DBMS > AllegroGraph vs. Amazon DynamoDB vs. searchxml vs. TigerGraph

System Properties Comparison AllegroGraph vs. Amazon DynamoDB vs. searchxml vs. TigerGraph

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Editorial information provided by DB-Engines

Name

Description

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

Hosted, scalable database service by Amazon with the data stored in Amazons cloud

DBMS for structured and unstructured content wrapped with an application server

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

Primary database model

Document store

with version 6.5
Graph DBMS
RDF store
Vector DBMS

Document store
Key-value store

Native XML DBMS
Search engine

Graph DBMS

Secondary database models

Spatial DBMS

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

Score	1.16
Rank	#179	Overall
	#30	Document stores
	#17	Graph DBMS
	#7	RDF stores
	#7	Vector DBMS

Score	77.57
Rank	#16	Overall
	#2	Document stores
	#2	Key-value stores

Score	0.01
Rank	#386	Overall
	#7	Native XML DBMS
	#24	Search engines

Score	1.83
Rank	#141	Overall
	#13	Graph DBMS

Website

allegrograph.com

aws.amazon.com/dynamodb

www.searchxml.net/category/products

www.tigergraph.com

Technical documentation

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

docs.aws.amazon.com/dynamodb

www.searchxml.net/support/handouts

docs.tigergraph.com

Developer

Franz Inc.

Amazon

informationpartners gmbh

Initial release

2004

2012

2015

2017

Current release

8.0, December 2023

1.0

License

Commercial or Open Source

commercial

Limited community edition free

commercial

free tier for a limited amount of database operations

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++

Server operating systems

Linux
OS X
Windows

hosted

Windows

Linux

Data scheme

yes

RDF schemas

schema-free

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

yes

Secondary indexes

yes

SQL

Support of SQL

SPARQL is used as query language

SQL-like query language (GSQL)

APIs and other access methods

RESTful HTTP API
SPARQL

RESTful HTTP API

RESTful HTTP API
WebDAV
XQuery
XSLT

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

Supported programming languages

C#
Clojure
Java
Lisp
Perl
Python
Ruby
Scala

.Net
ColdFusion
Erlang
Groovy
Java
JavaScript
Perl
PHP
Python
Ruby

C++

most other programming languages supported via APIs

C++
Java

Server-side scripts

Stored procedures

yes

JavaScript or Common Lisp

yes

on the application server

yes

Triggers

yes

by integration with AWS Lambda

Partitioning methods

Methods for storing different data on different nodes

with Federation

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication
Source-replica replication

yes

sychronisation to multiple collections

MapReduce

Offers an API for user-defined Map/Reduce methods

may be implemented via Amazon Elastic MapReduce (Amazon EMR)

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency or Eventual Consistency depending on configuration

Eventual Consistency
Immediate Consistency

can be specified for read operations

Immediate Consistency

Foreign keys

Referential integrity

yes

Relationships in graphs

Transaction concepts

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

ACID

ACID across one or more tables within a single AWS account and region

multiple readers, single writer

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.

User concepts

Access control

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

Access rights for users and roles can be defined via the AWS Identity and Access Management (IAM)

Domain, group and role-based access control at the document level and for application services

Role-based access control

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

Can Neuro-Symbolic AI Solve AI’s Weaknesses?
17 April 2024

100 Companies That Matter in KM – Franz Inc.
3 April 2024

Exploring AllegroGraph v8 – Unleashing the Power of Neuro-Symbolic AI (Recorded Webinar)
9 February 2024

What is Neuro-Symbolic AI?
23 January 2024

Allegro CL v11 – Now Available! – The Neuro-Symbolic AI Programming Platform
8 January 2024

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