DBMS > Kdb vs. LevelDB vs. MySQL vs. RDF4J vs. Sequoiadb

System Properties Comparison Kdb vs. LevelDB vs. MySQL vs. RDF4J vs. Sequoiadb

Editorial information provided by DB-Engines

Name

Description

High performance Time Series DBMS

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

Widely used open source RDBMS

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

NewSQL database with distributed OLTP and SQL

Primary database model

Time Series DBMS
Vector DBMS

Key-value store

Relational DBMS

Key/Value like access via memcached API

RDF store

Document store
Relational DBMS

Secondary database models

Relational DBMS

Document store
Spatial DBMS

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

Score	7.70
Rank	#53	Overall
	#3	Time Series DBMS
	#1	Vector DBMS

Score	2.75
Rank	#107	Overall
	#19	Key-value stores

Score	1087.72
Rank	#2	Overall
	#2	Relational DBMS

Score	0.71
Rank	#231	Overall
	#9	RDF stores

Score	0.48
Rank	#260	Overall
	#41	Document stores
	#121	Relational DBMS

Website

kx.com

github.com/google/leveldb

www.mysql.com

rdf4j.org

www.sequoiadb.com

Technical documentation

code.kx.com

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

dev.mysql.com/doc

rdf4j.org/documentation

www.sequoiadb.com/en/index.php?m=Files&a=index

Developer

Kx Systems, a division of First Derivatives plc

Google

Oracle

since 2010, originally MySQL AB, then Sun

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

Sequoiadb Ltd.

Initial release

2000

kdb was released 2000, kdb+ in 2003

2011

1995

2004

2013

Current release

3.6, May 2018

1.23, February 2021

8.3.0, January 2024

License

Commercial or Open Source

commercial

free 32-bit version

Open Source

BSD

Open Source

GPL version 2. Commercial licenses with extended functionallity are available

Open Source

Eclipse Distribution License (EDL), v1.0.

Open Source

Server: AGPL; Client: Apache V2

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

C++

C and C++

Java

C++

Server operating systems

Linux
OS X
Solaris
Windows

Illumos
Linux
OS X
Windows

FreeBSD
Linux
OS X
Solaris
Windows

Linux
OS X
Unix
Windows

Linux

Data scheme

yes

schema-free

yes

RDF Schemas

schema-free

Typing

predefined data types such as float or date

yes

oid, date, timestamp, binary, regex

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

table attribute 'grouped'

yes

SQL

Support of SQL

SQL-like query language (q)

yes

with proprietary extensions

SQL-like query language

APIs and other access methods

HTTP API
JDBC
Jupyter
Kafka
ODBC
WebSocket

ADO.NET
JDBC
ODBC
Proprietary native API

Java API
RIO

RDF Input/Output
Sail API
SeRQL

Sesame RDF Query Language
Sesame REST HTTP Protocol
SPARQL

proprietary protocol using JSON

Supported programming languages

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

Ada
C
C#
C++
D
Delphi
Eiffel
Erlang
Haskell
Java
JavaScript (Node.js)
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl

Java
PHP
Python

.Net
C++
Java
PHP
Python

Server-side scripts

Stored procedures

user defined functions

yes

proprietary syntax

yes

JavaScript

Triggers

yes

with views

yes

Partitioning methods

Methods for storing different data on different nodes

horizontal partitioning

none

horizontal partitioning, sharding with MySQL Cluster or MySQL Fabric

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

none

Multi-source replication
Source-replica replication

none

Source-replica replication

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

Immediate Consistency

Eventual Consistency

Foreign keys

Referential integrity

yes

not for MyISAM storage engine

Transaction concepts

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

ACID

not for MyISAM storage engine

ACID

Isolation support depends on the API used

Document is locked during a transaction

Concurrency

Support for concurrent manipulation of data

yes

table locks or row locks depending on storage engine

yes

Durability

Support for making data persistent

yes

with automatic compression on writes

yes

in-memory storage is supported as well

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

rights management via user accounts

Users with fine-grained authorization concept

no user groups or roles

simple password-based access control

More information provided by the system vendor

Specific characteristics

Integrated columnar database & programming system for streaming, real time and historical...
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Competitive advantages

provides seamless scalability; runs on industry standard server platforms; is top-ranked...
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Typical application scenarios

tick database streaming sensor data massive intelligence applications oil and gas...
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Key customers

Goldman Sachs Morgan Stanley Merrill Lynch J.P. Morgan Deutsche Bank IEX Securities...
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Market metrics

kdb+ performance and reliability proven by our customers in critical infrastructure...
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Licensing and pricing models

upon request
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