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

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

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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

An open-source, elastic, and workload-aware cloud data warehouse designed to meet businesses' massive-scale analytics needs at low cost and with low complexity

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

Primary database model

Document store
Key-value store

Relational DBMS

Document store

Time Series DBMS

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

Score	0.30
Rank	#287	Overall
	#130	Relational DBMS

Score	7.60
Rank	#52	Overall
	#9	Document stores

Score	0.06
Rank	#356	Overall
	#35	Time Series DBMS

Website

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

github.com/datafuselabs/databend
www.databend.com

realm.io

github.com/sitewhere/sitewhere

Technical documentation

docs.databend.com

realm.io/docs

sitewhere1.sitewhere.io/index.html

Developer

Atos Convergence Creators

Databend Labs

Realm, acquired by MongoDB in May 2019

SiteWhere

Initial release

2016

2021

2014

2010

Current release

1703

1.0.59, April 2023

License

Commercial or Open Source

commercial

Open Source

Apache Version 2.0

Open Source

Common Public Attribution License Version 1.0

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

Rust

Java

Server operating systems

Linux

hosted
Linux
macOS

Android
Backend: server-less
iOS
Windows

Linux
OS X
Windows

Data scheme

Schema and schema-less with LDAP views

yes

predefined scheme

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

yes

APIs and other access methods

LDAP

CLI Client
JDBC
RESTful HTTP API

HTTP REST

Supported programming languages

All languages with LDAP bindings

Go
Java
JavaScript (Node.js)
Python
Rust

.Net
Java

with Android only
Objective-C
React Native
Swift

Server-side scripts

Stored procedures

runs within the applications so server-side scripts are unnecessary

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

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency or Eventual Consistency depending on configuration

Immediate Consistency

Foreign keys

Referential integrity

Transaction concepts

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

Atomic execution of specific operations

yes

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

Users with fine-grained authorization concept, user roles

yes

Users with fine-grained authorization concept

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More resources

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