DBMS > Cubrid vs. Datomic vs. Hypertable vs. IRONdb

System Properties Comparison Cubrid vs. Datomic vs. Hypertable vs. IRONdb

Please select another system to include it in the comparison.

Editorial information provided by DB-Engines

Name

Hypertable has stopped its further development with March 2016 and is removed from the DB-Engines ranking.

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

Description

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

Datomic builds on immutable values, supports point-in-time queries and uses 3rd party systems for durability

An open source BigTable implementation based on distributed file systems such as Hadoop

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

Primary database model

Relational DBMS

Wide column store

Time Series DBMS

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

Score	1.20
Rank	#169	Overall
	#78	Relational DBMS

Score	1.59
Rank	#150	Overall
	#69	Relational DBMS

Website

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

www.datomic.com

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

Technical documentation

cubrid.org/manuals

docs.datomic.com

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

Developer

CUBRID Corporation, CUBRID Foundation

Cognitect

Hypertable Inc.

Circonus LLC.

Initial release

2008

2012

2009

2017

Current release

11.0, January 2021

1.0.6735, June 2023

0.9.8.11, March 2016

V0.10.20, January 2018

License

Commercial or Open Source

Open Source

Apache Version 2.0

commercial

limited edition free

Open Source

GNU version 3. Commercial license available

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

Java, Clojure

C++

C and C++

Server operating systems

Linux
Windows

All OS with a Java VM

Linux
OS X
Windows

an inofficial Windows port is available

Linux

Data scheme

yes

schema-free

Typing

predefined data types such as float or date

yes

text, numeric, histograms

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

restricted

only exact value or prefix value scans

SQL

Support of SQL

yes

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

APIs and other access methods

ADO.NET
JDBC
ODBC
OLE DB

RESTful HTTP API

C++ API
Thrift

HTTP API

Supported programming languages

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

Clojure
Java

C++
Java
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

Server-side scripts

Stored procedures

Java Stored Procedures

yes

Transaction Functions

yes, in Lua

Triggers

yes

By using transaction functions

Partitioning methods

Methods for storing different data on different nodes

none

But extensive use of caching in the application peers

Sharding

Automatic, metric affinity per node

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

none

But extensive use of caching in the application peers

selectable replication factor on file system level

configurable replication factor, datacenter aware

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Immediate consistency per node, eventual consistency across nodes

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

using external storage systems (e.g. Cassandra, DynamoDB, PostgreSQL, Couchbase and others)

yes

In-memory capabilities

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

yes

recommended only for testing and development

User concepts

Access control

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

Nubank buys firm behind Clojure programming language
28 July 2020, Finextra

Zoona Case Study
16 December 2017, AWS Blog

Architecting Software for Leverage
13 November 2021, InfoQ.com

TerminusDB Takes on Data Collaboration with a git-Like Approach
1 December 2020, The New Stack

Nubank acquires US company; PayPal studies cryptocurrencies
24 July 2020, iupana.com

provided by Google News

SQL and TimescaleDB. This article takes a closer look into… | by Alibaba Cloud
31 July 2019, DataDrivenInvestor

TimescaleDB goes distributed; implements ‘Chunking’ over ‘Sharding’ for scaling-out
22 August 2019, Packt Hub

Decorate your Windows XP with Hyperdesk
30 July 2008, CNET

The Collective: Customize Your Computer & Your Phone With Star Trek
18 March 2009, TrekMovie

Exclusive: Groupon Acquires Stealth Silicon Valley Startup Campfire Labs
28 December 2011, TechCrunch

provided by Google 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