DBMS > CouchDB vs. Kyligence Enterprise vs. MySQL vs. Pinecone

System Properties Comparison CouchDB vs. Kyligence Enterprise vs. MySQL vs. Pinecone

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Editorial information provided by DB-Engines

Name

Description

A native JSON - document store inspired by Lotus Notes, scalable from globally distributed server-clusters down to mobile phones.

A distributed analytics engine for big data, built on top of Apache Kylin

Widely used open source RDBMS

A managed, cloud-native vector database

Primary database model

Document store

Relational DBMS

Key/Value like access via memcached API

Vector DBMS

Secondary database models

Spatial DBMS

using the Geocouch extension

Document store
Spatial DBMS

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

Score	9.30
Rank	#45	Overall
	#7	Document stores

Score	0.40
Rank	#269	Overall
	#124	Relational DBMS

Score	1083.74
Rank	#2	Overall
	#2	Relational DBMS

Score	3.16
Rank	#95	Overall
	#2	Vector DBMS

Website

couchdb.apache.org

kyligence.io/kyligence-enterprise

www.mysql.com

www.pinecone.io

Technical documentation

docs.couchdb.org/en/stable

dev.mysql.com/doc

docs.pinecone.io/docs/overview

Developer

Apache Software Foundation

Apache top-level project, originally developed by Damien Katz, a former Lotus Notes developer

Kyligence, Inc.

Oracle

since 2010, originally MySQL AB, then Sun

Pinecone Systems, Inc

Initial release

2005

2016

1995

2019

Current release

3.3.3, December 2023

8.4.0, April 2024

License

Commercial or Open Source

Open Source

Apache version 2

commercial

Open Source

GPL version 2. Commercial licenses with extended functionallity are available

commercial

Cloud-based only

Only available as a cloud service

yes

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Implementation language

Erlang

Java

C and C++

Server operating systems

Android
BSD
Linux
OS X
Solaris
Windows

Linux

FreeBSD
Linux
OS X
Solaris
Windows

hosted

Data scheme

schema-free

yes

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

via views

yes

SQL

Support of SQL

ANSI SQL for queries (using Apache Calcite)

yes

with proprietary extensions

APIs and other access methods

RESTful HTTP/JSON API

JDBC
ODBC
RESTful HTTP API

ADO.NET
JDBC
ODBC
Proprietary native API

RESTful HTTP API

Supported programming languages

C
C#
ColdFusion
Erlang
Haskell
Java
JavaScript
Lisp
Lua
Objective-C
OCaml
Perl
PHP
PL/SQL
Python
Ruby
Smalltalk

Ada
C
C#
C++
D
Delphi
Eiffel
Erlang
Haskell
Java
JavaScript (Node.js)
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl

Python

Server-side scripts

Stored procedures

View functions in JavaScript

yes

proprietary syntax

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

improved architecture with release 2.0

horizontal partitioning, sharding with MySQL Cluster or MySQL Fabric

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

not for MyISAM storage engine

Transaction concepts

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

atomic operations within a single document possible

ACID

not for MyISAM storage engine

Concurrency

Support for concurrent manipulation of data

yes

strategy: optimistic locking

yes

table locks or row locks depending on storage engine

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

Access rights for users can be defined per database

Users with fine-grained authorization concept

no user groups or roles

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