DBMS > Cubrid vs. Dragonfly vs. Ignite vs. XTDB

System Properties Comparison Cubrid vs. Dragonfly vs. Ignite vs. XTDB

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Editorial information provided by DB-Engines

Name

Description

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

A drop-in Redis replacement that scales vertically to support millions of operations per second and terabyte sized workloads, all on a single instance

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.

A general purpose database with bitemporal SQL and Datalog and graph queries

Primary database model

Relational DBMS

Key-value store

Key-value store
Relational DBMS

Document store

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

Score	1.04
Rank	#187	Overall
	#87	Relational DBMS

Score	0.49
Rank	#261	Overall
	#38	Key-value stores

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

Score	0.18
Rank	#332	Overall
	#46	Document stores

Website

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

github.com/dragonflydb/dragonfly
www.dragonflydb.io

ignite.apache.org

github.com/xtdb/xtdb
www.xtdb.com

Technical documentation

cubrid.org/manuals

www.dragonflydb.io/docs

apacheignite.readme.io/docs

www.xtdb.com/docs

Developer

CUBRID Corporation, CUBRID Foundation

DragonflyDB team and community contributors

Apache Software Foundation

Juxt Ltd.

Initial release

2008

2023

2015

2019

Current release

11.0, January 2021

1.0, March 2023

Apache Ignite 2.6

1.19, September 2021

License

Commercial or Open Source

Open Source

Apache Version 2.0

Open Source

BSL 1.1

Open Source

Apache 2.0

Open Source

MIT License

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

C, C++, Java

C++

C++, Java, .Net

Clojure

Server operating systems

Linux
Windows

Linux

Linux
OS X
Solaris
Windows

All OS with a Java 8 (and higher) VM
Linux

Data scheme

yes

scheme-free

yes

schema-free

Typing

predefined data types such as float or date

yes

strings, hashes, lists, sets, sorted sets, bit arrays

yes

yes, extensible-data-notation format

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

yes

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

limited SQL, making use of Apache Calcite

APIs and other access methods

ADO.NET
JDBC
ODBC
OLE DB

Proprietary protocol

RESP - REdis Serialization Protocol

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

HTTP REST
JDBC

Supported programming languages

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

C
C#
C++
Clojure
D
Dart
Elixir
Erlang
Go
Haskell
Java
JavaScript (Node.js)
Lisp
Lua
Objective-C
Perl
PHP
Python
R
Ruby
Rust
Scala
Swift
Tcl

C#
C++
Java
PHP
Python
Ruby
Scala

Clojure
Java

Server-side scripts

Stored procedures

Java Stored Procedures

Lua

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

Triggers

yes

publish/subscribe channels provide some trigger functionality

yes (cache interceptors and events)

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

yes (replicated cache)

yes, each node contains all data

MapReduce

Offers an API for user-defined Map/Reduce methods

yes (compute grid and hadoop accelerator)

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

Atomic execution of command blocks and scripts

ACID

Concurrency

Support for concurrent manipulation of data

yes

yes, strict serializability by the server

yes

Durability

Support for making data persistent

yes

yes, flexibel persistency by using storage technologies like Apache Kafka, RocksDB or LMDB

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

yes

User concepts

Access control

fine grained access rights according to SQL-standard

Password-based authentication

Security Hooks for custom implementations

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