DBMS > Kinetica vs. Microsoft Azure AI Search vs. Oracle vs. Tigris

System Properties Comparison Kinetica vs. Microsoft Azure AI Search vs. Oracle vs. Tigris

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Editorial information provided by DB-Engines

Name

Description

Fully vectorized database across both GPUs and CPUs

Search-as-a-service for web and mobile app development

Widely used RDBMS

A horizontally scalable, ACID transactional, document database available both as a fully managed cloud service and for deployment on self-managed infrastructure

Primary database model

Relational DBMS

Search engine

Relational DBMS

Document store
Key-value store
Search engine
Time Series DBMS

Secondary database models

Spatial DBMS
Time Series DBMS

Vector DBMS

Document store
Graph DBMS

with Oracle Spatial and Graph
RDF store

with Oracle Spatial and Graph
Spatial DBMS

with Oracle Spatial and Graph
Vector DBMS

since Oracle 23

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

Score	0.66
Rank	#234	Overall
	#107	Relational DBMS

Score	5.52
Rank	#59	Overall
	#6	Search engines

Score	1244.08
Rank	#1	Overall
	#1	Relational DBMS

Score	0.09
Rank	#363	Overall
	#49	Document stores
	#54	Key-value stores
	#22	Search engines
	#38	Time Series DBMS

Website

www.kinetica.com

azure.microsoft.com/en-us/services/search

www.oracle.com/database

www.tigrisdata.com

Technical documentation

docs.kinetica.com

learn.microsoft.com/en-us/azure/search

docs.oracle.com/en/database

www.tigrisdata.com/docs

Developer

Kinetica

Microsoft

Oracle

Tigris Data, Inc.

Initial release

2012

2015

1980

2022

Current release

7.1, August 2021

23c, September 2023

License

Commercial or Open Source

commercial

restricted free version is available

Open Source

Apache Version 2.0

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

C, C++

C and C++

Server operating systems

Linux

hosted

AIX
HP-UX
Linux
OS X
Solaris
Windows
z/OS

Linux
macOS
Windows

Data scheme

yes

Schemaless in JSON and XML columns

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.

yes

Secondary indexes

yes

SQL

Support of SQL

SQL-like DML and DDL statements

yes

with proprietary extensions

APIs and other access methods

JDBC
ODBC
RESTful HTTP API

RESTful HTTP API

JDBC
ODBC
ODP.NET
Oracle Call Interface (OCI)

CLI Client
gRPC
RESTful HTTP API

Supported programming languages

C++
Java
JavaScript (Node.js)
Python

C#
Java
JavaScript
Python

C
C#
C++
Clojure
Cobol
Delphi
Eiffel
Erlang
Fortran
Groovy
Haskell
Java
JavaScript
Lisp
Objective C
OCaml
Perl
PHP
Python
R
Ruby
Scala
Tcl
Visual Basic

Go
Java
JavaScript (Node.js)

Server-side scripts

Stored procedures

user defined functions

PL/SQL

also stored procedures in Java possible

Triggers

yes

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

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

Implicit feature of the cloud service

Sharding, horizontal partitioning

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

yes

Implicit feature of the cloud service

Multi-source replication
Source-replica replication

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

can be realized in PL/SQL

Consistency concepts

Methods to ensure consistency in a distributed system

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

ACID

isolation level can be parameterized

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

yes, using FoundationDB

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

Version 12c introduced the new option 'Oracle Database In-Memory'

User concepts

Access control

Access rights for users and roles on table level

yes

using Azure authentication

fine grained access rights according to SQL-standard

Access rights for users and roles

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