
Linux
macOS
Solaris
Windows

Linux
OS X

Linux

Data scheme

schema-free

yes

dynamic schema

yes

Typing

predefined data types such as float or date

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

yes

JSON data types

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

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

SQL-like data manipulation statements

SQL-like query language (WOQL)

APIs and other access methods

Proprietary protocol
RESTful HTTP API

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

JDBC
ODBC
React Hooks
RESTful HTTP/JSON API
WebSocket

OWL
RESTful HTTP API
WOQL (Web Object Query Language)

Supported programming languages

C
C#
C++
Java
Python

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

.Net
C
C#
C++
ColdFusion
D
Dart
Delphi
Erlang
Go
Haskell
Java
JavaScript (Node.js)
Lisp
MatLab
Objective C
Perl
PHP
PowerShell
Prolog
Python
R
Ruby
Rust
Scala
Swift

JavaScript
Python

Server-side scripts

Stored procedures

yes

Custom Functions

since release 3.1

yes

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

A table resides as a whole on one (or more) nodes in a cluster

Graph Partitioning

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

the nodes on which a table resides can be defined

Journaling Streams

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

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

Atomic execution of specific operations

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

yes, using LMDB

yes

in-memory journaling

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 for users and roles

Role-based access control

More information provided by the system vendor

Specific characteristics

eXtremeDB is an in-memory and/or persistent database system that offers an ultra-small...
» more

Competitive advantages

eXtremeDB databases can be modeled relationally or as objects and can utilize SQL...
» more

Typical application scenarios

IoT application across all markets: Industrial Control, Netcom, Telecom, Defense,...
» more

Key customers

Schneider Electronics, F5 Networks, TNS, Boeing, Northrop Grumman, GoPro, ViaSat,...
» more

Market metrics

With hundreds of customers and over 30 million devices/applications using the product...
» more

Licensing and pricing models

For server use cases, there is a simple per-server license irrespective of the number...
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and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

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