DBMS > AllegroGraph vs. DuckDB vs. FatDB vs. OrientDB vs. Snowflake

System Properties Comparison AllegroGraph vs. DuckDB vs. FatDB vs. OrientDB vs. Snowflake

Editorial information provided by DB-Engines

Name

FatDB/FatCloud has ceased operations as a company with February 2014. FatDB is discontinued and excluded from the ranking.

Description

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

An embeddable, in-process, column-oriented SQL OLAP RDBMS

A .NET NoSQL DBMS that can integrate with and extend SQL Server.

Multi-model DBMS (Document, Graph, Key/Value)

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

Primary database model

Document store

with version 6.5
Graph DBMS
RDF store
Vector DBMS

Relational DBMS

Document store
Key-value store

Document store
Graph DBMS
Key-value store

Relational DBMS

Secondary database models

Spatial DBMS

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	4.63
Rank	#69	Overall
	#37	Relational DBMS

Score	3.25
Rank	#89	Overall
	#16	Document stores
	#6	Graph DBMS
	#13	Key-value stores

Score	130.36
Rank	#8	Overall
	#5	Relational DBMS

Website

Technical documentation

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

duckdb.org/docs

www.orientdb.com/docs/last/index.html

docs.snowflake.net/manuals/index.html

Developer

Franz Inc.

FatCloud

OrientDB LTD; CallidusCloud; SAP

Snowflake Computing Inc.

Initial release

2004

2018

2012

2010

2014

Current release

8.0, December 2023

1.0.0, June 2024

3.2.29, March 2024

License

Commercial or Open Source

commercial

Limited community edition free

Open Source

MIT License

commercial

Open Source

Apache version 2

commercial

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

C++

Java

Server operating systems

Linux
OS X
Windows

server-less

Windows

All OS with a Java JDK (>= JDK 6)

hosted

Data scheme

yes

RDF schemas

yes

schema-free

Schema can be enforced for whole record ("schema-full") or for some fields only ("schema-hybrid")

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

Secondary indexes

yes

SQL

Support of SQL

SPARQL is used as query language

yes

Via inetgration in SQL Server

SQL-like query language, no joins

yes

APIs and other access methods

RESTful HTTP API
SPARQL

Arrow Database Connectivity (ADBC)
CLI Client
JDBC
ODBC

.NET Client API
LINQ
RESTful HTTP API
RPC
Windows WCF Bindings

Tinkerpop technology stack with Blueprints, Gremlin, Pipes
Java API
RESTful HTTP/JSON API

CLI Client
JDBC
ODBC

Supported programming languages

C#
Clojure
Java
Lisp
Perl
Python
Ruby
Scala

C
C#

3rd party driver
C++
Crystal

3rd party driver
Go

3rd party driver
Java
Lisp

3rd party driver
Python
R
Ruby

3rd party driver
Rust
Swift
Zig

3rd party driver

.Net
C
C#
C++
Clojure
Java
JavaScript
JavaScript (Node.js)
PHP
Python
Ruby
Scala

JavaScript (Node.js)
Python

Server-side scripts

Stored procedures

yes

JavaScript or Common Lisp

yes

via applications

Java, Javascript

user defined functions

Triggers

yes

via applications

Hooks

similar concept for controling cloud resources

Partitioning methods

Methods for storing different data on different nodes

with Federation

none

Sharding

yes

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication
Source-replica replication

none

selectable replication factor

Multi-source replication

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

could be achieved with distributed queries

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency or Eventual Consistency depending on configuration

Immediate Consistency

Eventual Consistency
Immediate Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

relationship in graphs

yes

Transaction concepts

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

ACID

Concurrency

Support for concurrent manipulation of data

yes

yes, multi-version concurrency control (MVCC)

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

Can implement custom security layer via applications

Access rights for users and roles; record level security configurable

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

News

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9 February 2024

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23 January 2024

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