DBMS > EJDB vs. EXASOL vs. Kdb vs. MySQL vs. SingleStore

System Properties Comparison EJDB vs. EXASOL vs. Kdb vs. MySQL vs. SingleStore

Editorial information provided by DB-Engines

Name

Description

Embeddable document-store database library with JSON representation of queries (in MongoDB style)

High-performance, in-memory, MPP database specifically designed for in-memory analytics.

Widely used open source RDBMS

MySQL wire-compliant distributed RDBMS that combines an in-memory row-oriented and a disc-based column-oriented storage with patented universal storage to handle transactional and analytical workloads in one single table type

Primary database model

Document store

Relational DBMS

Time Series DBMS
Vector DBMS

Relational DBMS

Key/Value like access via memcached API

Relational DBMS

Secondary database models

Relational DBMS

Document store
Spatial DBMS

Document store
Spatial DBMS
Time Series DBMS
Vector DBMS

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

Score	0.13
Rank	#331	Overall
	#46	Document stores

Score	1.66
Rank	#138	Overall
	#64	Relational DBMS

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

Score	1029.49
Rank	#2	Overall
	#2	Relational DBMS

Score	4.02
Rank	#74	Overall
	#39	Relational DBMS

Website

github.com/Softmotions/ejdb

Technical documentation

github.com/Softmotions/ejdb/blob/master/README.md

www.exasol.com/resources

code.kx.com

dev.mysql.com/doc

docs.singlestore.com

Developer

Softmotions

Exasol

Kx Systems, a division of First Derivatives plc

Oracle

since 2010, originally MySQL AB, then Sun

SingleStore Inc.

Initial release

2012

2000

kdb was released 2000, kdb+ in 2003

1995

2013

Current release

3.6, May 2018

9.0.0, July 2024

8.5, January 2024

License

Commercial or Open Source

Open Source

GPLv2

commercial

free 32-bit version

Open Source

GPL version 2. Commercial licenses with extended functionallity are available

commercial

free developer edition available

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 and C++

C++, Go

Server operating systems

server-less

Linux
OS X
Solaris
Windows

FreeBSD
Linux
OS X
Solaris
Windows

Linux

64 bit version required

Data scheme

schema-free

yes

Typing

predefined data types such as float or date

yes

string, integer, double, bool, date, object_id

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

yes

SQL-like query language (q)

yes

with proprietary extensions

yes

but no triggers and foreign keys

APIs and other access methods

in-process shared library

.Net
JDBC
ODBC
WebSocket

HTTP API
JDBC
Jupyter
Kafka
ODBC
WebSocket

ADO.NET
JDBC
ODBC
Proprietary native API

Cluster Management API

as HTTP Rest and CLI
HTTP API
JDBC
MongoDB API
ODBC

Supported programming languages

Actionscript
C
C#
C++
Go
Java
JavaScript (Node.js)
Lua
Objective-C
Pike
Python
Ruby

Java
Lua
Python
R

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

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

Bash
C
C#
Java
JavaScript (Node.js)
Python

Server-side scripts

Stored procedures

user defined functions

yes

proprietary syntax

yes

Triggers

yes

with views

yes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

horizontal partitioning

horizontal partitioning, sharding with MySQL Cluster or MySQL Fabric

Sharding

hash partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

none

Source-replica replication

Multi-source replication
Source-replica replication

Source-replica replication

stores two copies of each physical data partition on two separate nodes

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Hadoop integration

similar paradigm used for internal processing

can define user-defined aggregate functions for map-reduce-style calculations

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Foreign keys

Referential integrity

typically not needed, however similar functionality with collection joins possible

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

Concurrency

Support for concurrent manipulation of data

yes

Read/Write Locking

yes

table locks or row locks depending on storage engine

yes, multi-version concurrency control (MVCC)

Durability

Support for making data persistent

yes

All updates are persistent, including those to disk-based columnstores and memory-based row stores. Transaction commits are supported via write-ahead log.

In-memory capabilities

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

yes

User concepts

Access control

Access rights for users, groups and roles according to SQL-standard

rights management via user accounts

Users with fine-grained authorization concept

no user groups or roles

Fine grained access control via users, groups and roles

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