DBMS > Amazon Redshift vs. Atos Standard Common Repository vs. Realm vs. Warp 10

System Properties Comparison Amazon Redshift vs. Atos Standard Common Repository vs. Realm vs. Warp 10

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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

Large scale data warehouse service for use with business intelligence tools

Highly scalable database system, designed for managing session and subscriber data in modern mobile communication networks

A DBMS built for use on mobile devices that’s a fast, easy to use alternative to SQLite and Core Data

TimeSeries DBMS specialized on timestamped geo data based on LevelDB or HBase

Primary database model

Relational DBMS

Document store
Key-value store

Document store

Time Series DBMS

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

Score	17.94
Rank	#34	Overall
	#21	Relational DBMS

Score	7.60
Rank	#52	Overall
	#9	Document stores

Score	0.07
Rank	#349	Overall
	#32	Time Series DBMS

Website

aws.amazon.com/redshift

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

realm.io

www.warp10.io

Technical documentation

docs.aws.amazon.com/redshift

realm.io/docs

www.warp10.io/content/02_Getting_started

Developer

Amazon (based on PostgreSQL)

Atos Convergence Creators

Realm, acquired by MongoDB in May 2019

SenX

Initial release

2012

2016

2014

2015

Current release

1703

License

Commercial or Open Source

commercial

Open Source

Apache License 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

Server operating systems

hosted

Linux

Android
Backend: server-less
iOS
Windows

Linux
OS X
Windows

Data scheme

yes

Schema and schema-less with LDAP views

yes

schema-free

Typing

predefined data types such as float or date

yes

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

restricted

yes

SQL

Support of SQL

yes

does not fully support an SQL-standard

APIs and other access methods

JDBC
ODBC

LDAP

HTTP API
Jupyter
WebSocket

Supported programming languages

All languages supporting JDBC/ODBC

All languages with LDAP bindings

.Net
Java

with Android only
Objective-C
React Native
Swift

Server-side scripts

Stored procedures

user defined functions

in Python

runs within the applications so server-side scripts are unnecessary

yes

WarpScript

Triggers

yes

Change Listeners

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

Immediate Consistency or Eventual Consistency depending on configuration

Immediate Consistency

based on HBase

Foreign keys

Referential integrity

yes

informational only, not enforced by the system

Transaction concepts

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

ACID

Atomic execution of specific operations

ACID

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

In-Memory realm

yes

User concepts

Access control

fine grained access rights according to SQL-standard

LDAP bind authentication

yes

Mandatory use of cryptographic tokens, containing fine-grained authorizations

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