DBMS > Atos Standard Common Repository vs. BigObject vs. Lovefield vs. Machbase Neo vs. RethinkDB

System Properties Comparison Atos Standard Common Repository vs. BigObject vs. Lovefield vs. Machbase Neo vs. RethinkDB

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

Embeddable relational database for web apps written in pure JavaScript

TimeSeries DBMS for AIoT and BigData

DBMS for the Web with a mechanism to push updated query results to applications in realtime.

Primary database model

Document store
Key-value store

Relational DBMS

a hierachical model (tree) can be imposed

Relational DBMS

Time Series DBMS

Document store

Secondary database models

Spatial DBMS

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

Score	0.19
Rank	#329	Overall
	#146	Relational DBMS

Score	0.33
Rank	#286	Overall
	#131	Relational DBMS

Score	0.17
Rank	#337	Overall
	#30	Time Series DBMS

Score	2.66
Rank	#107	Overall
	#20	Document stores

Website

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

bigobject.io

google.github.io/lovefield

machbase.com

rethinkdb.com

Technical documentation

docs.bigobject.io

github.com/google/lovefield/blob/master/docs/spec_index.md

machbase.com/dbms

rethinkdb.com/docs

Developer

Atos Convergence Creators

BigObject, Inc.

Google

Machbase

The Linux Foundation

since July 2017

Initial release

2016

2015

2014

2013

2009

Current release

1703

2.1.12, February 2017

V8.0, August 2023

2.4.1, August 2020

License

Commercial or Open Source

commercial

free community edition available

Open Source

Apache 2.0

commercial

free test version available

Open Source

Apache Version 2

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

JavaScript

C++

Server operating systems

Linux

distributed as a docker-image
OS X

distributed as a docker-image (boot2docker)
Windows

distributed as a docker-image (boot2docker)

server-less, requires a JavaScript environment (browser, Node.js)

tested with Chrome, Firefox, IE, Safari

Linux
macOS
Windows

Linux
OS X
Windows

Data scheme

Schema and schema-less with LDAP views

yes

schema-free

Typing

predefined data types such as float or date

optional

yes

string, binary, float, bool, date, geometry

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

SQL-like query language

via JavaScript builder pattern

SQL-like query language

APIs and other access methods

LDAP

fluentd
ODBC
RESTful HTTP API

gRPC
HTTP REST
JDBC
MQTT (Message Queue Telemetry Transport)
ODBC

Supported programming languages

All languages with LDAP bindings

JavaScript

C
C#
C++
Go
Java
JavaScript
PHP

via ODBC
Python
R

via ODBC
Scala

community-supported driver
C#

community-supported driver
C++

community-supported driver
Clojure

community-supported driver
Dart

community-supported driver
Erlang

community-supported driver
Go

community-supported driver
Haskell

community-supported driver
Java

official driver
JavaScript (Node.js)

official driver
Lisp

community-supported driver
Lua

community-supported driver
Objective-C

community-supported driver
Perl

community-supported driver
PHP

community-supported driver
Python

official driver
Ruby

official driver
Scala

community-supported driver

Server-side scripts

Stored procedures

Lua

Triggers

yes

Using read-only observers

Client-side triggers through changefeeds

Partitioning methods

Methods for storing different data on different nodes

Sharding

cell division

none

Sharding

range based

Replication methods

Methods for redundantly storing data on multiple nodes

yes

none

selectable replication factor

Source-replica replication

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

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

Atomic single-document operations

Concurrency

Support for concurrent manipulation of data

yes

Read/write lock on objects (tables, trees)

yes

MVCC based

Durability

Support for making data persistent

yes

yes, by using IndexedDB or the cloud service Firebase Realtime Database

yes

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

yes

using MemoryDB

yes

volatile and lookup table

User concepts

Access control

LDAP bind authentication

simple password-based access control

yes

users and table-level permissions

More information provided by the system vendor

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More resources

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