DBMS > Apache IoTDB vs. Cubrid vs. Firebird vs. Ignite vs. Microsoft Azure SQL Database

System Properties Comparison Apache IoTDB vs. Cubrid vs. Firebird vs. Ignite vs. Microsoft Azure SQL Database

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

Firebird is an open source RDBMS forked from Borland's InterBase

Apache Ignite is a memory-centric distributed database, caching, and processing platform for transactional, analytical, and streaming workloads, delivering in-memory speeds at petabyte scale.

Database as a Service offering with high compatibility to Microsoft SQL Server

Primary database model

Time Series DBMS

Relational DBMS

Key-value store
Relational DBMS

Relational DBMS

Secondary database models

Document store
Graph DBMS
Spatial DBMS

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

Score	1.31
Rank	#164	Overall
	#14	Time Series DBMS

Score	1.04
Rank	#187	Overall
	#87	Relational DBMS

Score	20.50
Rank	#30	Overall
	#18	Relational DBMS

Score	3.11
Rank	#96	Overall
	#15	Key-value stores
	#49	Relational DBMS

Score	76.78
Rank	#16	Overall
	#11	Relational DBMS

Website

iotdb.apache.org

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

www.firebirdsql.org

ignite.apache.org

azure.microsoft.com/en-us/products/azure-sql/database

Technical documentation

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

cubrid.org/manuals

www.firebirdsql.org/en/reference-manuals

apacheignite.readme.io/docs

docs.microsoft.com/en-us/azure/azure-sql

Developer

Apache Software Foundation

CUBRID Corporation, CUBRID Foundation

Firebird Foundation

Apache Software Foundation

Microsoft

Initial release

2018

2008

2000

As fork of Borland's InterBase

2015

2010

Current release

1.1.0, April 2023

11.0, January 2021

5.0.0, January 2024

Apache Ignite 2.6

V12

License

Commercial or Open Source

Open Source

Apache Version 2.0

Open Source

Apache Version 2.0

Open Source

Initial Developer's Public License

Open Source

Apache 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

C, C++, Java

C and C++

C++, Java, .Net

C++

Server operating systems

All OS with a Java VM (>= 1.8)

Linux
Windows

AIX
FreeBSD
HP-UX
Linux
OS X
server-less

Firebird Embedded Server
Solaris
Unix
Windows

Linux
OS X
Solaris
Windows

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.

yes

Secondary indexes

yes

SQL

Support of SQL

SQL-like query language

yes

ANSI-99 for query and DML statements, subset of DDL

yes

APIs and other access methods

JDBC
Native API

ADO.NET
JDBC
ODBC
OLE DB

ADO.NET
C/C++ API
JDBC

Jaybird
ODBC
OLE DB

HDFS API
Hibernate
JCache
JDBC
ODBC
Proprietary protocol
RESTful HTTP API
Spring Data

ADO.NET
JDBC
ODBC

Supported programming languages

C
C#
C++
Go
Java
Python
Scala

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

C
C#
C++
Delphi
Java
JavaScript

Node.js
Lua
Perl
PHP
Python
Ruby

C#
C++
Java
PHP
Python
Ruby
Scala

.Net
C#
Java
JavaScript (Node.js)
PHP
Python
Ruby

Server-side scripts

Stored procedures

yes

Java Stored Procedures

PSQL

yes (compute grid and cache interceptors can be used instead)

Transact SQL

Triggers

yes

yes (cache interceptors and events)

yes

Partitioning methods

Methods for storing different data on different nodes

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

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

yes (replicated cache)

yes, with always 3 replicas available

MapReduce

Offers an API for user-defined Map/Reduce methods

Integration with Hadoop and Spark

yes (compute grid and hadoop accelerator)

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

Features a multi-generational MVCC architecture, readers do not block writers

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

Users with fine-grained authorization concept

Security Hooks for custom implementations

fine grained access rights according to SQL-standard

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