DBMS > Apache Druid vs. Apache IoTDB vs. IBM Db2 Event Store vs. MySQL vs. Percona Server for MongoDB

System Properties Comparison Apache Druid vs. Apache IoTDB vs. IBM Db2 Event Store vs. MySQL vs. Percona Server for MongoDB

Editorial information provided by DB-Engines

Name

Description

Open-source analytics data store designed for sub-second OLAP queries on high dimensionality and high cardinality data

An IoT native database with high performance for data management and analysis, deployable on the edge and the cloud and integrated with Hadoop, Spark and Flink

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.

Primary database model

Relational DBMS
Time Series DBMS

Time Series DBMS

Event Store
Time Series DBMS

Relational DBMS

Key/Value like access via memcached API

Document store

Secondary database models

Document store
Spatial DBMS

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

Score	3.34
Rank	#88	Overall
	#48	Relational DBMS
	#7	Time Series DBMS

Score	1.18
Rank	#173	Overall
	#15	Time Series DBMS

Score	0.19
Rank	#323	Overall
	#2	Event Stores
	#28	Time Series DBMS

Score	1083.74
Rank	#2	Overall
	#2	Relational DBMS

Score	0.52
Rank	#254	Overall
	#39	Document stores

Website

druid.apache.org

iotdb.apache.org

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

www.mysql.com

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

Technical documentation

druid.apache.org/docs/latest/design

iotdb.apache.org/UserGuide/Master/QuickStart/QuickStart.html

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

dev.mysql.com/doc

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

Developer

Apache Software Foundation and contributors

Apache Software Foundation

IBM

Oracle

since 2010, originally MySQL AB, then Sun

Percona

Initial release

2012

2018

2017

1995

2015

Current release

29.0.1, April 2024

1.1.0, April 2023

2.0

8.4.0, April 2024

3.4.10-2.10, November 2017

License

Commercial or Open Source

Open Source

Apache license v2

Open Source

Apache Version 2.0

commercial

free developer edition available

Open Source

GPL version 2. Commercial licenses with extended functionallity are available

Open Source

GPL Version 2

Cloud-based only

Only available as a cloud service

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Implementation language

Java

C and C++

C++

Server operating systems

Linux
OS X
Unix

All OS with a Java VM (>= 1.8)

Linux

Linux, macOS, Windows for the developer addition

FreeBSD
Linux
OS X
Solaris
Windows

Linux

Data scheme

yes

schema-less columns are supported

yes

schema-free

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

SQL

Support of SQL

SQL for querying

SQL-like query language

yes

through the embedded Spark runtime

yes

with proprietary extensions

APIs and other access methods

JDBC
RESTful HTTP/JSON API

JDBC
Native API

ADO.NET
DB2 Connect
JDBC
ODBC
RESTful HTTP API

ADO.NET
JDBC
ODBC
Proprietary native API

proprietary protocol using JSON

Supported programming languages

Clojure
JavaScript
PHP
Python
R
Ruby
Scala

C
C#
C++
Go
Java
Python
Scala

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

Server-side scripts

Stored procedures

yes

proprietary syntax

JavaScript

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

manual/auto, time-based

horizontal partitioning (by time range) + vertical partitioning (by deviceId)

Sharding

horizontal partitioning, sharding with MySQL Cluster or MySQL Fabric

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes, via HDFS, S3 or other storage engines

selectable replication methods; using Raft/IoTConsensus algorithm to ensure strong/eventual data consistency among multiple replicas

Active-active shard replication

Multi-source replication
Source-replica replication

Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

Integration with Hadoop and Spark

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency
Strong Consistency with Raft

Eventual Consistency

Immediate Consistency

Eventual 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

Concurrency

Support for concurrent manipulation of data

yes

No - written data is immutable

yes

table locks or row locks depending on storage engine

yes

Durability

Support for making data persistent

yes

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

yes

In-memory capabilities

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

yes

via In-Memory Engine

User concepts

Access control

RBAC using LDAP or Druid internals for users and groups for read/write by datasource and system

yes

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

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