DBMS > Apache IoTDB vs. GBase vs. IBM Db2 warehouse

System Properties Comparison Apache IoTDB vs. GBase vs. IBM Db2 warehouse

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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

An analytical database for business intelligence with large customers in China.

Cloud-based data warehousing service

Primary database model

Time Series DBMS

Relational DBMS

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Trend Chart

Score	1.19
Rank	#176	Overall
	#15	Time Series DBMS

Score	1.04
Rank	#190	Overall
	#88	Relational DBMS

Score	1.34
Rank	#166	Overall
	#76	Relational DBMS

Website

iotdb.apache.org

www.gbase.cn

www.ibm.com/products/db2/warehouse

Technical documentation

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

Developer

Apache Software Foundation

IBM

Initial release

2018

2014

Current release

1.1.0, April 2023

GBase 8a

License

Commercial or Open Source

Open Source

Apache Version 2.0

commercial

Cloud-based only

Only available as a cloud service

yes

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)

hosted

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.

Import/export of XML data possible

Secondary indexes

yes

SQL

Support of SQL

SQL-like query language

yes

APIs and other access methods

JDBC
Native API

.NET Client API
JDBC
ODBC
OLE DB

Supported programming languages

C
C#
C++
Go
Java
Python
Scala

Java
JavaScript (Node.js)
Perl
PHP
Python
R
Ruby

Server-side scripts

Stored procedures

yes

PL/SQL, SQL PL

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

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

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

yes

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

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