DBMS > Apache IoTDB vs. BaseX vs. IBM Cloudant vs. Infobright vs. Microsoft Azure SQL Database

System Properties Comparison Apache IoTDB vs. BaseX vs. IBM Cloudant vs. Infobright vs. Microsoft Azure SQL Database

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

Light-weight Native XML DBMS with support for XQuery 3.0 and interactive GUI.

Database as a Service offering based on Apache CouchDB

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

Database as a Service offering with high compatibility to Microsoft SQL Server

Primary database model

Secondary database models

Document store
Graph DBMS
Spatial DBMS

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

Score	1.18
Rank	#173	Overall
	#15	Time Series DBMS

Score	1.73
Rank	#142	Overall
	#4	Native XML DBMS

Score	2.68
Rank	#106	Overall
	#20	Document stores

Score	0.96
Rank	#194	Overall
	#91	Relational DBMS

Score	77.99
Rank	#16	Overall
	#11	Relational DBMS

Website

iotdb.apache.org

basex.org

www.ibm.com/products/cloudant

ignitetech.com/softwarelibrary/infobrightdb

azure.microsoft.com/en-us/products/azure-sql/database

Technical documentation

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

docs.basex.org

cloud.ibm.com/docs/Cloudant

docs.microsoft.com/en-us/azure/azure-sql

Developer

Apache Software Foundation

BaseX GmbH

IBM, Apache Software Foundation

IBM acquired Cloudant in February 2014

Ignite Technologies Inc.; formerly InfoBright Inc.

Microsoft

Initial release

2018

2007

2010

2005

2010

Current release

1.1.0, April 2023

10.7, August 2023

V12

License

Commercial or Open Source

Open Source

Apache Version 2.0

Open Source

BSD license

commercial

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

commercial

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

Java

Erlang

C++

Server operating systems

All OS with a Java VM (>= 1.8)

Linux
OS X
Windows

hosted

Linux
Windows

hosted

Data scheme

yes

schema-free

yes

Typing

predefined data types such as float or date

yes

XQuery supports types

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

Knowledge Grid Technology used instead

yes

SQL

Support of SQL

SQL-like query language

yes

APIs and other access methods

JDBC
Native API

Java API
RESTful HTTP API
RESTXQ
WebDAV
XML:DB
XQJ

RESTful HTTP/JSON API

ADO.NET
JDBC
ODBC

Supported programming languages

C
C#
C++
Go
Java
Python
Scala

Actionscript
C
C#
Haskell
Java
JavaScript

Node.js
Lisp
Perl
PHP
Python
Qt
Rebol
Ruby
Scala
Visual Basic

C#
Java
JavaScript
Objective-C
PHP
Ruby

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

.Net
C#
Java
JavaScript (Node.js)
PHP
Python
Ruby

Server-side scripts

Stored procedures

yes

View functions (Map-Reduce) in JavaScript

Transact SQL

Triggers

yes

via events

yes

Partitioning methods

Methods for storing different data on different nodes

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

none

Sharding

none

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

none

Multi-source replication
Source-replica replication

Source-replica replication

yes, with always 3 replicas available

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

Eventual Consistency
Strong Consistency with Raft

Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

Support to ensure data integrity after non-atomic manipulations of data

multiple readers, single writer

atomic operations within a document possible

ACID

Concurrency

Support for concurrent manipulation of data

yes

Optimistic locking

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

Users with fine-grained authorization concept on 4 levels

Access rights for users can be defined per database

fine grained access rights according to SQL-standard

exploiting MySQL or PostgreSQL frontend capabilities

fine grained access rights according to SQL-standard

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