DBMS > Hive vs. IBM Cloudant vs. MySQL vs. SQream DB vs. Trafodion

System Properties Comparison Hive vs. IBM Cloudant vs. MySQL vs. SQream DB vs. Trafodion

Editorial information provided by DB-Engines

Name

Apache Trafodion has been retired in 2021. Therefore it is excluded from the DB-Engines Ranking.

Description

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

Database as a Service offering based on Apache CouchDB

Widely used open source RDBMS

a GPU-based, columnar RDBMS for big data analytics workloads

Transactional SQL-on-Hadoop DBMS

Primary database model

Relational DBMS

Document store

Relational DBMS

Key/Value like access via memcached API

Relational DBMS

Secondary database models

Document store
Spatial DBMS

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

Score	59.76
Rank	#18	Overall
	#12	Relational DBMS

Score	2.75
Rank	#104	Overall
	#19	Document stores

Score	1061.34
Rank	#2	Overall
	#2	Relational DBMS

Score	0.74
Rank	#224	Overall
	#103	Relational DBMS

Website

hive.apache.org

www.ibm.com/products/cloudant

www.mysql.com

sqream.com

trafodion.apache.org

Technical documentation

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

cloud.ibm.com/docs/Cloudant

dev.mysql.com/doc

docs.sqream.com

trafodion.apache.org/documentation.html

Developer

Apache Software Foundation

initially developed by Facebook

IBM, Apache Software Foundation

IBM acquired Cloudant in February 2014

Oracle

since 2010, originally MySQL AB, then Sun

SQream Technologies

Apache Software Foundation, originally developed by HP

Initial release

2012

2010

1995

2017

2014

Current release

3.1.3, April 2022

8.4.0, April 2024

2022.1.6, December 2022

2.3.0, February 2019

License

Commercial or Open Source

Open Source

Apache Version 2

commercial

Open Source

GPL version 2. Commercial licenses with extended functionallity are available

commercial

Open Source

Apache 2.0

Cloud-based only

Only available as a cloud service

yes

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Implementation language

Java

Erlang

C and C++

C++, CUDA, Haskell, Java, Scala

C++, Java

Server operating systems

All OS with a Java VM

hosted

FreeBSD
Linux
OS X
Solaris
Windows

Linux

Data scheme

yes

schema-free

yes

Typing

predefined data types such as float or date

yes

yes, ANSI Standard SQL Types

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

RESTful HTTP/JSON API

ADO.NET
JDBC
ODBC
Proprietary native API

.Net
JDBC
ODBC

ADO.NET
JDBC
ODBC

Supported programming languages

C++
Java
PHP
Python

C#
Java
JavaScript
Objective-C
PHP
Ruby

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

C++
Java
JavaScript (Node.js)
Python

All languages supporting JDBC/ODBC/ADO.Net

Server-side scripts

Stored procedures

yes

user defined functions and integration of map-reduce

View functions (Map-Reduce) in JavaScript

yes

proprietary syntax

user defined functions in Python

Java Stored Procedures

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

horizontal partitioning, sharding with MySQL Cluster or MySQL Fabric

horizontal and vertical partitioning

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

Multi-source replication
Source-replica replication

none

yes, via HBase

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

query execution via MapReduce

yes

via user defined functions and HBase

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

atomic operations within a document possible

ACID

not for MyISAM storage engine

ACID

Concurrency

Support for concurrent manipulation of data

yes

Optimistic locking

yes

table locks or row locks depending on storage engine

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

Access rights for users can be defined per database

Users with fine-grained authorization concept

no user groups or roles

fine grained access rights according to SQL-standard

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