DBMS > Kinetica vs. Valentina Server vs. Vertica

System Properties Comparison Kinetica vs. Valentina Server vs. Vertica

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Editorial information provided by DB-Engines

Name

Description

Fully vectorized database across both GPUs and CPUs

Object-relational database and reports server

Cloud or off-cloud analytical database and query engine for structured and semi-structured streaming and batch data. Machine learning platform with built-in algorithms, data preparation capabilities, and model evaluation and management via SQL or Python.

Primary database model

Relational DBMS

Column oriented

Secondary database models

Spatial DBMS
Time Series DBMS

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

Score	0.51
Rank	#253	Overall
	#116	Relational DBMS

Score	0.17
Rank	#322	Overall
	#144	Relational DBMS

Score	9.96
Rank	#42	Overall
	#26	Relational DBMS

Website

www.kinetica.com

www.valentina-db.net

www.vertica.com

Technical documentation

docs.kinetica.com

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

vertica.com/documentation

Developer

Kinetica

Paradigma Software

OpenText

previously Micro Focus and Hewlett Packard

Initial release

2012

1999

2005

Current release

7.1, August 2021

5.7.5

12.0.3, January 2023

License

Commercial or Open Source

commercial

Limited community edition free

Cloud-based only

Only available as a cloud service

on-premises, all major clouds - Amazon AWS, Microsoft Azure, Google Cloud Platform and containers

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

Linux

Data scheme

yes

Yes, but also semi-structure/unstructured data storage, and complex hierarchical data (like Parquet) stored and/or queried.

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

No Indexes Required. Different internal optimization strategy, but same functionality included.

SQL

Support of SQL

SQL-like DML and DDL statements

yes

Full 1999 standard plus machine learning, time series and geospatial. Over 650 functions.

APIs and other access methods

JDBC
ODBC
RESTful HTTP API

ODBC

ADO.NET
JDBC
Kafka Connector
ODBC
RESTful HTTP API
Spark Connector
vSQL

character-based, interactive, front-end utility

Supported programming languages

C++
Java
JavaScript (Node.js)
Python

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

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

Server-side scripts

Stored procedures

user defined functions

yes

yes, PostgreSQL PL/pgSQL, with minor differences

Triggers

yes

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

yes

yes, called Custom Alerts

Partitioning methods

Methods for storing different data on different nodes

Sharding

horizontal partitioning, hierarchical partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

Multi-source replication

One, or more copies of data replicated across nodes, or object-store used for repository.

MapReduce

Offers an API for user-defined Map/Reduce methods

Bi-directional Spark integration

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

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

User concepts

Access control

Access rights for users and roles on table level

fine grained access rights according to SQL-standard

fine grained access rights according to SQL-standard; supports Kerberos, LDAP, Ident and hash

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More resources

Recent citations in the news

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

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

Kinetica Launches Generative AI Solution for Real-Time Inferencing Powered by NVIDIA AI Enterprise
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Kinetica Delivers Real-Time Vector Similarity Search
21 March 2024, insideainews.com

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15 October 2020, NVIDIA Blog

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A Look at Valentina
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8 July 2024, Datanami

Why HPE Vertica 8 is the best fit for businesses to create an analytics-driven enterprise
16 July 2024, AIM

What’s New in OpenText Vertica
25 July 2023, OpenText

Querying a Vertica data source in Amazon Athena using the Athena Federated Query SDK
11 February 2021, AWS Blog

Postgres pioneer Michael Stonebraker promises to upend the database once more
26 December 2023, The Register

provided by Google News

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