DBMS > ClickHouse vs. Galaxybase vs. Quasardb vs. SQL.JS vs. TigerGraph

System Properties Comparison ClickHouse vs. Galaxybase vs. Quasardb vs. SQL.JS vs. TigerGraph

Editorial information provided by DB-Engines

Name

Description

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.

Scalable, ACID-compliant native distributed parallel graph platform

Distributed, high-performance timeseries database

Port of SQLite to JavaScript

A complete, distributed, parallel graph computing platform supporting web-scale data analytics in real-time

Primary database model

Secondary database models

Time Series DBMS

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

Score	15.55
Rank	#38	Overall
	#23	Relational DBMS

Score	0.07
Rank	#377	Overall
	#40	Graph DBMS

Score	0.21
Rank	#322	Overall
	#29	Time Series DBMS

Score	0.63
Rank	#241	Overall
	#112	Relational DBMS

Score	1.80
Rank	#138	Overall
	#13	Graph DBMS

Website

Technical documentation

clickhouse.com/docs

doc.quasar.ai/master

sql.js.org/documentation/index.html

docs.tigergraph.com

Developer

Clickhouse Inc.

Chuanglin(Createlink) Technology Co., Ltd 浙江创邻科技有限公司

quasardb

Alon Zakai

enhancements implemented by others

Initial release

2016

2017

2009

2012

2017

Current release

v24.4.1.2088-stable, May 2024

Nov 20, November 2021

3.14.1, January 2024

License

Commercial or Open Source

Open Source

Apache 2.0

commercial

Free community edition, Non-profit organizations and non-commercial usage are eligible for free licenses

Open Source

commercial

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.

ClickHouse Cloud: Get the performance you love from open source ClickHouse in a serverless offering that takes care of the details so you can spend more time getting insight out of the fastest database on earth.
DoubleCloud: Fully managed ClickHouse alongside best-in-class managed open-source services to build analytics at scale.
Aiven for Clickhouse: Managed cloud data warehousing with high-speed analytics.

Implementation language

C++

C and Java

C++

JavaScript

C++

Server operating systems

FreeBSD
Linux
macOS

Linux

BSD
Linux
OS X
Windows

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

Linux

Data scheme

yes

Strong typed schema

schema-free

yes

Typing

predefined data types such as float or date

yes

integer and binary

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

with tags

SQL

Support of SQL

Close to ANSI SQL (SQL/JSON + extensions)

SQL-like query language

yes

SQL-92 is not fully supported

SQL-like query language (GSQL)

APIs and other access methods

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

Browser interface
console (shell)
Graph API (Gremlin)
OpenCypher
Proprietary native API

HTTP API

JavaScript API

GSQL (TigerGraph Query Language)
Kafka
RESTful HTTP/JSON API

Supported programming languages

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

Go
Java
Python

.Net
C
C#
C++
Go
Java
JavaScript (Node.js)
PHP
Python
R

JavaScript

C++
Java

Server-side scripts

Stored procedures

yes

user defined procedures and functions

yes

Triggers

Partitioning methods

Methods for storing different data on different nodes

key based and custom

Sharding

consistent hashing

none

Replication methods

Methods for redundantly storing data on multiple nodes

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

Source-replica replication with selectable replication factor

none

MapReduce

Offers an API for user-defined Map/Reduce methods

with Hadoop integration

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

none

Foreign keys

Referential integrity

yes

Relationships in graphs

yes

Relationships in graphs

Transaction concepts

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

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

by using LevelDB

except by serializing a db to a file

yes

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

yes

Transient mode

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.

Role-based access control

Cryptographically strong user authentication and audit trail

Role-based access control

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