DBMS > Bangdb vs. EsgynDB vs. KairosDB vs. RDF4J vs. TimesTen

System Properties Comparison Bangdb vs. EsgynDB vs. KairosDB vs. RDF4J vs. TimesTen

Editorial information provided by DB-Engines

Name

Description

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

Enterprise-class SQL-on-Hadoop solution, powered by Apache Trafodion

Distributed Time Series DBMS based on Cassandra or H2

RDF4J is a Java framework for processing RDF data, supporting both memory-based and a disk-based storage.

In-Memory RDBMS compatible to Oracle

Primary database model

Document store
Graph DBMS
Time Series DBMS

Secondary database models

Spatial DBMS

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

Score	0.08
Rank	#347	Overall
	#47	Document stores
	#34	Graph DBMS
	#31	Time Series DBMS

Score	0.16
Rank	#329	Overall
	#146	Relational DBMS

Score	0.62
Rank	#239	Overall
	#20	Time Series DBMS

Score	0.69
Rank	#230	Overall
	#9	RDF stores

Score	1.31
Rank	#163	Overall
	#74	Relational DBMS

Website

bangdb.com

www.esgyn.cn

github.com/kairosdb/kairosdb

rdf4j.org

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

Technical documentation

docs.bangdb.com

kairosdb.github.io

rdf4j.org/documentation

docs.oracle.com/database/timesten-18.1

Developer

Sachin Sinha, BangDB

Esgyn

Since 2016 officially forked into an Eclipse project, former developer was Aduna Software.

Oracle, TimesTen Performance Software, HP

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

Initial release

2012

2015

2013

2004

1998

Current release

BangDB 2.0, October 2021

1.2.2, November 2018

11 Release 2 (11.2.2.8.0)

License

Commercial or Open Source

Open Source

BSD 3

commercial

Open Source

Apache 2.0

Open Source

Eclipse Distribution License (EDL), v1.0.

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++, Java

Java

Server operating systems

Linux

Linux
OS X
Windows

Linux
OS X
Unix
Windows

AIX
HP-UX
Linux
OS X
Solaris SPARC/x86
Windows

Data scheme

schema-free

yes

schema-free

yes

RDF Schemas

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.

Secondary indexes

yes

secondary, composite, nested, reverse, geospatial

yes

SQL

Support of SQL

SQL like support with command line tool

yes

APIs and other access methods

Proprietary protocol
RESTful HTTP API

ADO.NET
JDBC
ODBC

Graphite protocol
HTTP REST
Telnet API

Java API
RIO

RDF Input/Output
Sail API
SeRQL

Sesame RDF Query Language
Sesame REST HTTP Protocol
SPARQL

JDBC
ODBC
ODP.NET
Oracle Call Interface (OCI)

Supported programming languages

C
C#
C++
Java
Python

All languages supporting JDBC/ODBC/ADO.Net

Java
JavaScript

Node.js
PHP
Python

Java
PHP
Python

C
C++
Java
PL/SQL

Server-side scripts

Stored procedures

Java Stored Procedures

yes

PL/SQL

Triggers

yes, Notifications (with Streaming only)

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

Sharding

based on Cassandra

none

Replication methods

Methods for redundantly storing data on multiple nodes

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

Multi-source replication between multi datacenters

selectable replication factor

based on Cassandra

none

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Tunable consistency, set CAP knob accordingly

Immediate Consistency

Eventual Consistency

based on Cassandra
Immediate Consistency

based on Cassandra

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

Isolation support depends on the API used

ACID

Concurrency

Support for concurrent manipulation of data

yes, optimistic concurrency control

yes

Durability

Support for making data persistent

yes, implements WAL (Write ahead log) as well

yes

in-memory storage is supported 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)

fine grained access rights according to SQL-standard

simple password-based access control

fine grained access rights according to SQL-standard

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