DBMS > AllegroGraph vs. Amazon DynamoDB vs. JanusGraph vs. OrientDB vs. Vertica

System Properties Comparison AllegroGraph vs. Amazon DynamoDB vs. JanusGraph vs. OrientDB vs. Vertica

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

A Graph DBMS optimized for distributed clusters

It was forked from the latest code base of Titan in January 2017

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

Cloud or off-cloud analytical database and query engine for structured and semi-structured streaming and batch data. Machine learning platform with built-in algorithms, data preparation capabilities, and model evaluation and management via SQL or Python.

Primary database model

Document store

with version 6.5
Graph DBMS
RDF store
Vector DBMS

Document store
Key-value store

Graph DBMS

Document store
Graph DBMS
Key-value store

Relational DBMS

Column oriented

Secondary database models

Spatial DBMS

Spatial DBMS
Time Series 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	74.45
Rank	#17	Overall
	#3	Document stores
	#2	Key-value stores

Score	2.02
Rank	#125	Overall
	#12	Graph DBMS

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

Score	10.06
Rank	#42	Overall
	#26	Relational DBMS

Website

allegrograph.com

aws.amazon.com/dynamodb

janusgraph.org

orientdb.org

www.vertica.com

Technical documentation

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

docs.aws.amazon.com/dynamodb

docs.janusgraph.org

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

vertica.com/documentation

Developer

Franz Inc.

Amazon

Linux Foundation; originally developed as Titan by Aurelius

OrientDB LTD; CallidusCloud; SAP

OpenText

previously Micro Focus and Hewlett Packard

Initial release

2004

2012

2017

2010

2005

Current release

8.0, December 2023

0.6.3, February 2023

3.2.29, March 2024

12.0.3, January 2023

License

Commercial or Open Source

commercial

Limited community edition free

commercial

free tier for a limited amount of database operations

Open Source

Apache 2.0

Open Source

Apache version 2

commercial

Limited community edition free

Cloud-based only

Only available as a cloud service

yes

on-premises, all major clouds - Amazon AWS, Microsoft Azure, Google Cloud Platform and containers

DBaaS offerings (sponsored links)

Database as a Service

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

Implementation language

Java

C++

Server operating systems

Linux
OS X
Windows

hosted

Linux
OS X
Unix
Windows

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

Linux

Data scheme

yes

RDF schemas

schema-free

yes

schema-free

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

Yes, but also semi-structure/unstructured data storage, and complex hierarchical data (like Parquet) stored and/or queried.

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

No Indexes Required. Different internal optimization strategy, but same functionality included.

SQL

Support of SQL

SPARQL is used as query language

SQL-like query language, no joins

Full 1999 standard plus machine learning, time series and geospatial. Over 650 functions.

APIs and other access methods

RESTful HTTP API
SPARQL

RESTful HTTP API

Java API
TinkerPop Blueprints
TinkerPop Frames
TinkerPop Gremlin
TinkerPop Rexster

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

ADO.NET
JDBC
Kafka Connector
ODBC
RESTful HTTP API
Spark Connector
vSQL

character-based, interactive, front-end utility

Supported programming languages

C#
Clojure
Java
Lisp
Perl
Python
Ruby
Scala

.Net
ColdFusion
Erlang
Groovy
Java
JavaScript
Perl
PHP
Python
Ruby

Clojure
Java
Python

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

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

Server-side scripts

Stored procedures

yes

JavaScript or Common Lisp

yes

Java, Javascript

yes, PostgreSQL PL/pgSQL, with minor differences

Triggers

yes

by integration with AWS Lambda

yes

Hooks

yes, called Custom Alerts

Partitioning methods

Methods for storing different data on different nodes

with Federation

Sharding

yes

depending on the used storage backend (e.g. Cassandra, HBase, BerkeleyDB)

Sharding

horizontal partitioning, hierarchical partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication
Source-replica replication

yes

Multi-source replication

One, or more copies of data replicated across nodes, or object-store used for repository.

MapReduce

Offers an API for user-defined Map/Reduce methods

may be implemented via Amazon Elastic MapReduce (Amazon EMR)

yes

via Faunus, a graph analytics engine

could be achieved with distributed queries

Bi-directional Spark integration

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

Eventual Consistency
Immediate Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

Relationships in graphs

yes

relationship in graphs

yes

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

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

Supports various storage backends: Cassandra, HBase, Berkeley DB, Akiban, Hazelcast

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)

User authentification and security via Rexster Graph Server

Access rights for users and roles; record level security configurable

fine grained access rights according to SQL-standard; supports Kerberos, LDAP, Ident and hash

More information provided by the system vendor

Specific characteristics

Knowledge Graph Platform Leader FedShard - Designed for Entity-Event Knowledge Graph...
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Deploy-anywhere database for large-scale analytical deployments. Deploy off-cloud,...
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Competitive advantages

AllegroGraph is uniquely suited to support adhoc queries through SPARQL, Prolog and...
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Fast, scalable, and capable of high concurrency. Separation of compute/storage leverages...
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Typical application scenarios

Communication and network analytics, Embedded analytics, Fraud monitoring and Risk...
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Key customers

Abiba Systems, Adform, adMarketplace, AmeriPride, Anritsu, AOL, Avito, Auckland Transport,...
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Licensing and pricing models

Cost-based models and subscription-based models are both available. One license is...
» more

News

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23 January 2024

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