DBMS > Atos Standard Common Repository vs. Databricks vs. eXtremeDB vs. RethinkDB

System Properties Comparison Atos Standard Common Repository vs. Databricks vs. eXtremeDB vs. RethinkDB

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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

The Databricks Lakehouse Platform combines elements of data lakes and data warehouses to provide a unified view onto structured and unstructured data. It is based on Apache Spark.

Natively in-memory DBMS with options for persistency, high-availability and clustering

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

Primary database model

Document store
Key-value store

Document store
Relational DBMS

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	84.24
Rank	#14	Overall
	#2	Document stores
	#9	Relational DBMS

Score	0.79
Rank	#212	Overall
	#100	Relational DBMS
	#18	Time Series DBMS

Score	2.58
Rank	#105	Overall
	#20	Document stores

Website

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

www.databricks.com

www.mcobject.com

rethinkdb.com

Technical documentation

docs.databricks.com

www.mcobject.com/docs/extremedb.htm

rethinkdb.com/docs

Developer

Atos Convergence Creators

Databricks

McObject

The Linux Foundation

since July 2017

Initial release

2016

2013

2001

2009

Current release

1703

8.2, 2021

2.4.1, August 2020

License

Commercial or Open Source

commercial

Open Source

Apache Version 2

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 and C++

C++

Server operating systems

Linux

hosted

AIX
HP-UX
Linux
macOS
Solaris
Windows

Linux
OS X
Windows

Data scheme

Schema and schema-less with LDAP views

Flexible Schema (defined schema, partial schema, schema free)

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

support of XML interfaces available

Secondary indexes

yes

SQL

Support of SQL

with Databricks SQL

yes

with the option: eXtremeSQL

APIs and other access methods

LDAP

JDBC
ODBC
RESTful HTTP API

.NET Client API
JDBC
JNI
ODBC
Proprietary protocol
RESTful HTTP API

Supported programming languages

All languages with LDAP bindings

Python
R
Scala

.Net
C
C#
C++
Java
Lua
Python
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

user defined functions and aggregates

yes

Triggers

yes

by defining events

Client-side triggers through changefeeds

Partitioning methods

Methods for storing different data on different nodes

Sharding

cell division

horizontal partitioning / sharding

Sharding

range based

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Active Replication Fabric™ for IoT
Multi-source replication

by means of eXtremeDB Cluster option
Source-replica replication

by means of eXtremeDB High Availability option

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

Immediate Consistency

Foreign keys

Referential integrity

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

Optimistic (MVCC) and pessimistic (locking) strategies available

yes

MVCC based

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

yes

users and table-level permissions

More information provided by the system vendor

Specific characteristics

Supported database models : In addition to the Document store and Relational DBMS...
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