DBMS > Hive vs. IBM Cloudant vs. Sadas Engine vs. YottaDB

System Properties Comparison Hive vs. IBM Cloudant vs. Sadas Engine vs. YottaDB

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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

Database as a Service offering based on Apache CouchDB

SADAS Engine is a columnar DBMS specifically designed for high performance in data warehouse environments

A fast and solid embedded Key-value store

Primary database model

Secondary database models

Relational DBMS

using the Octo plugin

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	0.07
Rank	#373	Overall
	#157	Relational DBMS

Score	0.28
Rank	#306	Overall
	#44	Key-value stores

Website

hive.apache.org

www.ibm.com/products/cloudant

www.sadasengine.com

yottadb.com

Technical documentation

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

cloud.ibm.com/docs/Cloudant

www.sadasengine.com/en/sadas-engine-download-free-trial-and-documentation/#documentation

yottadb.com/resources/documentation

Developer

Apache Software Foundation

initially developed by Facebook

IBM, Apache Software Foundation

IBM acquired Cloudant in February 2014

SADAS s.r.l.

YottaDB, LLC

Initial release

2012

2010

2006

2001

Current release

3.1.3, April 2022

8.0

License

Commercial or Open Source

Open Source

Apache Version 2

commercial

free trial version available

Open Source

AGPL 3.0

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

Java

Erlang

C++

Server operating systems

All OS with a Java VM

hosted

AIX
Linux
Windows

Docker
Linux

Data scheme

yes

schema-free

yes

schema-free

Typing

predefined data types such as float or date

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.

Secondary indexes

yes

SQL

Support of SQL

SQL-like DML and DDL statements

yes

by using the Octo plugin

APIs and other access methods

JDBC
ODBC
Thrift

RESTful HTTP/JSON API

JDBC
ODBC
Proprietary protocol

PostgreSQL wire protocol

using the Octo plugin
Proprietary protocol

Supported programming languages

C++
Java
PHP
Python

C#
Java
JavaScript
Objective-C
PHP
Ruby

.Net
C
C#
C++
Groovy
Java
PHP
Python

C
Go
JavaScript (Node.js)
Lua
M
Perl
Python
Rust

Server-side scripts

Stored procedures

yes

user defined functions and integration of map-reduce

View functions (Map-Reduce) in JavaScript

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

Multi-source replication
Source-replica replication

none

yes

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

Transaction concepts

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

atomic operations within a document possible

optimistic locking

Concurrency

Support for concurrent manipulation of data

yes

Optimistic locking

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

managed by 'Learn by Usage'

yes

User concepts

Access control

Access rights for users, groups and roles

Access rights for users can be defined per database

Access rights for users, groups and roles according to SQL-standard

Users and groups based on OS-security mechanisms

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More resources

DB-Engines blog posts

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13 May 2013, Paul Andlinger

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