DBMS > Apache IoTDB vs. EventStoreDB vs. Microsoft SQL Server vs. PostGIS

System Properties Comparison Apache IoTDB vs. EventStoreDB vs. Microsoft SQL Server vs. PostGIS

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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

Industrial-strength, open-source database solution built from the ground up for event sourcing.

Microsofts flagship relational DBMS

Spatial extension of PostgreSQL

Primary database model

Secondary database models

Document store
Graph DBMS
Spatial DBMS

Relational DBMS

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

Score	1.31
Rank	#164	Overall
	#14	Time Series DBMS

Score	1.19
Rank	#173	Overall
	#1	Event Stores

Score	821.56
Rank	#3	Overall
	#3	Relational DBMS

Score	21.72
Rank	#29	Overall
	#1	Spatial DBMS

Website

iotdb.apache.org

www.eventstore.com

www.microsoft.com/en-us/sql-server

postgis.net

Technical documentation

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

developers.eventstore.com

learn.microsoft.com/en-US/sql/sql-server

postgis.net/documentation

Developer

Apache Software Foundation

Event Store Limited

Microsoft

Initial release

2018

2012

1989

2005

Current release

1.1.0, April 2023

21.2, February 2021

SQL Server 2022, November 2022

3.4.2, February 2024

License

Commercial or Open Source

Open Source

Apache Version 2.0

Open Source

commercial

restricted free version is available

Open Source

GPL v2.0

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

Java

C++

Server operating systems

All OS with a Java VM (>= 1.8)

Linux
Windows

Data scheme

yes

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-like query language

yes

APIs and other access methods

JDBC
Native API

ADO.NET
JDBC
ODBC
OLE DB
Tabular Data Stream (TDS)

Supported programming languages

C
C#
C++
Go
Java
Python
Scala

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

Server-side scripts

Stored procedures

yes

Transact SQL, .NET languages, R, Python and (with SQL Server 2019) Java

user defined functions

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

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

tables can be distributed across several files (horizontal partitioning); sharding through federation

yes

based on PostgreSQL

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, but depending on the SQL-Server Edition

yes

based on PostgreSQL

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

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

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

yes

based on PostgreSQL

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