DBMS > Hive vs. JaguarDB vs. Oracle Rdb vs. Sadas Engine

System Properties Comparison Hive vs. JaguarDB vs. Oracle Rdb vs. Sadas Engine

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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

Performant, highly scalable DBMS for AI and IoT applications

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

Primary database model

Relational DBMS

Key-value store
Vector DBMS

Relational DBMS

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

Score	61.17
Rank	#18	Overall
	#12	Relational DBMS

Score	0.00
Rank	#383	Overall
	#60	Key-value stores
	#13	Vector DBMS

Score	1.08
Rank	#184	Overall
	#85	Relational DBMS

Score	0.00
Rank	#383	Overall
	#158	Relational DBMS

Website

hive.apache.org

www.jaguardb.com

www.oracle.com/database/technologies/related/rdb.html

www.sadasengine.com

Technical documentation

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

www.jaguardb.com/support.html

www.oracle.com/database/technologies/related/rdb-doc.html

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

Developer

Apache Software Foundation

initially developed by Facebook

DataJaguar, Inc.

Oracle, originally developed by Digital Equipment Corporation (DEC)

SADAS s.r.l.

Initial release

2012

2015

1984

2006

Current release

3.1.3, April 2022

3.3 July 2023

7.4.1.1, 2021

8.0

License

Commercial or Open Source

Open Source

Apache Version 2

Open Source

GPL V3.0

commercial

free trial version available

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

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

Implementation language

Java

C++

the server part. Clients available in other languages

C++

Server operating systems

All OS with a Java VM

Linux

HP Open VMS

AIX
Linux
Windows

Data scheme

yes

Flexible Schema (defined schema, partial schema, schema free)

yes

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

A subset of ANSI SQL is implemented

but no views, foreign keys, triggers

yes

APIs and other access methods

JDBC
ODBC
Thrift

JDBC
ODBC

JDBC
ODBC
Proprietary protocol

Supported programming languages

C++
Java
PHP
Python

C
C++
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
Scala

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

Server-side scripts

Stored procedures

yes

user defined functions and integration of map-reduce

Triggers

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

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

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

yes, on a single node

Concurrency

Support for concurrent manipulation of data

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'

User concepts

Access control

Access rights for users, groups and roles

rights management via user accounts

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

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More resources

DB-Engines blog posts

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