DBMS > Kinetica vs. NSDb vs. Oracle Rdb vs. SWC-DB

System Properties Comparison Kinetica vs. NSDb vs. Oracle Rdb vs. SWC-DB

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Editorial information provided by DB-Engines

Name

Description

Fully vectorized database across both GPUs and CPUs

Scalable, High-performance Time Series DBMS designed for Real-time Analytics on top of Kubernetes

A high performance, scalable Wide Column DBMS

Primary database model

Secondary database models

Spatial DBMS
Time Series DBMS

Time Series DBMS

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

Score	0.42
Rank	#261	Overall
	#120	Relational DBMS

Score	0.00
Rank	#385	Overall
	#40	Time Series DBMS

Score	1.04
Rank	#184	Overall
	#84	Relational DBMS

Score	0.01
Rank	#378	Overall
	#13	Wide column stores

Website

www.kinetica.com

nsdb.io

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

github.com/kashirin-alex/swc-db
www.swcdb.org

Technical documentation

docs.kinetica.com

nsdb.io/Architecture

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

Developer

Kinetica

Oracle, originally developed by Digital Equipment Corporation (DEC)

Alex Kashirin

Initial release

2012

2017

1984

2020

Current release

7.1, August 2021

7.4.1.1, 2021

0.5, April 2021

License

Commercial or Open Source

commercial

Open Source

Apache Version 2.0

commercial

Open Source

GPL V3

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, Scala

C++

Server operating systems

Linux

Linux
macOS

HP Open VMS

Linux

Data scheme

yes

Flexible Schema (defined schema, partial schema, schema free)

schema-free

Typing

predefined data types such as float or date

yes

yes: int, bigint, decimal, string

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

all fields are automatically indexed

yes

SQL

Support of SQL

SQL-like DML and DDL statements

SQL-like query language

yes

SQL-like query language

APIs and other access methods

JDBC
ODBC
RESTful HTTP API

gRPC
HTTP REST
WebSocket

Proprietary protocol
Thrift

Supported programming languages

C++
Java
JavaScript (Node.js)
Python

Java
Scala

C++

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

Replication methods

Methods for redundantly storing data on multiple nodes

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

Eventual Consistency

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

Using Apache Lucene

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

User concepts

Access control

Access rights for users and roles on table level

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