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

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

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Editorial information provided by DB-Engines

Name

Description

Performant, highly scalable DBMS for AI and IoT applications

Fully vectorized database across both GPUs and CPUs

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

Primary database model

Key-value store
Vector DBMS

Relational DBMS

Secondary database models

Spatial DBMS
Time Series DBMS

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

Score	0.09
Rank	#356	Overall
	#53	Key-value stores
	#13	Vector DBMS

Score	0.69
Rank	#234	Overall
	#107	Relational DBMS

Score	1.08
Rank	#187	Overall
	#85	Relational DBMS

Score	0.03
Rank	#379	Overall
	#156	Relational DBMS

Website

www.jaguardb.com

www.kinetica.com

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

www.sadasengine.com

Technical documentation

www.jaguardb.com/support.html

docs.kinetica.com

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

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

Developer

DataJaguar, Inc.

Kinetica

Oracle, originally developed by Digital Equipment Corporation (DEC)

SADAS s.r.l.

Initial release

2015

2012

1984

2006

Current release

3.3 July 2023

7.1, August 2021

7.4.1.1, 2021

8.0

License

Commercial or Open Source

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

C++

the server part. Clients available in other languages

C, C++

C++

Server operating systems

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

A subset of ANSI SQL is implemented

but no views, foreign keys, triggers

SQL-like DML and DDL statements

yes

APIs and other access methods

JDBC
ODBC

JDBC
ODBC
RESTful HTTP API

JDBC
ODBC
Proprietary protocol

Supported programming languages

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

C++
Java
JavaScript (Node.js)
Python

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

Server-side scripts

Stored procedures

user defined functions

Triggers

yes

triggers when inserted values for one or more columns fall within a specified range

Partitioning methods

Methods for storing different data on different nodes

Sharding

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication

Source-replica replication

none

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

Immediate Consistency or Eventual Consistency depending on configuration

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

GPU vRAM or System RAM

yes

managed by 'Learn by Usage'

User concepts

Access control

rights management via user accounts

Access rights for users and roles on table level

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

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