DBMS > Apache IoTDB vs. Cubrid vs. GridDB vs. Microsoft SQL Server

System Properties Comparison Apache IoTDB vs. Cubrid vs. GridDB vs. Microsoft SQL Server

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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

CUBRID is an open-source SQL-based relational database management system with object extensions for OLTP

Scalable in-memory time series database optimized for IoT and Big Data

Microsofts flagship relational DBMS

Primary database model

Secondary database models

Key-value store
Relational DBMS

Document store
Graph DBMS
Spatial DBMS

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

Score	1.31
Rank	#159	Overall
	#14	Time Series DBMS

Score	0.97
Rank	#189	Overall
	#86	Relational DBMS

Score	1.91
Rank	#123	Overall
	#10	Time Series DBMS

Score	807.76
Rank	#3	Overall
	#3	Relational DBMS

Website

iotdb.apache.org

cubrid.com (korean)
cubrid.org (english)

griddb.net

www.microsoft.com/en-us/sql-server

Technical documentation

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

cubrid.org/manuals

docs.griddb.net

learn.microsoft.com/en-US/sql/sql-server

Developer

Apache Software Foundation

CUBRID Corporation, CUBRID Foundation

Toshiba Corporation

Microsoft

Initial release

2018

2008

2013

1989

Current release

1.1.0, April 2023

11.0, January 2021

5.1, August 2022

SQL Server 2022, November 2022

License

Commercial or Open Source

Open Source

Apache Version 2.0

Open Source

Apache Version 2.0

Open Source

AGPL version 3 and Apache License, version 2.0 , commercial license (standard and advanced editions) also available

commercial

restricted free version is available

Cloud-based only

Only available as a cloud service

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Implementation language

Java

C, C++, Java

C++

Server operating systems

All OS with a Java VM (>= 1.8)

Linux
Windows

Linux

Linux
Windows

Data scheme

yes

Typing

predefined data types such as float or date

yes

numerical, string, blob, geometry, boolean, timestamp

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

Secondary indexes

yes

SQL

Support of SQL

SQL-like query language

yes

SQL92, SQL-like TQL (Toshiba Query Language)

yes

APIs and other access methods

JDBC
Native API

ADO.NET
JDBC
ODBC
OLE DB

JDBC
ODBC
Proprietary protocol
RESTful HTTP/JSON API

ADO.NET
JDBC
ODBC
OLE DB
Tabular Data Stream (TDS)

Supported programming languages

C
C#
C++
Go
Java
Python
Scala

C
C#
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby

C
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby

C#
C++
Delphi
Go
Java
JavaScript (Node.js)
PHP
Python
R
Ruby
Visual Basic

Server-side scripts

Stored procedures

yes

Java Stored Procedures

Transact SQL, .NET languages, R, Python and (with SQL Server 2019) Java

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

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

none

Sharding

tables can be distributed across several files (horizontal partitioning); sharding through federation

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

yes, but depending on the SQL-Server Edition

MapReduce

Offers an API for user-defined Map/Reduce methods

Integration with Hadoop and Spark

Connector for using GridDB as an input source and output destination for Hadoop MapReduce jobs

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency
Strong Consistency with Raft

Immediate Consistency

Immediate consistency within container, eventual consistency across containers

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

ACID at container level

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

Access rights for users can be defined per database

fine grained access rights according to SQL-standard

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