DBMS > Kinetica vs. VoltDB

System Properties Comparison Kinetica vs. VoltDB

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Editorial information provided by DB-Engines

Name

Description

Fully vectorized database across both GPUs and CPUs

Distributed In-Memory NewSQL RDBMS

Used for OLTP applications with a high frequency of relatively simple transactions, that can hold all their data in memory

Primary database model

Relational DBMS

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

Score	0.59
Rank	#221	Overall
	#105	Relational DBMS

Score	1.58
Rank	#141	Overall
	#69	Relational DBMS

Website

www.kinetica.com

www.voltdb.com

Technical documentation

www.kinetica.com/docs

docs.voltdb.com

Developer

Kinetica

VoltDB Inc.

Initial release

2012

2010

Current release

7.1, August 2021

11.3, April 2022

License

Commercial or Open Source

commercial

Open Source

AGPL for Community Edition, commercial license for Enterprise, AWS, and Pro Editions

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++

Java, C++

Server operating systems

Linux

Linux
OS X

for development

Data scheme

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

yes

only a subset of SQL 99

APIs and other access methods

JDBC
ODBC
RESTful HTTP API

Java API
JDBC
RESTful HTTP/JSON API

Supported programming languages

C++
Java
JavaScript (Node.js)
Python

C#
C++
Erlang

not officially supported
Go
Java
JavaScript

Node.js
PHP
Python

Server-side scripts

Stored procedures

user defined functions

Java

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

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency or Eventual Consistency depending on configuration

Foreign keys

Referential integrity

yes

FOREIGN KEY constraints are not supported

Transaction concepts

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

ACID

Transactions are executed single-threaded within stored procedures

Concurrency

Support for concurrent manipulation of data

yes

Data access is serialized by the server

Durability

Support for making data persistent

yes

Snapshots and command logging

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

User concepts

Access control

Access rights for users and roles on table level

Users and roles with access to stored procedures

More information provided by the system vendor

Specific characteristics

Native and fully vectorized database across both GPUs and CPUs, with memory first...
» more

Competitive advantages

Best in class geospatial and temporal analytics. Lockless architecture provides real-time...
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Typical application scenarios

Any application requiring (1) real time insights, (2) time series analysis (3) geospatial...
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Key customers

Citibank, US Air Force, Softbank, OVO, Telkomsel, USPS, 2 of the top 3 US Telcos,...
» more

Market metrics

The largest IoT deployment in the world, NORAD, runs on Kinetica.
» more

Licensing and pricing models

Always Free Tier in the Cloud, Pay-As-You-Go Consumption Based Pricing, and Portable...
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and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

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More resources

Recent citations in the news

Bank Replaces Hundreds of Spark Streaming Nodes with Kinetica
6 January 2022, Datanami

GPU Database Market Growth, Trends, Forecast and COVID-19 Impacts (2022 - 2027)
22 June 2022, NewsOrigins

Global GPU Database Market 2022 – Key Players, Industry Demand, Overview and Supply Chain Analysis, Forecast 2028 – Designer Women
22 June 2022, Designer Women

Review: Kinetica analyzes billions of rows in real time
29 April 2019, InfoWorld

Preventing the Next 9/11 Goal of NORAD's New Streaming Data Warehouse
30 August 2021, Datanami

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5 July 2022, Designer Women

Database Management Systems (DBMS) Market 2022 Size, Share and Outlook – BMC Software, Oracle, IBM, Broadcom, Couchbase Server – Designer Women
21 June 2022, Designer Women

In-Memory Database Market Size 2022 Analysis by Competitive Vendors in Top Regions and Countries, Revenue, Growth Rate, Development Trends, Threats, Opportunities and Forecast to 2025
6 July 2022, Digital Journal

Global In-Memory Database Market Scope with New Innovations, Regional Trends, Future Investments, Industry Growth Analysis and Demand Forecast by 2022-2029
27 June 2022, Digital Journal

RDBMS Software Market Report 2022 with Countries Data and Market Overview by Size, Share, Trends, Factors and Player and forecast to 2028 – Microsoft, PostgreSQL Global Development Group, VoltDB, ThinkSQL – Indian Defence News
2 July 2022, Indian Defence News

provided by Google News

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