DBMS > Hive vs. MySQL vs. RethinkDB vs. SAP Adaptive Server

System Properties Comparison Hive vs. MySQL vs. RethinkDB vs. SAP Adaptive Server

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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

Widely used open source RDBMS

DBMS for the Web with a mechanism to push updated query results to applications in realtime.

The SAP (Sybase) Adaptive Server Enterprise (ASE) is an enterprise-class RDBMS

Primary database model

Relational DBMS

Key/Value like access via memcached API

Document store

Relational DBMS

Secondary database models

Document store
Spatial DBMS

Spatial DBMS

with Boeing's Spatial Query Server

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

Score	61.17
Rank	#18	Overall
	#12	Relational DBMS

Score	1083.74
Rank	#2	Overall
	#2	Relational DBMS

Score	2.74
Rank	#105	Overall
	#19	Document stores

Score	36.31
Rank	#25	Overall
	#17	Relational DBMS

Website

hive.apache.org

www.mysql.com

rethinkdb.com

www.sap.com/products/technology-platform/sybase-ase.html

Technical documentation

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

dev.mysql.com/doc

rethinkdb.com/docs

help.sap.com/docs/SAP_ASE

Developer

Apache Software Foundation

initially developed by Facebook

Oracle

since 2010, originally MySQL AB, then Sun

The Linux Foundation

since July 2017

SAP, Sybase

Initial release

2012

1995

2009

1987

Current release

3.1.3, April 2022

8.4.0, April 2024

2.4.1, August 2020

16.0

License

Commercial or Open Source

Open Source

Apache Version 2

Open Source

GPL version 2. Commercial licenses with extended functionallity are available

Open Source

Apache Version 2

commercial

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 and C++

C++

C and C++

Server operating systems

All OS with a Java VM

FreeBSD
Linux
OS X
Solaris
Windows

Linux
OS X
Windows

AIX
HP-UX
Linux
Solaris
Unix
Windows

Data scheme

yes

schema-free

yes

Typing

predefined data types such as float or date

yes

string, binary, float, bool, date, geometry

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

SQL-like DML and DDL statements

yes

with proprietary extensions

yes

APIs and other access methods

JDBC
ODBC
Thrift

ADO.NET
JDBC
ODBC
Proprietary native API

ADO.NET
JDBC
ODBC
OLE DB
Tabular Data Stream (TDS)

Supported programming languages

C++
Java
PHP
Python

Ada
C
C#
C++
D
Delphi
Eiffel
Erlang
Haskell
Java
JavaScript (Node.js)
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl

community-supported driver
C#

community-supported driver
C++

community-supported driver
Clojure

community-supported driver
Dart

community-supported driver
Erlang

community-supported driver
Go

community-supported driver
Haskell

community-supported driver
Java

official driver
JavaScript (Node.js)

official driver
Lisp

community-supported driver
Lua

community-supported driver
Objective-C

community-supported driver
Perl

community-supported driver
PHP

community-supported driver
Python

official driver
Ruby

official driver
Scala

community-supported driver

C
C++
Cobol
Java
Java
Perl
PHP
Python

Server-side scripts

Stored procedures

yes

user defined functions and integration of map-reduce

yes

proprietary syntax

Java and Transact-SQL

Triggers

yes

Client-side triggers through changefeeds

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

horizontal partitioning, sharding with MySQL Cluster or MySQL Fabric

Sharding

range based

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

Multi-source replication
Source-replica replication

Source-replica replication

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

query execution via MapReduce

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

not for MyISAM storage engine

yes

Transaction concepts

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

ACID

not for MyISAM storage engine

Atomic single-document operations

ACID

Concurrency

Support for concurrent manipulation of data

yes

table locks or row locks depending on storage engine

yes

MVCC based

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 rights for users, groups and roles

Users with fine-grained authorization concept

no user groups or roles

yes

users and table-level permissions

fine grained access rights according to SQL-standard

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