DBMS > AgensGraph vs. AllegroGraph vs. ClickHouse vs. Kyligence Enterprise

System Properties Comparison AgensGraph vs. AllegroGraph vs. ClickHouse vs. Kyligence Enterprise

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Editorial information provided by DB-Engines

Name

Description

Multi-model database supporting relational and graph data models and built upon PostgreSQL

High performance, persistent RDF store with additional support for Graph DBMS

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.

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

Primary database model

Graph DBMS
Relational DBMS

Document store

with version 6.5
Graph DBMS
RDF store
Vector DBMS

Relational DBMS

Secondary database models

Spatial DBMS

Time Series DBMS

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

Score	0.17
Rank	#320	Overall
	#29	Graph DBMS
	#143	Relational DBMS

Score	0.84
Rank	#204	Overall
	#35	Document stores
	#18	Graph DBMS
	#7	RDF stores
	#10	Vector DBMS

Score	15.88
Rank	#37	Overall
	#22	Relational DBMS

Score	0.44
Rank	#259	Overall
	#118	Relational DBMS

Website

bitnine.net/agensgraph

allegrograph.com

clickhouse.com

kyligence.io/kyligence-enterprise

Technical documentation

bitnine.net/documentation

franz.com/agraph/support/documentation/current/agraph-introduction.html

clickhouse.com/docs

Developer

Bitnine Global Inc.

Franz Inc.

Clickhouse Inc.

Kyligence, Inc.

Initial release

2016

2004

2016

Current release

2.1, December 2018

8.0, December 2023

v24.6.2.17-stable, July 2024

License

Commercial or Open Source

Open Source

Apache License 2.0

commercial

Limited community edition free

Open Source

Apache 2.0

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.

Implementation language

C++

Java

Server operating systems

Linux
OS X
Windows

FreeBSD
Linux
macOS

Linux

Data scheme

depending on used data model

yes

RDF schemas

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.

bulk load of XML files possible

Secondary indexes

yes

SQL

Support of SQL

yes

SPARQL is used as query language

Close to ANSI SQL (SQL/JSON + extensions)

ANSI SQL for queries (using Apache Calcite)

APIs and other access methods

Cypher Query Language
JDBC

RESTful HTTP API
SPARQL

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

JDBC
ODBC
RESTful HTTP API

Supported programming languages

C
Java
JavaScript
Python

C#
Clojure
Java
Lisp
Perl
Python
Ruby
Scala

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

Server-side scripts

Stored procedures

yes

JavaScript or Common Lisp

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

no, but can be realized using table inheritance

with Federation

key based and custom

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

Multi-source replication
Source-replica replication

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

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Immediate Consistency or Eventual Consistency depending on configuration

Immediate Consistency

Foreign keys

Referential integrity

yes

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

In-memory capabilities

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

yes

User concepts

Access control

fine grained access rights according to SQL-standard

Users with fine-grained authorization concept, user roles and pluggable authentication

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.

More information provided by the system vendor

News

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16 September 2024

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10 September 2024

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Awesome AI Companies – Franz Inc.
17 July 2024

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