DBMS > Atos Standard Common Repository vs. IRONdb vs. Splice Machine vs. ToroDB

System Properties Comparison Atos Standard Common Repository vs. IRONdb vs. Splice Machine vs. ToroDB

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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.

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

Description

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

Open-Source SQL RDBMS for Operational and Analytical use cases with native Machine Learning, powered by Hadoop and Spark

A MongoDB-compatible JSON document store, built on top of PostgreSQL

Primary database model

Document store
Key-value store

Time Series DBMS

Relational DBMS

Document store

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Score	0.54
Rank	#250	Overall
	#114	Relational DBMS

Website

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

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

splicemachine.com

github.com/torodb/server

Technical documentation

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

splicemachine.com/how-it-works

Developer

Atos Convergence Creators

Circonus LLC.

Splice Machine

8Kdata

Initial release

2016

2017

2014

2016

Current release

1703

V0.10.20, January 2018

3.1, March 2021

License

Commercial or Open Source

commercial

Open Source

AGPL 3.0, commercial license available

Open Source

AGPL-V3

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++

Java

Server operating systems

Linux

Linux
OS X
Solaris
Windows

All OS with a Java 7 VM

Data scheme

Schema and schema-less with LDAP views

schema-free

yes

schema-free

Typing

predefined data types such as float or date

optional

yes

text, numeric, histograms

yes

string, integer, double, boolean, date, object_id

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 (Circonus Analytics Query Language: CAQL)

yes

APIs and other access methods

LDAP

HTTP API

JDBC
Native Spark Datasource
ODBC

Supported programming languages

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

C#
C++
Java
JavaScript (Node.js)
Python
R
Scala

Server-side scripts

Stored procedures

yes, in Lua

yes

Java

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

cell division

Automatic, metric affinity per node

Shared Nothhing Auto-Sharding, Columnar Partitioning

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes

configurable replication factor, datacenter aware

Multi-source replication
Source-replica replication

Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

Yes, via Full Spark Integration

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency or Eventual Consistency depending on configuration

Immediate consistency per node, eventual consistency across nodes

Immediate Consistency

Eventual Consistency
Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

Atomic execution of specific operations

ACID

Concurrency

Support for concurrent manipulation of data

yes

yes, multi-version concurrency control (MVCC)

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

LDAP bind authentication

Access rights for users, groups and roles according to SQL-standard

Access rights for users and roles

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