DBMS > Apache Kylin vs. Cubrid vs. etcd vs. Postgres-XL

System Properties Comparison Apache Kylin vs. Cubrid vs. etcd vs. Postgres-XL

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Editorial information provided by DB-Engines

Name

Description

A distributed analytics engine for big data, providing a SQL interface and multi-dimensional analysis (OLAP) and leveraging the Hadoop stack

CUBRID is an open-source SQL-based relational database management system with object extensions for OLTP

A distributed reliable key-value store

Based on PostgreSQL enhanced with MPP and write-scale-out cluster features

Primary database model

Relational DBMS

Key-value store

Relational DBMS

Secondary database models

Document store
Spatial DBMS

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

Score	1.25
Rank	#170	Overall
	#77	Relational DBMS

Score	1.04
Rank	#187	Overall
	#87	Relational DBMS

Score	7.03
Rank	#54	Overall
	#5	Key-value stores

Score	0.53
Rank	#254	Overall
	#117	Relational DBMS

Website

kylin.apache.org

cubrid.com (korean)
cubrid.org (english)

etcd.io
github.com/etcd-io/etcd

www.postgres-xl.org

Technical documentation

kylin.apache.org/docs

cubrid.org/manuals

etcd.io/docs
github.com/etcd-io/etcd/tree/master/Documentation

www.postgres-xl.org/documentation

Developer

Apache Software Foundation, originally contributed from eBay Inc

CUBRID Corporation, CUBRID Foundation

Initial release

2015

2008

2014

since 2012, originally named StormDB

Current release

3.1.0, July 2020

11.0, January 2021

3.4, August 2019

10 R1, October 2018

License

Commercial or Open Source

Open Source

Apache Version 2.0

Open Source

Apache Version 2.0

Open Source

Apache Version 2.0

Open Source

Mozilla public license

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

Java

C, C++, Java

Server operating systems

Linux

Linux
Windows

FreeBSD
Linux
Windows

experimental

Linux
macOS

Data scheme

yes

schema-free

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.

yes

XML type, but no XML query functionality

Secondary indexes

yes

SQL

Support of SQL

ANSI SQL for queries (using Apache Calcite)

yes

distributed, parallel query execution

APIs and other access methods

JDBC
ODBC
RESTful HTTP API

ADO.NET
JDBC
ODBC
OLE DB

gRPC
JSON over HTTP

ADO.NET
JDBC
native C library
ODBC
streaming API for large objects

Supported programming languages

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

.Net
C
C++
Clojure
Erlang
Go
Haskell
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Ruby
Rust
Scala
Tcl

.Net
C
C++
Delphi
Erlang
Java
JavaScript (Node.js)
Perl
PHP
Python
Tcl

Server-side scripts

Stored procedures

Java Stored Procedures

user defined functions

Triggers

yes

yes, watching key changes

yes

Partitioning methods

Methods for storing different data on different nodes

none

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

Using Raft consensus algorithm to ensure data replication with strong consistency among multiple replicas.

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

MVCC

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.

User concepts

Access control

fine grained access rights according to SQL-standard

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