DBMS > Infobright vs. Kinetica vs. LevelDB vs. MySQL vs. SAP IQ

System Properties Comparison Infobright vs. Kinetica vs. LevelDB vs. MySQL vs. SAP IQ

Editorial information provided by DB-Engines

Name

Description

High performant column-oriented DBMS for analytic workloads using MySQL or PostgreSQL as a frontend

Fully vectorized database across both GPUs and CPUs

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

Widely used open source RDBMS

Columnar RDBMS optimized for Big Data analytics

Primary database model

Relational DBMS

Key-value store

Relational DBMS

Key/Value like access via memcached API

Relational DBMS

column-oriented

Secondary database models

Spatial DBMS
Time Series DBMS

Document store
Spatial DBMS

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

Score	1.02
Rank	#192	Overall
	#90	Relational DBMS

Score	0.66
Rank	#234	Overall
	#107	Relational DBMS

Score	2.25
Rank	#115	Overall
	#19	Key-value stores

Score	1061.34
Rank	#2	Overall
	#2	Relational DBMS

Score	2.64
Rank	#108	Overall
	#52	Relational DBMS

Website

ignitetech.com/softwarelibrary/infobrightdb

www.kinetica.com

github.com/google/leveldb

www.mysql.com

www.sap.com/products/technology-platform/sybase-iq-big-data-management.html

Technical documentation

docs.kinetica.com

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

dev.mysql.com/doc

help.sap.com/docs/SAP_IQ

Developer

Ignite Technologies Inc.; formerly InfoBright Inc.

Kinetica

Google

Oracle

since 2010, originally MySQL AB, then Sun

SAP, formerly Sybase

Initial release

2005

2012

2011

1995

1994

Current release

7.1, August 2021

1.23, February 2021

8.4.0, April 2024

16.1 SPS04, April 2019

License

Commercial or Open Source

commercial

The open source (GPLv2) version did not support inserts/updates/deletes and was discontinued with July 2016

commercial

Open Source

BSD

Open Source

GPL version 2. Commercial licenses with extended functionallity are available

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.

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Implementation language

C, C++

C++

C and C++

Server operating systems

Linux
Windows

Linux

Illumos
Linux
OS X
Windows

FreeBSD
Linux
OS X
Solaris
Windows

AIX
HP-UX
Linux
Solaris
Windows

Data scheme

yes

schema-free

yes

Typing

predefined data types such as float or date

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

Knowledge Grid Technology used instead

yes

SQL

Support of SQL

yes

SQL-like DML and DDL statements

yes

with proprietary extensions

yes

APIs and other access methods

ADO.NET
JDBC
ODBC

JDBC
ODBC
RESTful HTTP API

ADO.NET
JDBC
ODBC
Proprietary native API

ADO.NET
JDBC
ODBC
RESTful HTTP API

Supported programming languages

.Net
C
C#
C++
D
Eiffel
Erlang
Haskell
Java
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl

C++
Java
JavaScript (Node.js)
Python

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

C
C#
C++
Java
Perl
PHP
Python
Ruby

Server-side scripts

Stored procedures

user defined functions

yes

proprietary syntax

yes

Triggers

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

none

Sharding

none

horizontal partitioning, sharding with MySQL Cluster or MySQL Fabric

shared disk or shared nothing architectures with SAP IQ Multiplexer

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

none

Multi-source replication
Source-replica replication

SAP/Sybase Replication Server

MapReduce

Offers an API for user-defined Map/Reduce methods

Hadoop integration

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Immediate Consistency or Eventual Consistency depending on configuration

Immediate Consistency

Foreign keys

Referential integrity

yes

not for MyISAM storage engine

yes

Transaction concepts

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

ACID

not for MyISAM storage engine

ACID

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 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

fine grained access rights according to SQL-standard

exploiting MySQL or PostgreSQL frontend capabilities

Access rights for users and roles on table level

Users with fine-grained authorization concept

no user groups or roles

fine grained access rights according to SQL-standard

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