DBMS > Kdb vs. LMDB vs. MaxDB vs. MySQL vs. SAP SQL Anywhere

System Properties Comparison Kdb vs. LMDB vs. MaxDB vs. MySQL vs. SAP SQL Anywhere

Editorial information provided by DB-Engines

Name

Description

High performance Time Series DBMS

A high performant, light-weight, embedded key-value database library

A robust and reliable RDBMS optimized to run all major SAP solutions

Widely used open source RDBMS

RDBMS database and synchronization technologies for server, desktop, remote office, and mobile environments

Primary database model

Time Series DBMS
Vector DBMS

Key-value store

Relational DBMS

Key/Value like access via memcached API

Relational DBMS

Secondary database models

Relational DBMS

Document store
Spatial DBMS

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

Score	7.73
Rank	#45	Overall
	#2	Time Series DBMS
	#1	Vector DBMS

Score	1.94
Rank	#120	Overall
	#20	Key-value stores

Score	2.15
Rank	#115	Overall
	#55	Relational DBMS

Score	1029.49
Rank	#2	Overall
	#2	Relational DBMS

Score	3.50
Rank	#81	Overall
	#44	Relational DBMS

Website

kx.com

www.symas.com/symas-embedded-database-lmdb

maxdb.sap.com

www.mysql.com

www.sap.com/products/technology-platform/sql-anywhere.html

Technical documentation

code.kx.com

www.lmdb.tech/doc

maxdb.sap.com/documentation

dev.mysql.com/doc

help.sap.com/docs/SAP_SQL_Anywhere

Developer

Kx Systems, a division of First Derivatives plc

Symas

SAP, acquired from Software AG (Adabas-D) in 1997

Oracle

since 2010, originally MySQL AB, then Sun

SAP

formerly Sybase

Initial release

2000

kdb was released 2000, kdb+ in 2003

2011

1984

1995

1992

Current release

3.6, May 2018

0.9.32, January 2024

7.9.10.12, February 2024

9.0.0, July 2024

17, July 2015

License

Commercial or Open Source

commercial

free 32-bit version

Open Source

commercial

Limited community edition free

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.

Implementation language

C++

C and C++

Server operating systems

Linux
OS X
Solaris
Windows

Linux
Unix
Windows

AIX
HP-UX
Linux
Solaris
Windows

FreeBSD
Linux
OS X
Solaris
Windows

AIX
HP-UX
Linux
OS X
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

yes

table attribute 'grouped'

yes

SQL

Support of SQL

SQL-like query language (q)

yes

with proprietary extensions

yes

APIs and other access methods

HTTP API
JDBC
Jupyter
Kafka
ODBC
WebSocket

ADO.NET
JDBC
ODBC
WebDAV

ADO.NET
JDBC
ODBC
Proprietary native API

ADO.NET
HTTP API
JDBC
ODBC

Supported programming languages

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

.Net
C
C++
Clojure
Go
Haskell
Java
JavaScript (Node.js)
Lisp
Lua
MatLab
Nim
Objective C
OCaml
Perl
PHP
Python
R
Ruby
Rust
Swift
Tcl

.Net
C#
Java
Perl
PHP
Python

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++
Delphi
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby

Server-side scripts

Stored procedures

user defined functions

yes

proprietary syntax

yes, in C/C++, Java, .Net or Perl

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

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

none

Source-replica replication

Multi-source replication
Source-replica replication

Source-replica replication

Database mirroring

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

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

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

fine grained access rights according to SQL-standard

Users with fine-grained authorization concept

no user groups or roles

fine grained access rights according to SQL-standard

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...
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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...
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Licensing and pricing models

upon request
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and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.