DBMS > ArcadeDB vs. Atos Standard Common Repository vs. IRONdb vs. Quasardb

System Properties Comparison ArcadeDB vs. Atos Standard Common Repository vs. IRONdb vs. Quasardb

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Editorial information provided by DB-Engines

Name

This system has been discontinued and will be removed from the DB-Engines ranking.

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

Description

Fast and scalable multi-model DBMS, originally forked from OrientDB but most of the code has been rewritten

Highly scalable database system, designed for managing session and subscriber data in modern mobile communication networks

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

Distributed, high-performance timeseries database

Primary database model

Document store
Graph DBMS
Key-value store
Time Series DBMS

in next version

Document store
Key-value store

Time Series DBMS

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

Score	0.02
Rank	#366	Overall
	#50	Document stores
	#38	Graph DBMS
	#53	Key-value stores
	#36	Time Series DBMS

Score	0.14
Rank	#332	Overall
	#29	Time Series DBMS

Website

arcadedb.com

atos.net/en/convergence-creators/portfolio/standard-common-repository

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

quasar.ai

Technical documentation

docs.arcadedb.com

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

doc.quasar.ai/master

Developer

Arcade Data

Atos Convergence Creators

Circonus LLC.

quasardb

Initial release

2021

2016

2017

2009

Current release

September 2021

1703

V0.10.20, January 2018

3.14.1, January 2024

License

Commercial or Open Source

Open Source

Apache Version 2.0

commercial

Free community edition, Non-profit organizations and non-commercial usage are eligible for free licenses

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

Java

C and C++

C++

Server operating systems

All OS with a Java VM

Linux

BSD
Linux
OS X
Windows

Data scheme

schema-free

Schema and schema-less with LDAP views

schema-free

Typing

predefined data types such as float or date

yes

optional

yes

text, numeric, histograms

yes

integer and binary

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

with tags

SQL

Support of SQL

SQL-like query language, no joins

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

SQL-like query language

APIs and other access methods

JDBC
MongoDB API
OpenCypher
PostgreSQL wire protocol
Redis API
RESTful HTTP/JSON API
TinkerPop Gremlin

LDAP

HTTP API

Supported programming languages

Java

All languages with LDAP bindings

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

.Net
C
C#
C++
Go
Java
JavaScript (Node.js)
PHP
Python
R

Server-side scripts

Stored procedures

yes, in Lua

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

cell division

Automatic, metric affinity per node

Sharding

consistent hashing

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

yes

configurable replication factor, datacenter aware

Source-replica replication with selectable replication factor

MapReduce

Offers an API for user-defined Map/Reduce methods

with Hadoop integration

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Immediate Consistency or Eventual Consistency depending on configuration

Immediate consistency per node, eventual consistency across nodes

Immediate Consistency

Foreign keys

Referential integrity

yes

relationship in graphs

Transaction concepts

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

ACID

Atomic execution of specific operations

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

by using LevelDB

In-memory capabilities

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

yes

Transient mode

User concepts

Access control

LDAP bind authentication

Cryptographically strong user authentication and audit trail

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