DBMS > Hive vs. Microsoft Access

System Properties Comparison Hive vs. Microsoft Access

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Editorial information provided by DB-Engines

Name

Description

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

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Score	76.19
Rank	#14	Overall
	#9	Relational DBMS

Score	115.40
Rank	#10	Overall
	#7	Relational DBMS

Website

hive.apache.org

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

Technical documentation

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

developer.microsoft.com/en-us/access

Developer

Apache Software Foundation

initially developed by Facebook

Microsoft

Initial release

2012

1992

Current release

3.1.2, August 2019

1902 (16.0.11328.20222), March 2019

License

Commercial or Open Source

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++

Server operating systems

All OS with a Java VM

Windows

Not a real database server, but making use of DLLs

Data scheme

yes

Typing

predefined data types such as float or date

yes

Secondary indexes

yes

SQL

Support of SQL

SQL-like DML and DDL statements

yes

but not compliant to any SQL standard

APIs and other access methods

JDBC
ODBC
Thrift

ADO.NET
DAO
ODBC
OLE DB

Supported programming languages

C++
Java
PHP
Python

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

Server-side scripts

Stored procedures

yes

user defined functions and integration of map-reduce

yes

since Access 2010 using the ACE-engine

Triggers

yes

since Access 2010 using the ACE-engine

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

query execution via MapReduce

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

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

User concepts

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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More resources

DB-Engines blog posts

Why is Hadoop not listed in the DB-Engines Ranking?
13 May 2013, Paul Andlinger

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MS Access drops in DB-Engines Ranking
2 May 2013, Paul Andlinger

Microsoft SQL Server regained rank 2 in the DB-Engines popularity ranking
3 December 2012, Matthias Gelbmann

New DB-Engines Ranking shows the popularity of database management systems
3 October 2012, Matthias Gelbmann, Paul Andlinger

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