DBMS > AlaSQL vs. ClickHouse vs. Cubrid vs. Dragonfly

System Properties Comparison AlaSQL vs. ClickHouse vs. Cubrid vs. Dragonfly

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Editorial information provided by DB-Engines

Name

Description

JavaScript DBMS library

A high-performance, column-oriented SQL DBMS for online analytical processing (OLAP) that uses all available system resources to their full potential to process each analytical query as fast as possible. It is available as both an open-source software and a cloud offering.

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

A drop-in Redis replacement that scales vertically to support millions of operations per second and terabyte sized workloads, all on a single instance

Primary database model

Document store
Relational DBMS

Relational DBMS

Key-value store

Secondary database models

Time Series DBMS

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

Score	0.42
Rank	#264	Overall
	#42	Document stores
	#122	Relational DBMS

Score	15.88
Rank	#37	Overall
	#22	Relational DBMS

Score	0.97
Rank	#189	Overall
	#86	Relational DBMS

Score	0.44
Rank	#255	Overall
	#38	Key-value stores

Website

alasql.org

clickhouse.com

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

github.com/dragonflydb/dragonfly
www.dragonflydb.io

Technical documentation

github.com/AlaSQL/alasql

clickhouse.com/docs

cubrid.org/manuals

www.dragonflydb.io/docs

Developer

Andrey Gershun & Mathias R. Wulff

Clickhouse Inc.

CUBRID Corporation, CUBRID Foundation

DragonflyDB team and community contributors

Initial release

2014

2016

2008

2023

Current release

v24.6.2.17-stable, July 2024

11.0, January 2021

1.0, March 2023

License

Commercial or Open Source

Open Source

MIT-License

Open Source

Apache 2.0

Open Source

Apache Version 2.0

Open Source

BSL 1.1

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.

DoubleCloud: Fully managed ClickHouse alongside best-in-class managed open-source services to build analytics at scale.
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Implementation language

JavaScript

C++

C, C++, Java

C++

Server operating systems

server-less, requires a JavaScript environment (browser, Node.js)

FreeBSD
Linux
macOS

Linux
Windows

Linux

Data scheme

schema-free

yes

scheme-free

Typing

predefined data types such as float or date

yes

strings, hashes, lists, sets, sorted sets, bit arrays

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

Close to SQL99, but no user access control, stored procedures and host language bindings.

Close to ANSI SQL (SQL/JSON + extensions)

yes

APIs and other access methods

JavaScript API

gRPC
HTTP REST
JDBC
MySQL wire protocol
ODBC
PostgreSQL wire protocol
Proprietary protocol

ADO.NET
JDBC
ODBC
OLE DB

Proprietary protocol

RESP - REdis Serialization Protocol

Supported programming languages

JavaScript

3rd party library
C++
Elixir

3rd party library
Go

3rd party library
Java

3rd party library
JavaScript (Node.js)

3rd party library
Kotlin

3rd party library
Nim

3rd party library
Perl

3rd party library
PHP

3rd party library
Python

3rd party library
R

3rd party library
Ruby

3rd party library
Rust
Scala

3rd party library

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

C
C#
C++
Clojure
D
Dart
Elixir
Erlang
Go
Haskell
Java
JavaScript (Node.js)
Lisp
Lua
Objective-C
Perl
PHP
Python
R
Ruby
Rust
Scala
Swift
Tcl

Server-side scripts

Stored procedures

yes

Java Stored Procedures

Lua

Triggers

yes

publish/subscribe channels provide some trigger functionality

Partitioning methods

Methods for storing different data on different nodes

none

key based and custom

none

Replication methods

Methods for redundantly storing data on multiple nodes

none

Asynchronous and synchronous physical replication; geographically distributed replicas; support for object storages.

Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

none

Immediate Consistency

Eventual Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

yes

only for local storage and DOM-storage

ACID

Atomic execution of command blocks and scripts

Concurrency

Support for concurrent manipulation of data

yes

yes, strict serializability by the server

Durability

Support for making data persistent

yes

by using IndexedDB, SQL.JS or proprietary FileStorage

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 and roles. Column and row based policies. Quotas and resource limits. Pluggable authentication with LDAP and Kerberos. Password based, X.509 certificate, and SSH key authentication.

fine grained access rights according to SQL-standard

Password-based authentication

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