DBMS > Apache Phoenix vs. Atos Standard Common Repository vs. Microsoft Access vs. Oracle Berkeley DB vs. Snowflake

System Properties Comparison Apache Phoenix vs. Atos Standard Common Repository vs. Microsoft Access vs. Oracle Berkeley DB vs. Snowflake

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

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.)

Widely used in-process key-value store

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

Primary database model

Relational DBMS

Document store
Key-value store

Relational DBMS

Key-value store

supports sorted and unsorted key sets
Native XML DBMS

in the Oracle Berkeley DB XML version

Relational DBMS

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

Score	1.97
Rank	#126	Overall
	#59	Relational DBMS

Score	104.92
Rank	#11	Overall
	#8	Relational DBMS

Score	2.21
Rank	#117	Overall
	#20	Key-value stores
	#3	Native XML DBMS

Score	121.33
Rank	#9	Overall
	#6	Relational DBMS

Website

phoenix.apache.org

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

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

www.oracle.com/database/technologies/related/berkeleydb.html

www.snowflake.com

Technical documentation

phoenix.apache.org

developer.microsoft.com/en-us/access

docs.oracle.com/cd/E17076_05/html/index.html

docs.snowflake.net/manuals/index.html

Developer

Apache Software Foundation

Atos Convergence Creators

Microsoft

Oracle

originally developed by Sleepycat, which was acquired by Oracle

Snowflake Computing Inc.

Initial release

2014

2016

1992

1994

2014

Current release

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

1703

1902 (16.0.11328.20222), March 2019

18.1.40, May 2020

License

Commercial or Open Source

Open Source

Apache Version 2.0

commercial

Bundled with Microsoft Office

Open Source

commercial license available

commercial

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

Java

C++

C, Java, C++ (depending on the Berkeley DB edition)

Server operating systems

Linux
Unix
Windows

Linux

Windows

Not a real database server, but making use of DLLs

AIX
Android
FreeBSD
iOS
Linux
OS X
Solaris
VxWorks
Windows

hosted

Data scheme

yes

late-bound, schema-on-read capabilities

Schema and schema-less with LDAP views

yes

schema-free

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

only with the Berkeley DB XML edition

yes

Secondary indexes

yes

SQL

Support of SQL

yes

but not compliant to any SQL standard

yes

SQL interfaced based on SQLite is available

yes

APIs and other access methods

JDBC

LDAP

ADO.NET
DAO
ODBC
OLE DB

CLI Client
JDBC
ODBC

Supported programming languages

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

All languages with LDAP bindings

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

.Net

Figaro is a .Net framework assembly that extends Berkeley DB XML into an embeddable database engine for .NET
others

Third-party libraries to manipulate Berkeley DB files are available for many languages
C
C#
C++
Java
JavaScript (Node.js)

3rd party binding
Perl
Python
Tcl

JavaScript (Node.js)
Python

Server-side scripts

Stored procedures

user defined functions

yes

since Access 2010 using the ACE-engine

user defined functions

Triggers

yes

since Access 2010 using the ACE-engine

yes

only for the SQL API

similar concept for controling cloud resources

Partitioning methods

Methods for storing different data on different nodes

Sharding

cell division

none

yes

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication
Source-replica replication

yes

none

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

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

User concepts

Access control

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

LDAP bind authentication

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

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

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