DBMS > Apache Phoenix vs. Atos Standard Common Repository vs. Cassandra vs. Microsoft Access vs. Tibero

System Properties Comparison Apache Phoenix vs. Atos Standard Common Repository vs. Cassandra vs. Microsoft Access vs. Tibero

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

Wide-column store based on ideas of BigTable and DynamoDB

Optimized for write access

Microsoft Access combines a backend RDBMS (JET / ACE Engine) with a GUI frontend for data manipulation and queries.

The Access frontend is often used for accessing other datasources (DBMS, Excel, etc.)

A secure RDBMS, designed for easy portability from Oracle

Primary database model

Relational DBMS

Document store
Key-value store

Wide column store

Relational DBMS

Secondary database models

Vector DBMS

starting with release V5

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

Score	1.97
Rank	#126	Overall
	#59	Relational DBMS

Score	101.89
Rank	#12	Overall
	#1	Wide column stores

Score	104.92
Rank	#11	Overall
	#8	Relational DBMS

Score	1.78
Rank	#140	Overall
	#64	Relational DBMS

Website

phoenix.apache.org

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

cassandra.apache.org

www.microsoft.com/en-us/microsoft-365/access

us.tmaxsoft.com/products/tibero

Technical documentation

phoenix.apache.org

cassandra.apache.org/doc/latest

developer.microsoft.com/en-us/access

technet.tmaxsoft.com/upload/download/online/tibero/pver-20150504-000002/index.html

Developer

Apache Software Foundation

Atos Convergence Creators

Apache Software Foundation

Apache top level project, originally developped by Facebook

Microsoft

TmaxSoft

Initial release

2014

2016

2008

1992

2003

Current release

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

1703

4.1.3, July 2023

1902 (16.0.11328.20222), March 2019

6, April 2015

License

Commercial or Open Source

Open Source

Apache Version 2.0

commercial

Open Source

Apache version 2

commercial

Bundled with Microsoft Office

commercial

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.

Astra DB: Multi-cloud DBaaS built on Apache Cassandra.

Implementation language

Java

C++

C and Assembler

Server operating systems

Linux
Unix
Windows

Linux

BSD
Linux
OS X
Windows

Windows

Not a real database server, but making use of DLLs

AIX
HP-UX
Linux
Solaris
Windows

Data scheme

yes

late-bound, schema-on-read capabilities

Schema and schema-less with LDAP views

schema-free

yes

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

restricted

only equality queries, not always the best performing solution

yes

SQL

Support of SQL

yes

SQL-like SELECT, DML and DDL statements (CQL)

yes

but not compliant to any SQL standard

yes

APIs and other access methods

JDBC

LDAP

Proprietary protocol

CQL (Cassandra Query Language, an SQL-like language)
Thrift

ADO.NET
DAO
ODBC
OLE DB

JDBC
ODBC
ODP.NET
Oracle Call Interface (OCI)
Tibero CLI

Supported programming languages

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

All languages with LDAP bindings

C#
C++
Clojure
Erlang
Go
Haskell
Java
JavaScript

Node.js
Perl
PHP
Python
Ruby
Scala

C
C#
C++
Delphi
Java (JDBC-ODBC)
VBA
Visual Basic.NET

C
C#
C++
Cobol
Java
Objective-C
Perl
PHP
Python
Ruby
Visual Basic

Server-side scripts

Stored procedures

user defined functions

yes

since Access 2010 using the ACE-engine

Persistent Stored Procedure (PSM)

Triggers

yes

since Access 2010 using the ACE-engine

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

cell division

Sharding

no "single point of failure"

none

horizontal partitioning

by range, hash, list or composite

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication
Source-replica replication

yes

selectable replication factor

Representation of geographical distribution of servers is possible

none

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

Hadoop integration

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency or Eventual Consistency

Immediate Consistency or Eventual Consistency depending on configuration

Eventual Consistency
Immediate Consistency

can be individually decided for each write operation

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

Atomicity and isolation are supported for single operations

ACID

but no files for transaction logging

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

but no files for transaction logging

yes

In-memory capabilities

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

yes

planned for next version

User concepts

Access control

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

LDAP bind authentication

Access rights for users can be defined per object

a simple user-level security was built in till version Access 2003

fine grained access rights according to SQL-standard (SQL 92, SQL 99)

More information provided by the system vendor

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Licensing and pricing models

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