DBMS > Atos Standard Common Repository vs. BigchainDB vs. dBASE vs. Google BigQuery vs. Newts

System Properties Comparison Atos Standard Common Repository vs. BigchainDB vs. dBASE vs. Google BigQuery vs. Newts

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

BigchainDB is scalable blockchain database offering decentralization, immutability and native assets

dBase was one of the first databases with a development environment on PC's. Its latest version dBase V is still sold as dBase classic, which needs a DOS Emulation. The up-to-date product is dBase plus.

Large scale data warehouse service with append-only tables

Time Series DBMS based on Cassandra

Primary database model

Document store
Key-value store

Document store

Relational DBMS

Time Series DBMS

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

Score	0.85
Rank	#208	Overall
	#35	Document stores

Score	9.70
Rank	#44	Overall
	#28	Relational DBMS

Score	58.10
Rank	#19	Overall
	#13	Relational DBMS

Score	0.07
Rank	#375	Overall
	#41	Time Series DBMS

Website

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

www.bigchaindb.com

www.dbase.com

cloud.google.com/bigquery

opennms.github.io/newts

Technical documentation

bigchaindb.readthedocs.io/en/latest

www.dbase.com/support/knowledgebase

cloud.google.com/bigquery/docs

github.com/OpenNMS/newts/wiki

Developer

Atos Convergence Creators

Asthon Tate

Google

OpenNMS Group

Initial release

2016

1979

2010

2014

Current release

1703

dBASE 2019, 2019

License

Commercial or Open Source

commercial

Open Source

AGPL v3

commercial

Open Source

Apache 2.0

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

Python

Java

Server operating systems

Linux

DOS

dBase Classic
Windows

dBase Pro

hosted

Linux
OS X
Windows

Data scheme

Schema and schema-less with LDAP views

schema-free

yes

schema-free

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
RESTful HTTP API

none

The IDE can access other DBMS or ODBC-sources.

RESTful HTTP/JSON API

HTTP REST
Java API

Supported programming languages

All languages with LDAP bindings

Go
Haskell
Java
JavaScript
Python
Ruby

dBase proprietary IDE

.Net
Java
JavaScript
Objective-C
PHP
Python
Ruby

Java

Server-side scripts

Stored procedures

The IDE can access stored procedures in other database systems.

user defined functions

in JavaScript

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

cell division

Sharding

none

Sharding

based on Cassandra

Replication methods

Methods for redundantly storing data on multiple nodes

yes

selectable replication factor

none

selectable replication factor

based on Cassandra

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

Foreign keys

Referential integrity

yes

Transaction concepts

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

Atomic execution of specific operations

not for dBase internal data, but IDE does support transactions when accessing external DBMS

Since BigQuery is designed for querying data

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

yes,with MongoDB ord RethinkDB

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

yes

Access rights for users and roles

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

Google Cloud Identity & Access Management (IAM)

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