DBMS > Apache IoTDB vs. EDB Postgres vs. H2GIS

System Properties Comparison Apache IoTDB vs. EDB Postgres vs. H2GIS

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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

The EDB Postgres Platform is an enterprise-class data management platform based on the open source database PostgreSQL with flexible deployment options and Oracle compatibility features, complemented by tool kits for management, integration, and migration.

Spatial extension of H2

Primary database model

Time Series DBMS

Relational DBMS

Spatial DBMS

Secondary database models

Document store
Spatial DBMS

Relational DBMS

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

Score	1.19
Rank	#176	Overall
	#15	Time Series DBMS

Score	2.18
Rank	#122	Overall
	#59	Relational DBMS

Score	0.05
Rank	#372	Overall
	#7	Spatial DBMS

Website

iotdb.apache.org

www.enterprisedb.com

www.h2gis.org

Technical documentation

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

www.enterprisedb.com/docs

www.h2gis.org/docs/home

Developer

Apache Software Foundation

EnterpriseDB

CNRS

Initial release

2018

2005

2013

Current release

1.1.0, April 2023

14, December 2021

License

Commercial or Open Source

Open Source

Apache Version 2.0

commercial

BSD for PostgreSQL-components

Open Source

LGPL 3.0

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

Java

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

specific XML-type available, but no XML query functionality.

Secondary indexes

yes

SQL

Support of SQL

SQL-like query language

yes

standard with numerous extensions

yes

APIs and other access methods

JDBC
Native API

ADO.NET
JDBC
native C library
ODBC
streaming API for large objects

Supported programming languages

C
C#
C++
Go
Java
Python
Scala

.Net
C
C++
Delphi
Java
Perl
PHP
Python
Tcl

Java

Server-side scripts

Stored procedures

yes

user defined functions

realized in proprietary language PL/pgSQL or with common languages like Perl, Python, Tcl etc.

yes

based on H2

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

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

horizontal partitioning

by hash, list or range

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

Multi-source replication

yes

based on H2

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

yes, multi-version concurrency control (MVCC)

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 H2

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