DBMS > Atos Standard Common Repository vs. Google BigQuery vs. JaguarDB vs. Newts vs. SiteWhere

System Properties Comparison Atos Standard Common Repository vs. Google BigQuery vs. JaguarDB vs. Newts vs. SiteWhere

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

Large scale data warehouse service with append-only tables

Performant, highly scalable DBMS for AI and IoT applications

Time Series DBMS based on Cassandra

M2M integration platform for persisting/querying time series data

Primary database model

Document store
Key-value store

Relational DBMS

Key-value store
Vector DBMS

Time Series DBMS

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

Score	58.10
Rank	#19	Overall
	#13	Relational DBMS

Score	0.06
Rank	#381	Overall
	#59	Key-value stores
	#13	Vector DBMS

Score	0.07
Rank	#375	Overall
	#41	Time Series DBMS

Score	0.06
Rank	#383	Overall
	#43	Time Series DBMS

Website

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

cloud.google.com/bigquery

www.jaguardb.com

opennms.github.io/newts

github.com/sitewhere/sitewhere

Technical documentation

cloud.google.com/bigquery/docs

www.jaguardb.com/support.html

github.com/OpenNMS/newts/wiki

sitewhere1.sitewhere.io/index.html

Developer

Atos Convergence Creators

Google

DataJaguar, Inc.

OpenNMS Group

SiteWhere

Initial release

2016

2010

2015

2014

2010

Current release

1703

3.3 July 2023

License

Commercial or Open Source

commercial

Open Source

GPL V3.0

Open Source

Apache 2.0

Open Source

Common Public Attribution License Version 1.0

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

Java

C++

the server part. Clients available in other languages

Java

Server operating systems

Linux

hosted

Linux

Linux
OS X
Windows

Data scheme

Schema and schema-less with LDAP views

yes

schema-free

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

A subset of ANSI SQL is implemented

but no views, foreign keys, triggers

APIs and other access methods

LDAP

RESTful HTTP/JSON API

JDBC
ODBC

HTTP REST
Java API

HTTP REST

Supported programming languages

All languages with LDAP bindings

.Net
Java
JavaScript
Objective-C
PHP
Python
Ruby

C
C++
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
Scala

Java

Server-side scripts

Stored procedures

user defined functions

in JavaScript

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

cell division

none

Sharding

based on Cassandra

Sharding

based on HBase

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Multi-source replication

selectable replication factor

based on Cassandra

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

Eventual Consistency

based on Cassandra
Immediate Consistency

based on Cassandra

Immediate Consistency

Foreign keys

Referential integrity

Transaction concepts

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

Atomic execution of specific operations

Since BigQuery is designed for querying data

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

User concepts

Access control

LDAP bind authentication

Access privileges (owner, writer, reader) on dataset, table or view level

Google Cloud Identity & Access Management (IAM)

rights management via user accounts

Users with fine-grained authorization concept

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