DBMS > Apache Phoenix vs. Atos Standard Common Repository vs. Couchbase vs. Hive vs. Microsoft Access

System Properties Comparison Apache Phoenix vs. Atos Standard Common Repository vs. Couchbase vs. Hive vs. Microsoft Access

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 distributed document store with integrated cache, a powerful search engine, in-built operational and analytical capabilities, and an embedded mobile database

data warehouse software for querying and managing large distributed datasets, built on Hadoop

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.)

Primary database model

Relational DBMS

Document store
Key-value store

Document store

Relational DBMS

Secondary database models

Key-value store

originating from the former Membase product and supporting the Memcached protocol
Spatial DBMS

using the Geocouch extension
Search engine
Time Series DBMS
Vector DBMS

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

Score	1.97
Rank	#126	Overall
	#59	Relational DBMS

Score	17.30
Rank	#36	Overall
	#5	Document stores

Score	61.17
Rank	#18	Overall
	#12	Relational DBMS

Score	104.92
Rank	#11	Overall
	#8	Relational DBMS

Website

phoenix.apache.org

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

www.couchbase.com

hive.apache.org

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

Technical documentation

phoenix.apache.org

docs.couchbase.com

cwiki.apache.org/confluence/display/Hive/Home

developer.microsoft.com/en-us/access

Developer

Apache Software Foundation

Atos Convergence Creators

Couchbase, Inc.

Apache Software Foundation

initially developed by Facebook

Microsoft

Initial release

2014

2016

2011

2012

1992

Current release

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

1703

Server: 7.2, June 2023; Mobile: 3.1, March 2022; Couchbase Capella (DBaaS), June 2023

3.1.3, April 2022

1902 (16.0.11328.20222), March 2019

License

Commercial or Open Source

Open Source

Apache Version 2.0

commercial

Open Source

Business Source License (BSL 1.1); Commercial licenses also available

Open Source

Apache Version 2

commercial

Bundled with Microsoft Office

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

Java

C, C++, Go and Erlang

Java

C++

Server operating systems

Linux
Unix
Windows

Linux

Linux
OS X
Windows

All OS with a Java VM

Windows

Not a real database server, but making use of DLLs

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

SQL

Support of SQL

yes

SQL++, extends ANSI SQL to JSON for operational, transactional, and analytic use cases

SQL-like DML and DDL statements

yes

but not compliant to any SQL standard

APIs and other access methods

JDBC

LDAP

CLI Client
HTTP REST
Kafka Connector
Native language bindings for CRUD, Query, Search and Analytics APIs
Spark Connector
Spring Data

JDBC
ODBC
Thrift

ADO.NET
DAO
ODBC
OLE DB

Supported programming languages

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

All languages with LDAP bindings

.Net
C
Go
Java
JavaScript

Node.js
Kotlin
PHP
Python
Ruby
Scala

C++
Java
PHP
Python

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

Server-side scripts

Stored procedures

user defined functions

Functions and timers in JavaScript and UDFs in Java, Python, SQL++

yes

user defined functions and integration of map-reduce

yes

since Access 2010 using the ACE-engine

Triggers

yes

via the TAP protocol

yes

since Access 2010 using the ACE-engine

Partitioning methods

Methods for storing different data on different nodes

Sharding

cell division

Automatic Sharding

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication
Source-replica replication

yes

Multi-source replication

including cross data center replication
Source-replica replication

selectable replication factor

none

MapReduce

Offers an API for user-defined Map/Reduce methods

Hadoop integration

yes

query execution via MapReduce

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

selectable on a per-operation basis

Eventual 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

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

but no files for transaction logging

In-memory capabilities

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

yes

Ephemeral buckets

User concepts

Access control

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

LDAP bind authentication

User and Administrator separation with password-based and LDAP integrated Authentication. Role-base access control.

Access rights for users, groups and roles

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

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