DBMS > AllegroGraph vs. Citus vs. HugeGraph vs. Snowflake vs. VictoriaMetrics

System Properties Comparison AllegroGraph vs. Citus vs. HugeGraph vs. Snowflake vs. VictoriaMetrics

Editorial information provided by DB-Engines

Name

Description

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

Scalable hybrid operational and analytics RDBMS for big data use cases based on PostgreSQL

A fast-speed and highly-scalable Graph DBMS

Cloud-based data warehousing service for structured and semi-structured data

A fast, cost-effective and scalable Time Series DBMS and monitoring solution

Primary database model

Document store

with version 6.5
Graph DBMS
RDF store
Vector DBMS

Secondary database models

Spatial DBMS

Document store

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

Score	1.13
Rank	#179	Overall
	#30	Document stores
	#17	Graph DBMS
	#7	RDF stores
	#7	Vector DBMS

Score	2.15
Rank	#117	Overall
	#56	Relational DBMS

Score	0.17
Rank	#335	Overall
	#31	Graph DBMS

Score	130.36
Rank	#8	Overall
	#5	Relational DBMS

Score	1.23
Rank	#172	Overall
	#15	Time Series DBMS

Website

allegrograph.com

www.citusdata.com

github.com/hugegraph
hugegraph.apache.org

www.snowflake.com

victoriametrics.com

Technical documentation

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

docs.citusdata.com

hugegraph.apache.org/docs

docs.snowflake.net/manuals/index.html

docs.victoriametrics.com
github.com/VictoriaMetrics/VictoriaMetrics/wiki

Developer

Franz Inc.

Baidu

Snowflake Computing Inc.

VictoriaMetrics

Initial release

2004

2010

2018

2014

2018

Current release

8.0, December 2023

8.1, December 2018

0.9

v1.91, May 2023

License

Commercial or Open Source

commercial

Limited community edition free

Open Source

AGPL, commercial license also available

Open Source

Apache Version 2.0

commercial

Open Source

Apache Version 2.0

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

Java

Server operating systems

Linux
OS X
Windows

Linux

Linux
macOS
Unix

hosted

FreeBSD
Linux
macOS
OpenBSD

Data scheme

yes

RDF schemas

yes

support of semi-structured data formats (JSON, XML, Avro)

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

yes

specific XML type available, but no XML query functionality

yes

Secondary indexes

yes

also supports composite index and range index

SQL

Support of SQL

SPARQL is used as query language

yes

standard, with numerous extensions

yes

APIs and other access methods

RESTful HTTP API
SPARQL

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

Java API
RESTful HTTP API
TinkerPop Gremlin

CLI Client
JDBC
ODBC

Graphite protocol
InfluxDB Line Protocol
OpenTSDB
Prometheus Query API
Prometheus Remote Read/Write

Supported programming languages

C#
Clojure
Java
Lisp
Perl
Python
Ruby
Scala

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

Groovy
Java
Python

JavaScript (Node.js)
Python

Server-side scripts

Stored procedures

yes

JavaScript or Common Lisp

user defined functions

realized in proprietary language PL/pgSQL or with common languages like Perl, Python, Tcl etc.

asynchronous Gremlin script jobs

user defined functions

Triggers

yes

similar concept for controling cloud resources

Partitioning methods

Methods for storing different data on different nodes

with Federation

Sharding

yes

depending on used storage backend, e.g. Cassandra and HBase

yes

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication
Source-replica replication

Source-replica replication

other methods possible by using 3rd party extensions

yes

depending on used storage backend, e.g. Cassandra and HBase

yes

Synchronous replication

MapReduce

Offers an API for user-defined Map/Reduce methods

via hugegraph-spark

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency or Eventual Consistency depending on configuration

Immediate Consistency

Eventual Consistency

Immediate Consistency

Eventual Consistency

Foreign keys

Referential integrity

yes

edges in graph

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

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

fine grained access rights according to SQL-standard

Users, roles and permissions

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

More information provided by the system vendor

Specific characteristics

Knowledge Graph Platform Leader FedShard - Designed for Entity-Event Knowledge Graph...
» more

Competitive advantages

AllegroGraph is uniquely suited to support adhoc queries through SPARQL, Prolog and...
» more

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23 January 2024

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