DBMS > Apache Phoenix vs. Atos Standard Common Repository vs. OushuDB vs. Snowflake

System Properties Comparison Apache Phoenix vs. Atos Standard Common Repository vs. OushuDB vs. Snowflake

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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

A scale-out RDBMS with evolutionary schema built on Apache HBase

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

A data warehouse powered by Apache HAWQ supporting descriptive analysis and advanced machine learning

Cloud-based data warehousing service for structured and semi-structured data

Primary database model

Relational DBMS

Document store
Key-value store

Relational DBMS

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

Score	1.90
Rank	#125	Overall
	#59	Relational DBMS

Score	0.05
Rank	#357	Overall
	#151	Relational DBMS

Score	133.72
Rank	#7	Overall
	#5	Relational DBMS

Website

phoenix.apache.org

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

www.oushu.com/product/oushuDB

www.snowflake.com

Technical documentation

phoenix.apache.org

www.oushu.com/documentation

docs.snowflake.net/manuals/index.html

Developer

Apache Software Foundation

Atos Convergence Creators

Oushu

Snowflake Computing Inc.

Initial release

2014

2016

2014

Current release

5.0-HBase2, July 2018 and 4.15-HBase1, December 2019

1703

4.0.1, August 2020

License

Commercial or Open Source

Open Source

Apache Version 2.0

commercial

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

Linux
Unix
Windows

Linux

hosted

Data scheme

yes

late-bound, schema-on-read capabilities

Schema and schema-less with LDAP views

yes

support of semi-structured data formats (JSON, XML, Avro)

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

yes

SQL

Support of SQL

yes

Full-featured ANSI SQL support

yes

APIs and other access methods

JDBC

LDAP

JDBC
ODBC

CLI Client
JDBC
ODBC

Supported programming languages

C
C#
C++
Go
Groovy
Java
PHP
Python
Scala

All languages with LDAP bindings

C
C++

JavaScript (Node.js)
Python

Server-side scripts

Stored procedures

user defined functions

yes

user defined functions

Triggers

yes

similar concept for controling cloud resources

Partitioning methods

Methods for storing different data on different nodes

Sharding

cell division

yes

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication
Source-replica replication

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

Hadoop integration

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency or Eventual Consistency

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

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

User concepts

Access control

Access Control Lists (using HBase ACL) for RBAC, integration with Apache Ranger for RBAC & ABAC, multi-tenancy

LDAP bind authentication

Kerberos, SSL and role based access

Users with fine-grained authorization concept, user roles and pluggable authentication

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