DBMS > Cubrid vs. IRONdb vs. JaguarDB vs. Yaacomo

System Properties Comparison Cubrid vs. IRONdb vs. JaguarDB vs. Yaacomo

Please select another system to include it in the comparison.

Editorial information provided by DB-Engines

Name

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

Yaacomo seems to be discontinued and is removed from the DB-Engines ranking

Description

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

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

Performant, highly scalable DBMS for AI and IoT applications

OpenCL based in-memory RDBMS, designed for efficiently utilizing the hardware via parallel computing

Primary database model

Relational DBMS

Time Series DBMS

Key-value store
Vector DBMS

Relational DBMS

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

Score	1.04
Rank	#187	Overall
	#87	Relational DBMS

Score	0.06
Rank	#381	Overall
	#59	Key-value stores
	#14	Vector DBMS

Website

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

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

www.jaguardb.com

yaacomo.com

Technical documentation

cubrid.org/manuals

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

www.jaguardb.com/support.html

Developer

CUBRID Corporation, CUBRID Foundation

Circonus LLC.

DataJaguar, Inc.

Q2WEB GmbH

Initial release

2008

2017

2015

2009

Current release

11.0, January 2021

V0.10.20, January 2018

3.3 July 2023

License

Commercial or Open Source

Open Source

Apache Version 2.0

commercial

Open Source

GPL V3.0

commercial

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

C, C++, Java

C and C++

C++

the server part. Clients available in other languages

Server operating systems

Linux
Windows

Linux

Android
Linux
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.

Secondary indexes

yes

SQL

Support of SQL

yes

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

A subset of ANSI SQL is implemented

but no views, foreign keys, triggers

yes

APIs and other access methods

ADO.NET
JDBC
ODBC
OLE DB

HTTP API

JDBC
ODBC

Supported programming languages

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

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

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

Server-side scripts

Stored procedures

Java Stored Procedures

yes, in Lua

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

none

Automatic, metric affinity per node

Sharding

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

configurable replication factor, datacenter aware

Multi-source replication

Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Immediate consistency per node, eventual consistency across nodes

Eventual Consistency

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

fine grained access rights according to SQL-standard

rights management via user accounts

fine grained access rights according to SQL-standard

More information provided by the system vendor

We invite representatives of system vendors to contact us for updating and extending the system information,
and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

Related products and services

We invite representatives of vendors of related products to contact us for presenting information about their offerings here.

More resources

Recent citations in the news

Application observability firm Apica buys telemetry data startup Circonus and adds more funding
21 February 2024, SiliconANGLE News

Apica Acquires Telemetry Data Management Pioneer Circonus And Lands New Funding
22 February 2024, Datanami

Apica gets $6 million in funding and buys Circonus -
21 February 2024, Enterprise Times

provided by Google News

Share this page