DBMS > Kinetica vs. MarkLogic vs. Sadas Engine vs. Valentina Server

System Properties Comparison Kinetica vs. MarkLogic vs. Sadas Engine vs. Valentina Server

Please select another system to include it in the comparison.

Editorial information provided by DB-Engines

Name

Description

Fully vectorized database across both GPUs and CPUs

Operational and transactional Enterprise NoSQL database

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

Object-relational database and reports server

Primary database model

Relational DBMS

Document store
Native XML DBMS
RDF store

as of version 7
Search engine

Relational DBMS

Secondary database models

Spatial DBMS
Time Series DBMS

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

Score	0.69
Rank	#234	Overall
	#107	Relational DBMS

Score	6.50
Rank	#56	Overall
	#10	Document stores
	#1	Native XML DBMS
	#1	RDF stores
	#5	Search engines

Score	0.03
Rank	#379	Overall
	#156	Relational DBMS

Score	0.18
Rank	#329	Overall
	#144	Relational DBMS

Website

Technical documentation

docs.kinetica.com

docs.marklogic.com

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

valentina-db.com/docs/dokuwiki/v5/doku.php

Developer

Kinetica

MarkLogic Corp.

SADAS s.r.l.

Paradigma Software

Initial release

2012

2001

2006

1999

Current release

7.1, August 2021

11.0, December 2022

8.0

5.7.5

License

Commercial or Open Source

commercial

restricted free version is available

commercial

free trial version available

commercial

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, C++

C++

Server operating systems

Linux

Linux
OS X
Windows

AIX
Linux
Windows

Linux
OS X
Windows

Data scheme

yes

schema-free

Schema can be enforced

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

SQL92

yes

APIs and other access methods

JDBC
ODBC
RESTful HTTP API

Java API
Node.js Client API
ODBC
proprietary Optic API

Proprietary Query API, introduced with version 9
RESTful HTTP API
SPARQL
WebDAV
XDBC
XQuery
XSLT

JDBC
ODBC
Proprietary protocol

ODBC

Supported programming languages

C++
Java
JavaScript (Node.js)
Python

C
C#
C++
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby

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

.Net
C
C#
C++
Objective-C
PHP
Ruby
Visual Basic
Visual Basic.NET

Server-side scripts

Stored procedures

user defined functions

yes

via XQuery or JavaScript

yes

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

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

yes

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

via Hadoop Connector, HDFS Direct Access and in-database MapReduce jobs

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

can act as a resource manager in an XA/JTA transaction

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, with Range Indexes

yes

managed by 'Learn by Usage'

yes

User concepts

Access control

Access rights for users and roles on table level

Role-based access control at the document and subdocument levels

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

fine grained access rights according to SQL-standard

More information provided by the system vendor

We invite representatives of system vendors to contact us for updating and extending the system information,
and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

Related products and services

We invite representatives of vendors of related products to contact us for presenting information about their offerings here.

More resources

Recent citations in the news

Kinetica Delivers Real-Time Vector Similarity Search
21 March 2024, insideBIGDATA

Kinetica Elevates RAG with Fast Access to Real-Time Data
26 March 2024, Datanami

Kinetica ramps up RAG for generative AI, empowering enterprises with real-time operational data
18 March 2024, SiliconANGLE News

Kinetica Launches Generative AI Solution for Real-Time Inferencing Powered by NVIDIA AI Enterprise
18 March 2024, GlobeNewswire

Transforming spatiotemporal data analysis with GPUs and generative AI
30 October 2023, InfoWorld

provided by Google News

MarkLogic “The NoSQL Database”. In the MarkLogic Query Console, you can… | by Abhay Srivastava | Apr, 2024
23 April 2024, Medium

Database Platform to Simplify Complex Data | Progress Marklogic
7 February 2023, Progress Software

ABN AMRO Moves Progress-Powered Credit Store App to Azure Cloud; Achieves 40% Faster Data Processing, Lower ...
12 March 2024, GlobeNewswire

Seven Quick Steps to Setting Up MarkLogic Server in Kubernetes
1 February 2024, BI-Platform.nl

Progress's $355m move for MarkLogic sets the tone for 2023
4 January 2023, The Stack

provided by Google News

A Look at Valentina — SitePoint
18 April 2014, SitePoint

MySQL GUI Tools for Windows and Ubuntu/Linux: Top 8 free or open source
7 December 2018, H2S Media

provided by Google News

Share this page