DBMS > Kdb vs. Kinetica vs. SQLite vs. TimesTen vs. Transwarp StellarDB

System Properties Comparison Kdb vs. Kinetica vs. SQLite vs. TimesTen vs. Transwarp StellarDB

Editorial information provided by DB-Engines

Name

Description

High performance Time Series DBMS

Fully vectorized database across both GPUs and CPUs

Widely used embeddable, in-process RDBMS

In-Memory RDBMS compatible to Oracle

A distributed graph DBMS built for enterprise-level graph applications

Primary database model

Time Series DBMS
Vector DBMS

Relational DBMS

Graph DBMS

Secondary database models

Relational DBMS

Spatial DBMS
Time Series DBMS

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

Score	7.71
Rank	#49	Overall
	#2	Time Series DBMS
	#1	Vector DBMS

Score	0.66
Rank	#234	Overall
	#107	Relational DBMS

Score	111.41
Rank	#10	Overall
	#7	Relational DBMS

Score	1.36
Rank	#161	Overall
	#75	Relational DBMS

Score	0.07
Rank	#371	Overall
	#39	Graph DBMS

Website

kx.com

www.kinetica.com

www.sqlite.org

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

www.transwarp.cn/en/product/stellardb

Technical documentation

code.kx.com

docs.kinetica.com

www.sqlite.org/docs.html

docs.oracle.com/database/timesten-18.1

Developer

Kx Systems, a division of First Derivatives plc

Kinetica

Dwayne Richard Hipp

Oracle, TimesTen Performance Software, HP

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

Transwarp

Initial release

2000

kdb was released 2000, kdb+ in 2003

2012

2000

1998

Current release

3.6, May 2018

7.1, August 2021

3.46.0 (23 May 2024), May 2024

11 Release 2 (11.2.2.8.0)

License

Commercial or Open Source

commercial

free 32-bit version

commercial

Open Source

Public Domain

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++

Server operating systems

Linux
OS X
Solaris
Windows

Linux

server-less

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

Data scheme

yes

dynamic column types

yes

Typing

predefined data types such as float or date

yes

not rigid because of 'dynamic typing' concept.

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

table attribute 'grouped'

yes

SQL

Support of SQL

SQL-like query language (q)

SQL-like DML and DDL statements

yes

SQL-92 is not fully supported

yes

SQL-like query language

APIs and other access methods

HTTP API
JDBC
Jupyter
Kafka
ODBC
WebSocket

JDBC
ODBC
RESTful HTTP API

ADO.NET

inofficial driver
JDBC

inofficial driver
ODBC

inofficial driver

JDBC
ODBC
ODP.NET
Oracle Call Interface (OCI)

OpenCypher

Supported programming languages

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

C++
Java
JavaScript (Node.js)
Python

Actionscript
Ada
Basic
C
C#
C++
D
Delphi
Forth
Fortran
Haskell
Java
JavaScript
Lisp
Lua
MatLab
Objective-C
OCaml
Perl
PHP
PL/SQL
Python
R
Ruby
Scala
Scheme
Smalltalk
Tcl

C
C++
Java
PL/SQL

Server-side scripts

Stored procedures

user defined functions

PL/SQL

Triggers

yes

with views

yes

triggers when inserted values for one or more columns fall within a specified range

yes

Partitioning methods

Methods for storing different data on different nodes

horizontal partitioning

Sharding

none

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

none

Multi-source replication
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

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

via file-system locks

yes

Durability

Support for making data persistent

yes

by means of logfiles and checkpoints

yes

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

yes

GPU vRAM or System RAM

yes

User concepts

Access control

rights management via user accounts

Access rights for users and roles on table level

fine grained access rights according to SQL-standard

yes

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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