DBMS > Apache IoTDB vs. EDB Postgres vs. Graph Engine vs. H2

System Properties Comparison Apache IoTDB vs. EDB Postgres vs. Graph Engine vs. H2

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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.

A distributed in-memory data processing engine, underpinned by a strongly-typed RAM store and a general distributed computation engine

Full-featured RDBMS with a small footprint, either embedded into a Java application or used as a database server.

Primary database model

Time Series DBMS

Relational DBMS

Graph DBMS
Key-value store

Relational DBMS

Secondary database models

Document store
Spatial 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	1.90
Rank	#135	Overall
	#63	Relational DBMS

Score	0.61
Rank	#240	Overall
	#21	Graph DBMS
	#35	Key-value stores

Score	8.13
Rank	#49	Overall
	#31	Relational DBMS

Website

Technical documentation

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

www.enterprisedb.com/docs

www.graphengine.io/docs/manual

www.h2database.com/html/main.html

Developer

Apache Software Foundation

EnterpriseDB

Microsoft

Thomas Mueller

Initial release

2018

2005

2010

2005

Current release

1.1.0, April 2023

14, December 2021

2.2.220, July 2023

License

Commercial or Open Source

Open Source

Apache Version 2.0

commercial

BSD for PostgreSQL-components

Open Source

MIT License

Open Source

dual-licence (Mozilla public license, Eclipse public license)

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

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

Implementation language

Java

.NET and C

Java

Server operating systems

All OS with a Java VM (>= 1.8)

Linux
Windows

.NET

All OS with a Java VM

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

RESTful HTTP API

JDBC
ODBC

Supported programming languages

C
C#
C++
Go
Java
Python
Scala

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

C#
C++
F#
Visual Basic

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

Java Stored Procedures and User-Defined Functions

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

horizontal partitioning

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

With clustering: 2 database servers on different computers operate on identical copies of a database

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)

yes

yes, multi-version concurrency control (MVCC)

Durability

Support for making data persistent

yes

optional: either by committing a write-ahead log (WAL) to the local persistent storage or by dumping the memory to a persistent storage

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

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