DBMS > Atos Standard Common Repository vs. BigObject vs. HyperSQL vs. SiteWhere

System Properties Comparison Atos Standard Common Repository vs. BigObject vs. HyperSQL 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

Analytic DBMS for real-time computations and queries

Multithreaded, transactional RDBMS written in Java

also known as HSQLDB

M2M integration platform for persisting/querying time series data

Primary database model

Document store
Key-value store

Relational DBMS

a hierachical model (tree) can be imposed

Relational DBMS

Time Series DBMS

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

Score	0.13
Rank	#333	Overall
	#147	Relational DBMS

Score	3.49
Rank	#87	Overall
	#47	Relational DBMS

Score	0.06
Rank	#356	Overall
	#35	Time Series DBMS

Website

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

bigobject.io

hsqldb.org

github.com/sitewhere/sitewhere

Technical documentation

docs.bigobject.io

hsqldb.org/web/hsqlDocsFrame.html

sitewhere1.sitewhere.io/index.html

Developer

Atos Convergence Creators

BigObject, Inc.

SiteWhere

Initial release

2016

2015

2001

2010

Current release

1703

2.7.2, June 2023

License

Commercial or Open Source

commercial

free community edition available

Open Source

based on BSD license

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

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

Embedded (into Java applications) and Client-Server operating modes

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

SQL-like DML and DDL statements

yes

APIs and other access methods

LDAP

fluentd
ODBC
RESTful HTTP API

HTTP API

JDBC via HTTP
JDBC
ODBC

HTTP REST

Supported programming languages

All languages with LDAP bindings

All languages supporting JDBC/ODBC
Java

Server-side scripts

Stored procedures

Lua

Java, SQL

Triggers

yes

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

none

Immediate Consistency

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

ACID

Concurrency

Support for concurrent manipulation of data

yes

Read/write lock on objects (tables, trees)

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

fine grained access rights according to SQL-standard

Users with fine-grained authorization concept

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