DBMS > Apache IoTDB vs. Infobright vs. MySQL vs. Prometheus vs. SAP IQ

System Properties Comparison Apache IoTDB vs. Infobright vs. MySQL vs. Prometheus vs. SAP IQ

Editorial information provided by DB-Engines

Name

Description

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

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

Widely used open source RDBMS

Open-source Time Series DBMS and monitoring system

Columnar RDBMS optimized for Big Data analytics

Primary database model

Time Series DBMS

Relational DBMS

Key/Value like access via memcached API

Time Series DBMS

Relational DBMS

column-oriented

Secondary database models

Document store
Spatial DBMS

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

Score	1.31
Rank	#164	Overall
	#14	Time Series DBMS

Score	1.02
Rank	#192	Overall
	#90	Relational DBMS

Score	1061.34
Rank	#2	Overall
	#2	Relational DBMS

Score	7.69
Rank	#50	Overall
	#3	Time Series DBMS

Score	2.64
Rank	#108	Overall
	#52	Relational DBMS

Website

iotdb.apache.org

ignitetech.com/softwarelibrary/infobrightdb

www.mysql.com

prometheus.io

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

Technical documentation

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

dev.mysql.com/doc

prometheus.io/docs

help.sap.com/docs/SAP_IQ

Developer

Apache Software Foundation

Ignite Technologies Inc.; formerly InfoBright Inc.

Oracle

since 2010, originally MySQL AB, then Sun

SAP, formerly Sybase

Initial release

2018

2005

1995

2015

1994

Current release

1.1.0, April 2023

8.4.0, April 2024

16.1 SPS04, April 2019

License

Commercial or Open Source

Open Source

Apache Version 2.0

commercial

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

Open Source

GPL version 2. Commercial licenses with extended functionallity are available

Open Source

Apache 2.0

commercial

Cloud-based only

Only available as a cloud service

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Database as a Service

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Implementation language

Java

C and C++

Server operating systems

All OS with a Java VM (>= 1.8)

Linux
Windows

FreeBSD
Linux
OS X
Solaris
Windows

Linux
Windows

AIX
HP-UX
Linux
Solaris
Windows

Data scheme

yes

Typing

predefined data types such as float or date

yes

Numeric data only

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

Import of XML data possible

Secondary indexes

yes

Knowledge Grid Technology used instead

yes

SQL

Support of SQL

SQL-like query language

yes

with proprietary extensions

yes

APIs and other access methods

JDBC
Native API

ADO.NET
JDBC
ODBC

ADO.NET
JDBC
ODBC
Proprietary native API

RESTful HTTP/JSON API

ADO.NET
JDBC
ODBC
RESTful HTTP API

Supported programming languages

C
C#
C++
Go
Java
Python
Scala

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

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

.Net
C++
Go
Haskell
Java
JavaScript (Node.js)
Python
Ruby

C
C#
C++
Java
Perl
PHP
Python
Ruby

Server-side scripts

Stored procedures

yes

proprietary syntax

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

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

none

horizontal partitioning, sharding with MySQL Cluster or MySQL Fabric

Sharding

shared disk or shared nothing architectures with SAP IQ Multiplexer

Replication methods

Methods for redundantly storing data on multiple nodes

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

Source-replica replication

Multi-source replication
Source-replica replication

yes

by Federation

SAP/Sybase Replication Server

MapReduce

Offers an API for user-defined Map/Reduce methods

Integration with Hadoop and Spark

Hadoop integration

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency
Strong Consistency with Raft

Immediate Consistency

none

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

yes

fine grained access rights according to SQL-standard

exploiting MySQL or PostgreSQL frontend capabilities

Users with fine-grained authorization concept

no user groups or roles

fine grained access rights according to SQL-standard

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