DBMS > Kdb vs. Newts vs. Pinecone

System Properties Comparison Kdb vs. Newts vs. Pinecone

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Editorial information provided by DB-Engines

Name

Description

High performance Time Series DBMS

Time Series DBMS based on Cassandra

A managed, cloud-native vector database

Primary database model

Time Series DBMS
Vector DBMS

Time Series DBMS

Vector DBMS

Secondary database models

Relational DBMS

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

Score	7.73
Rank	#45	Overall
	#2	Time Series DBMS
	#1	Vector DBMS

Score	0.00
Rank	#385	Overall
	#40	Time Series DBMS

Score	3.02
Rank	#87	Overall
	#3	Vector DBMS

Website

kx.com

opennms.github.io/newts

www.pinecone.io

Technical documentation

code.kx.com

github.com/OpenNMS/newts/wiki

docs.pinecone.io/docs/overview

Developer

Kx Systems, a division of First Derivatives plc

OpenNMS Group

Pinecone Systems, Inc

Initial release

2000

kdb was released 2000, kdb+ in 2003

2014

2019

Current release

3.6, May 2018

License

Commercial or Open Source

commercial

free 32-bit version

Open Source

Apache 2.0

commercial

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

Java

Server operating systems

Linux
OS X
Solaris
Windows

Linux
OS X
Windows

hosted

Data scheme

yes

schema-free

Typing

predefined data types such as float or date

yes

String, Number, Boolean

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

table attribute 'grouped'

SQL

Support of SQL

SQL-like query language (q)

APIs and other access methods

HTTP API
JDBC
Jupyter
Kafka
ODBC
WebSocket

HTTP REST
Java API

RESTful HTTP API

Supported programming languages

C
C#
C++
Go
J
Java
JavaScript
Lua
MatLab
Perl
PHP
Python
R
Scala

Java

Python

Server-side scripts

Stored procedures

user defined functions

Triggers

yes

with views

Partitioning methods

Methods for storing different data on different nodes

horizontal partitioning

Sharding

based on Cassandra

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

selectable replication factor

based on Cassandra

MapReduce

Offers an API for user-defined Map/Reduce methods

similar paradigm used for internal processing

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

based on Cassandra
Immediate Consistency

based on Cassandra

Foreign keys

Referential integrity

yes

Transaction concepts

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

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

User concepts

Access control

rights management via user accounts

More information provided by the system vendor

Specific characteristics

Integrated columnar database & programming system for streaming, real time and historical...
» more

Competitive advantages

provides seamless scalability; runs on industry standard server platforms; is top-ranked...
» more

Typical application scenarios

tick database streaming sensor data massive intelligence applications oil and gas...
» more

Key customers

Goldman Sachs Morgan Stanley Merrill Lynch J.P. Morgan Deutsche Bank IEX Securities...
» more

Market metrics

kdb+ performance and reliability proven by our customers in critical infrastructure...
» more

Licensing and pricing models

upon request
» more

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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

DB-Engines blog posts

Vector databases
2 June 2023, Matthias Gelbmann

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