DBMS > Apache IoTDB vs. GBase vs. IBM Cloudant vs. IRONdb vs. PostgreSQL

System Properties Comparison Apache IoTDB vs. GBase vs. IBM Cloudant vs. IRONdb vs. PostgreSQL

Editorial information provided by DB-Engines

Name

IRONdb seems to be discontinued. Therefore it is excluded from the DB-Engines Ranking.

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

Widely used RDBMS in China, including analytical, transactional, distributed transactional, and cloud-native data warehousing.

Database as a Service offering based on Apache CouchDB

A distributed Time Series DBMS with a focus on scalability, fault tolerance and operational simplicity

Widely used open source RDBMS

Developed as objectoriented DBMS (Postgres), gradually enhanced with 'standards' like SQL

Primary database model

with object oriented extensions, e.g.: user defined types/functions and inheritance. Handling of key/value pairs with hstore module.

Secondary database models

Document store
Graph DBMS

with Apache Age
Spatial DBMS
Vector DBMS

with pgvector extension

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

Score	1.18
Rank	#173	Overall
	#15	Time Series DBMS

Score	1.07
Rank	#185	Overall
	#86	Relational DBMS

Score	2.68
Rank	#106	Overall
	#20	Document stores

Score	645.54
Rank	#4	Overall
	#4	Relational DBMS

Website

iotdb.apache.org

www.gbase.cn

www.ibm.com/products/cloudant

www.circonus.com/solutions/time-series-database/

www.postgresql.org

Technical documentation

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

cloud.ibm.com/docs/Cloudant

docs.circonus.com/irondb/category/getting-started

www.postgresql.org/docs

Developer

Apache Software Foundation

General Data Technology Co., Ltd.

IBM, Apache Software Foundation

IBM acquired Cloudant in February 2014

Circonus LLC.

PostgreSQL Global Development Group

www.postgresql.org/developer

Initial release

2018

2004

2010

2017

1989

1989: Postgres, 1996: PostgreSQL

Current release

1.1.0, April 2023

GBase 8a, GBase 8s, GBase 8c

V0.10.20, January 2018

16.3, May 2024

License

Commercial or Open Source

Open Source

Apache Version 2.0

commercial

Open Source

BSD

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

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Implementation language

Java

C, Java, Python

Erlang

C and C++

Server operating systems

All OS with a Java VM (>= 1.8)

Linux

hosted

Linux

FreeBSD
HP-UX
Linux
NetBSD
OpenBSD
OS X
Solaris
Unix
Windows

Data scheme

yes

schema-free

yes

Typing

predefined data types such as float or date

yes

text, numeric, histograms

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

Standard with numerous extensions

SQL-like query language (Circonus Analytics Query Language: CAQL)

yes

standard with numerous extensions

APIs and other access methods

JDBC
Native API

ADO.NET
C API
JDBC
ODBC

RESTful HTTP/JSON API

HTTP API

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

Supported programming languages

C
C#
C++
Go
Java
Python
Scala

C#
Java
JavaScript
Objective-C
PHP
Ruby

.Net
C
C++
Clojure
Erlang
Go
Haskell
Java
JavaScript
JavaScript (Node.js)
Lisp
Lua
Perl
PHP
Python
R
Ruby
Rust
Scala

.Net
C
C++
Delphi
Java

JDBC
JavaScript (Node.js)
Perl
PHP
Python
Tcl

Server-side scripts

Stored procedures

yes

user defined functions

View functions (Map-Reduce) in JavaScript

yes, in Lua

user defined functions

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

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

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

horizontal partitioning (by range, list and hash) and vertical partitioning

Sharding

Automatic, metric affinity per node

partitioning by range, list and (since PostgreSQL 11) by hash

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

Multi-source replication
Source-replica replication

configurable replication factor, datacenter aware

Source-replica replication

other methods possible by using 3rd party extensions

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

Eventual Consistency

Immediate consistency per node, eventual consistency across nodes

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

atomic operations within a document possible

ACID

Concurrency

Support for concurrent manipulation of data

yes

Optimistic locking

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

Access rights for users can be defined per database

fine grained access rights according to SQL-standard

More information provided by the system vendor

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