DBMS > 4D vs. AllegroGraph vs. Apache Impala vs. VoltDB

System Properties Comparison 4D vs. AllegroGraph vs. Apache Impala vs. VoltDB

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Editorial information provided by DB-Engines

Name

Description

Application development environment with integrated database management system

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

Analytic DBMS for Hadoop

Distributed In-Memory NewSQL RDBMS

Used for OLTP applications with a high frequency of relatively simple transactions, that can hold all their data in memory

Primary database model

Relational DBMS

Document store

with version 6.5
Graph DBMS
RDF store
Vector DBMS

Relational DBMS

Secondary database models

Spatial DBMS

Document store

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

Score	2.58
Rank	#108	Overall
	#54	Relational DBMS

Score	1.06
Rank	#187	Overall
	#30	Document stores
	#17	Graph DBMS
	#7	RDF stores
	#7	Vector DBMS

Score	13.77
Rank	#40	Overall
	#24	Relational DBMS

Score	1.44
Rank	#158	Overall
	#73	Relational DBMS

Website

Technical documentation

developer.4d.com

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

impala.apache.org/impala-docs.html

docs.voltdb.com

Developer

4D, Inc

Franz Inc.

Apache Software Foundation

Apache top-level project, originally developed by Cloudera

VoltDB Inc.

Initial release

1984

2004

2013

2010

Current release

v20, April 2023

8.0, December 2023

4.1.0, June 2022

11.3, April 2022

License

Commercial or Open Source

commercial

Limited community edition free

Open Source

Apache Version 2

Open Source

AGPL for Community Edition, commercial license for Enterprise, AWS, and Pro Editions

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

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

Implementation language

C++

Java, C++

Server operating systems

OS X
Windows

Linux
OS X
Windows

Linux

Linux
OS X

for development

Data scheme

yes

RDF schemas

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.

yes

bulk load of XML files possible

Secondary indexes

yes

SQL

Support of SQL

yes

close to SQL 92

SPARQL is used as query language

SQL-like DML and DDL statements

yes

only a subset of SQL 99

APIs and other access methods

ODBC
RESTful HTTP API

by using 4D Mobile
SOAP webservices

RESTful HTTP API
SPARQL

JDBC
ODBC

Java API
JDBC
RESTful HTTP/JSON API

Supported programming languages

4D proprietary IDE
PHP

C#
Clojure
Java
Lisp
Perl
Python
Ruby
Scala

All languages supporting JDBC/ODBC

C#
C++
Erlang

not officially supported
Go
Java
JavaScript

Node.js
PHP
Python

Server-side scripts

Stored procedures

yes

JavaScript or Common Lisp

yes

user defined functions and integration of map-reduce

Java

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

none

with Federation

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication

Multi-source replication
Source-replica replication

selectable replication factor

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

query execution via MapReduce

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Immediate Consistency or Eventual Consistency depending on configuration

Eventual Consistency

Foreign keys

Referential integrity

yes

FOREIGN KEY constraints are not supported

Transaction concepts

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

ACID

Transactions are executed single-threaded within stored procedures

Concurrency

Support for concurrent manipulation of data

yes

Data access is serialized by the server

Durability

Support for making data persistent

yes

Snapshots and command logging

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

User concepts

Access control

Users and groups

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

Access rights for users, groups and roles

based on Apache Sentry and Kerberos

Users and roles with access to stored procedures

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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More resources

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