DBMS > Atos Standard Common Repository vs. Realm vs. SiteWhere vs. TigerGraph

System Properties Comparison Atos Standard Common Repository vs. Realm vs. SiteWhere vs. TigerGraph

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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

A DBMS built for use on mobile devices that’s a fast, easy to use alternative to SQLite and Core Data

M2M integration platform for persisting/querying time series data

A complete, distributed, parallel graph computing platform supporting web-scale data analytics in real-time

Primary database model

Document store
Key-value store

Document store

Time Series DBMS

Graph DBMS

DB-Engines Ranking measures the popularity of database management systems
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Score	7.60
Rank	#52	Overall
	#9	Document stores

Score	0.06
Rank	#356	Overall
	#35	Time Series DBMS

Score	1.83
Rank	#139	Overall
	#13	Graph DBMS

Website

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

realm.io

github.com/sitewhere/sitewhere

www.tigergraph.com

Technical documentation

realm.io/docs

sitewhere1.sitewhere.io/index.html

docs.tigergraph.com

Developer

Atos Convergence Creators

Realm, acquired by MongoDB in May 2019

SiteWhere

Initial release

2016

2014

2010

2017

Current release

1703

License

Commercial or Open Source

commercial

Open Source

Common Public Attribution License Version 1.0

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

Java

C++

Server operating systems

Linux

Android
Backend: server-less
iOS
Windows

Linux
OS X
Windows

Linux

Data scheme

Schema and schema-less with LDAP views

yes

predefined scheme

yes

Typing

predefined data types such as float or date

optional

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.

yes

Secondary indexes

yes

SQL

Support of SQL

SQL-like query language (GSQL)

APIs and other access methods

LDAP

HTTP REST

GSQL (TigerGraph Query Language)
Kafka
RESTful HTTP/JSON API

Supported programming languages

All languages with LDAP bindings

.Net
Java

with Android only
Objective-C
React Native
Swift

C++
Java

Server-side scripts

Stored procedures

runs within the applications so server-side scripts are unnecessary

yes

Triggers

yes

Change Listeners

Partitioning methods

Methods for storing different data on different nodes

Sharding

cell division

none

Sharding

based on HBase

Replication methods

Methods for redundantly storing data on multiple nodes

yes

none

selectable replication factor

based on HBase

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency or Eventual Consistency depending on configuration

Immediate Consistency

Foreign keys

Referential integrity

yes

Relationships in graphs

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

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

In-Memory realm

User concepts

Access control

LDAP bind authentication

yes

Users with fine-grained authorization concept

Role-based access control

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