DBMS > Atos Standard Common Repository vs. BigObject vs. Ehcache vs. ITTIA

System Properties Comparison Atos Standard Common Repository vs. BigObject vs. Ehcache vs. ITTIA

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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.

Description

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

Analytic DBMS for real-time computations and queries

A widely adopted Java cache with tiered storage options

Edge Time Series DBMS with Real-Time Stream Processing

Primary database model

Document store
Key-value store

Relational DBMS

a hierachical model (tree) can be imposed

Key-value store

Time Series DBMS

Secondary database models

Relational DBMS

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

Score	0.19
Rank	#329	Overall
	#146	Relational DBMS

Score	4.64
Rank	#68	Overall
	#8	Key-value stores

Score	0.44
Rank	#267	Overall
	#23	Time Series DBMS

Website

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

bigobject.io

www.ehcache.org

www.ittia.com

Technical documentation

docs.bigobject.io

www.ehcache.org/documentation

Developer

Atos Convergence Creators

BigObject, Inc.

Terracotta Inc, owned by Software AG

ITTIA L.L.C.

Initial release

2016

2015

2009

2007

Current release

1703

3.10.0, March 2022

8.7

License

Commercial or Open Source

commercial

free community edition available

Open Source

Apache Version 2; commercial licenses 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

Java

C and C++

Server operating systems

Linux

distributed as a docker-image
OS X

distributed as a docker-image (boot2docker)
Windows

distributed as a docker-image (boot2docker)

All OS with a Java VM

Linux
Windows

Data scheme

Schema and schema-less with LDAP views

yes

schema-free

Fixed schema

Typing

predefined data types such as float or date

optional

yes

Float/Blob/Integer/String/Unicode/Date/Time/Timestamp/Interval

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 DML and DDL statements

yes

APIs and other access methods

LDAP

fluentd
ODBC
RESTful HTTP API

JCache

JDBC
ODBC
RESTful HTTP API
WebSocket

Supported programming languages

All languages with LDAP bindings

Java

C
C++
JavaScript (Node.js)
Python

Server-side scripts

Stored procedures

Lua

yes

Triggers

yes

Cache Event Listeners

Partitioning methods

Methods for storing different data on different nodes

Sharding

cell division

none

Sharding

by using Terracotta Server

Replication methods

Methods for redundantly storing data on multiple nodes

yes

none

yes

by using Terracotta Server

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency or Eventual Consistency depending on configuration

none

Tunable Consistency (Strong, Eventual, Weak)

Foreign keys

Referential integrity

yes

automatically between fact table and dimension tables

yes

Transaction concepts

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

Atomic execution of specific operations

yes

supports JTA and can work as an XA resource

yes

Concurrency

Support for concurrent manipulation of data

yes

Read/write lock on objects (tables, trees)

yes

yes, multi-version concurrency control (MVCC)

Durability

Support for making data persistent

yes

using a tiered cache-storage approach

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

Database file passwords

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