DBMS > AllegroGraph vs. Amazon Neptune vs. Google BigQuery vs. LeanXcale vs. OpenEdge

System Properties Comparison AllegroGraph vs. Amazon Neptune vs. Google BigQuery vs. LeanXcale vs. OpenEdge

Editorial information provided by DB-Engines

Name

Description

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

Fast, reliable graph database built for the cloud

Large scale data warehouse service with append-only tables

A highly scalable full ACID SQL database with fast NoSQL data ingestion and GIS capabilities

Application development environment with integrated database management system

Primary database model

Document store

with version 6.5
Graph DBMS
RDF store
Vector DBMS

Graph DBMS
RDF store

Relational DBMS

Key-value store
Relational DBMS

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
	#8	Vector DBMS

Score	2.29
Rank	#113	Overall
	#9	Graph DBMS
	#5	RDF stores

Score	58.10
Rank	#19	Overall
	#13	Relational DBMS

Score	0.36
Rank	#280	Overall
	#40	Key-value stores
	#129	Relational DBMS

Score	3.45
Rank	#85	Overall
	#46	Relational DBMS

Website

allegrograph.com

aws.amazon.com/neptune

cloud.google.com/bigquery

www.leanxcale.com

www.progress.com/openedge

Technical documentation

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

aws.amazon.com/neptune/developer-resources

cloud.google.com/bigquery/docs

documentation.progress.com/output/ua/OpenEdge_latest

Developer

Franz Inc.

Amazon

Google

LeanXcale

Progress Software Corporation

Initial release

2004

2017

2010

2015

1984

Current release

8.0, December 2023

OpenEdge 12.2, March 2020

License

Commercial or Open Source

commercial

Limited community edition free

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.

Server operating systems

Linux
OS X
Windows

hosted

AIX
HP-UX
Linux
Solaris
Windows

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

yes

through Apache Derby

yes

close to SQL 92

APIs and other access methods

RESTful HTTP API
SPARQL

OpenCypher
RDF 1.1 / SPARQL 1.1
TinkerPop Gremlin

RESTful HTTP/JSON API

JDBC
Kafka Connector
ODBC
proprietary key/value interface
Spark Connector

JDBC
ODBC

Supported programming languages

C#
Clojure
Java
Lisp
Perl
Python
Ruby
Scala

C#
Go
Java
JavaScript
PHP
Python
Ruby
Scala

.Net
Java
JavaScript
Objective-C
PHP
Python
Ruby

C
Java
Scala

Progress proprietary ABL (Advanced Business Language)

Server-side scripts

Stored procedures

yes

JavaScript or Common Lisp

user defined functions

in JavaScript

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

with Federation

none

horizontal partitioning

since Version 11.4

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication
Source-replica replication

Multi-availability zones high availability, asynchronous replication for up to 15 read replicas within a single region. Global database clusters consists of a primary write DB cluster in one region, and up to five secondary read DB clusters in different regions. Each secondary region can have up to 16 reader instances.

Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency or Eventual Consistency depending on configuration

Immediate Consistency

Foreign keys

Referential integrity

yes

Relationships in graphs

yes

Transaction concepts

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

ACID

Since BigQuery is designed for querying data

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

with encyption-at-rest

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

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

Access privileges (owner, writer, reader) on dataset, table or view level

Google Cloud Identity & Access Management (IAM)

Users and groups

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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