DBMS > Apache IoTDB vs. Greenplum vs. H2 vs. H2GIS vs. HBase

System Properties Comparison Apache IoTDB vs. Greenplum vs. H2 vs. H2GIS vs. HBase

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

Analytic Database platform built on PostgreSQL. Full name is Pivotal Greenplum Database

A logical database in Greenplum is an array of individual PostgreSQL databases working together to present a single database image.

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

Spatial extension of H2

Wide-column store based on Apache Hadoop and on concepts of BigTable

Primary database model

Secondary database models

Document store
Spatial DBMS

Spatial DBMS

Relational DBMS

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

Score	1.18
Rank	#173	Overall
	#15	Time Series DBMS

Score	8.37
Rank	#48	Overall
	#30	Relational DBMS

Score	8.13
Rank	#49	Overall
	#31	Relational DBMS

Score	0.00
Rank	#383	Overall
	#7	Spatial DBMS

Score	30.50
Rank	#26	Overall
	#2	Wide column stores

Website

Technical documentation

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

docs.greenplum.org

www.h2database.com/html/main.html

www.h2gis.org/docs/home

hbase.apache.org/book.html

Developer

Apache Software Foundation

Pivotal Software Inc.

Thomas Mueller

CNRS

Apache Software Foundation

Apache top-level project, originally developed by Powerset

Initial release

2018

2005

2013

2008

Current release

1.1.0, April 2023

7.0.0, September 2023

2.2.220, July 2023

2.3.4, January 2021

License

Commercial or Open Source

Open Source

Apache Version 2.0

Open Source

Apache 2.0

Open Source

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

Open Source

LGPL 3.0

Open Source

Apache version 2

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

Server operating systems

All OS with a Java VM (>= 1.8)

Linux

All OS with a Java VM

Linux
Unix
Windows

using Cygwin

Data scheme

yes

schema-free, schema definition possible

Typing

predefined data types such as float or date

yes

options to bring your own types, AVRO

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

since Version 4.2

Secondary indexes

yes

SQL

Support of SQL

SQL-like query language

yes

APIs and other access methods

JDBC
Native API

JDBC
ODBC

Java API
RESTful HTTP API
Thrift

Supported programming languages

C
C#
C++
Go
Java
Python
Scala

C
Java
Perl
Python
R

Java

C
C#
C++
Groovy
Java
PHP
Python
Scala

Server-side scripts

Stored procedures

yes

Java Stored Procedures and User-Defined Functions

yes

based on H2

yes

Coprocessors in Java

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

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

Sharding

none

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

Source-replica replication

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

yes

based on H2

Multi-source replication
Source-replica replication

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

Immediate Consistency

Immediate Consistency or Eventual Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

Single row ACID (across millions of columns)

Concurrency

Support for concurrent manipulation of data

yes

yes, multi-version concurrency control (MVCC)

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 H2

Access Control Lists (ACL) for RBAC, integration with Apache Ranger for RBAC & ABAC

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