DBMS > Bangdb vs. Kdb vs. LevelDB vs. RDF4J

System Properties Comparison Bangdb vs. Kdb vs. LevelDB vs. RDF4J

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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

High performance Time Series DBMS

Embeddable fast key-value storage library that provides an ordered mapping from string keys to string values

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

Primary database model

Document store
Graph DBMS
Time Series DBMS

Time Series DBMS
Vector DBMS

Key-value store

RDF store

Secondary database models

Spatial DBMS

Relational 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	7.55
Rank	#53	Overall
	#3	Time Series DBMS
	#1	Vector DBMS

Score	2.35
Rank	#111	Overall
	#19	Key-value stores

Score	0.69
Rank	#230	Overall
	#9	RDF stores

Website

bangdb.com

kx.com

github.com/google/leveldb

rdf4j.org

Technical documentation

docs.bangdb.com

code.kx.com

github.com/google/leveldb/blob/main/doc/index.md

rdf4j.org/documentation

Developer

Sachin Sinha, BangDB

Kx Systems, a division of First Derivatives plc

Google

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

Initial release

2012

2000

kdb was released 2000, kdb+ in 2003

2011

2004

Current release

BangDB 2.0, October 2021

3.6, May 2018

1.23, February 2021

License

Commercial or Open Source

Open Source

BSD 3

commercial

free 32-bit version

Open Source

BSD

Open Source

Eclipse Distribution License (EDL), v1.0.

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

Server operating systems

Linux

Linux
OS X
Solaris
Windows

Illumos
Linux
OS X
Windows

Linux
OS X
Unix
Windows

Data scheme

schema-free

yes

schema-free

yes

RDF Schemas

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.

yes

Secondary indexes

yes

secondary, composite, nested, reverse, geospatial

yes

table attribute 'grouped'

yes

SQL

Support of SQL

SQL like support with command line tool

SQL-like query language (q)

APIs and other access methods

Proprietary protocol
RESTful HTTP API

HTTP API
JDBC
Jupyter
Kafka
ODBC
WebSocket

Java API
RIO

RDF Input/Output
Sail API
SeRQL

Sesame RDF Query Language
Sesame REST HTTP Protocol
SPARQL

Supported programming languages

C
C#
C++
Java
Python

C
C#
C++
Go
J
Java
JavaScript
Lua
MatLab
Perl
PHP
Python
R
Scala

C++
Go
Java

3rd party binding
JavaScript (Node.js)

3rd party binding
Python

3rd party binding

Java
PHP
Python

Server-side scripts

Stored procedures

user defined functions

yes

Triggers

yes, Notifications (with Streaming only)

yes

with views

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

none

Replication methods

Methods for redundantly storing data on multiple nodes

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

Source-replica replication

none

MapReduce

Offers an API for user-defined Map/Reduce methods

similar paradigm used for internal processing

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

Isolation support depends on the API used

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

with automatic compression on writes

yes

in-memory storage is supported as well

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)

rights management via user accounts

More information provided by the system vendor

Specific characteristics

Integrated columnar database & programming system for streaming, real time and historical...
» more

Competitive advantages

provides seamless scalability; runs on industry standard server platforms; is top-ranked...
» more

Typical application scenarios

tick database streaming sensor data massive intelligence applications oil and gas...
» more

Key customers

Goldman Sachs Morgan Stanley Merrill Lynch J.P. Morgan Deutsche Bank IEX Securities...
» more

Market metrics

kdb+ performance and reliability proven by our customers in critical infrastructure...
» more

Licensing and pricing models

upon request
» more

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