DBMS > IBM Db2 Event Store vs. MySQL vs. Percona Server for MongoDB vs. Quasardb

System Properties Comparison IBM Db2 Event Store vs. MySQL vs. Percona Server for MongoDB vs. Quasardb

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Editorial information provided by DB-Engines

Name

Description

Distributed Event Store optimized for Internet of Things use cases

Widely used open source RDBMS

A drop-in replacement for MongoDB Community Edition with enterprise-grade features.

Distributed, high-performance timeseries database

Primary database model

Event Store
Time Series DBMS

Relational DBMS

Key/Value like access via memcached API

Document store

Time Series DBMS

Secondary database models

Document store
Spatial DBMS

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

Score	0.27
Rank	#309	Overall
	#2	Event Stores
	#28	Time Series DBMS

Score	1061.34
Rank	#2	Overall
	#2	Relational DBMS

Score	0.60
Rank	#246	Overall
	#39	Document stores

Score	0.21
Rank	#322	Overall
	#29	Time Series DBMS

Website

www.ibm.com/products/db2-event-store

www.mysql.com

www.percona.com/mongodb/software/percona-server-for-mongodb

quasar.ai

Technical documentation

www.ibm.com/docs/en/db2-event-store

dev.mysql.com/doc

docs.percona.com/percona-distribution-for-mongodb

doc.quasar.ai/master

Developer

IBM

Oracle

since 2010, originally MySQL AB, then Sun

Percona

quasardb

Initial release

2017

1995

2015

2009

Current release

2.0

8.4.0, April 2024

3.4.10-2.10, November 2017

3.14.1, January 2024

License

Commercial or Open Source

commercial

free developer edition available

Open Source

GPL version 2. Commercial licenses with extended functionallity are available

Open Source

GPL Version 2

commercial

Free community edition, Non-profit organizations and non-commercial usage are eligible for free licenses

Cloud-based only

Only available as a cloud service

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Database as a Service

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Implementation language

C and C++

C++

Server operating systems

Linux

Linux, macOS, Windows for the developer addition

FreeBSD
Linux
OS X
Solaris
Windows

Linux

BSD
Linux
OS X
Windows

Data scheme

yes

schema-free

Typing

predefined data types such as float or date

yes

integer and binary

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

with tags

SQL

Support of SQL

yes

through the embedded Spark runtime

yes

with proprietary extensions

SQL-like query language

APIs and other access methods

ADO.NET
DB2 Connect
JDBC
ODBC
RESTful HTTP API

ADO.NET
JDBC
ODBC
Proprietary native API

proprietary protocol using JSON

HTTP API

Supported programming languages

C
C#
C++
Cobol
Delphi
Fortran
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Ruby
Scala
Visual Basic

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

Actionscript
C
C#
C++
Clojure
ColdFusion
D
Dart
Delphi
Erlang
Go
Groovy
Haskell
Java
JavaScript
Lisp
Lua
MatLab
Perl
PHP
PowerShell
Prolog
Python
R
Ruby
Scala
Smalltalk

.Net
C
C#
C++
Go
Java
JavaScript (Node.js)
PHP
Python
R

Server-side scripts

Stored procedures

yes

proprietary syntax

JavaScript

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

horizontal partitioning, sharding with MySQL Cluster or MySQL Fabric

Sharding

consistent hashing

Replication methods

Methods for redundantly storing data on multiple nodes

Active-active shard replication

Multi-source replication
Source-replica replication

Source-replica replication

Source-replica replication with selectable replication factor

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

with Hadoop integration

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

Immediate Consistency

Eventual Consistency
Immediate Consistency

Immediate 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

Concurrency

Support for concurrent manipulation of data

No - written data is immutable

yes

table locks or row locks depending on storage engine

yes

Durability

Support for making data persistent

Yes - Synchronous writes to local disk combined with replication and asynchronous writes in parquet format to permanent shared storage

yes

by using LevelDB

In-memory capabilities

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

yes

via In-Memory Engine

yes

Transient mode

User concepts

Access control

fine grained access rights according to SQL-standard

Users with fine-grained authorization concept

no user groups or roles

Access rights for users and roles

Cryptographically strong user authentication and audit trail

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