DBMS > Apache IoTDB vs. Microsoft Azure SQL Database vs. OrigoDB vs. SiriDB

System Properties Comparison Apache IoTDB vs. Microsoft Azure SQL Database vs. OrigoDB vs. SiriDB

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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

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

A fully ACID in-memory object graph database

Open Source Time Series DBMS

Primary database model

Time Series DBMS

Relational DBMS

Document store
Object oriented DBMS

Time Series DBMS

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	77.99
Rank	#16	Overall
	#11	Relational DBMS

Score	0.00
Rank	#383	Overall
	#53	Document stores
	#20	Object oriented DBMS

Score	0.00
Rank	#383	Overall
	#41	Time Series DBMS

Website

iotdb.apache.org

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

origodb.com

siridb.com

Technical documentation

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

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

origodb.com/docs

docs.siridb.com

Developer

Apache Software Foundation

Microsoft

Robert Friberg et al

Cesbit

Initial release

2018

2010

2009

under the name LiveDB

2017

Current release

1.1.0, April 2023

V12

License

Commercial or Open Source

Open Source

Apache Version 2.0

commercial

Open Source

MIT License

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

C++

Server operating systems

All OS with a Java VM (>= 1.8)

hosted

Linux
Windows

Linux

Data scheme

yes

Typing

predefined data types such as float or date

yes

User defined using .NET types and collections

yes

Numeric data

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

can be achieved using .NET

Secondary indexes

yes

SQL

Support of SQL

SQL-like query language

yes

APIs and other access methods

JDBC
Native API

ADO.NET
JDBC
ODBC

.NET Client API
HTTP API
LINQ

HTTP API

Supported programming languages

C
C#
C++
Go
Java
Python
Scala

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

.Net

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

Server-side scripts

Stored procedures

yes

Transact SQL

yes

Triggers

yes

Domain Events

Partitioning methods

Methods for storing different data on different nodes

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

horizontal partitioning

client side managed; servers are not synchronized

Sharding

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

yes, with always 3 replicas available

Source-replica replication

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

Integration with Hadoop and Spark

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency
Strong Consistency with Raft

Immediate Consistency

Foreign keys

Referential integrity

yes

depending on model

Transaction concepts

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

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

Write ahead log

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

Role based authorization

simple rights management via user accounts

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