DBMS > AllegroGraph vs. Apache Phoenix vs. Riak TS vs. VelocityDB

System Properties Comparison AllegroGraph vs. Apache Phoenix vs. Riak TS vs. VelocityDB

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Editorial information provided by DB-Engines

Name

Description

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

A scale-out RDBMS with evolutionary schema built on Apache HBase

Riak TS is a distributed NoSQL database optimized for time series data and based on Riak KV

A .NET Object Database that can be embedded/distributed and extended to a graph data model (VelocityGraph)

Primary database model

Document store

with version 6.5
Graph DBMS
RDF store
Vector DBMS

Relational DBMS

Time Series DBMS

Graph DBMS
Object oriented DBMS

Secondary database models

Spatial DBMS

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

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

Score	1.97
Rank	#126	Overall
	#59	Relational DBMS

Score	0.20
Rank	#319	Overall
	#27	Time Series DBMS

Score	0.05
Rank	#358	Overall
	#36	Graph DBMS
	#16	Object oriented DBMS

Website

allegrograph.com

phoenix.apache.org

velocitydb.com

Technical documentation

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

phoenix.apache.org

www.tiot.jp/riak-docs/riak/ts/latest

velocitydb.com/UserGuide

Developer

Franz Inc.

Apache Software Foundation

Open Source, formerly Basho Technologies

VelocityDB Inc

Initial release

2004

2014

2015

2011

Current release

8.0, December 2023

5.0-HBase2, July 2018 and 4.15-HBase1, December 2019

3.0.0, September 2022

7.x

License

Commercial or Open Source

commercial

Limited community edition free

Open Source

Apache Version 2.0

Open Source

commercial

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

Java

Erlang

Server operating systems

Linux
OS X
Windows

Linux
Unix
Windows

Linux
OS X

Any that supports .NET

Data scheme

yes

RDF schemas

yes

late-bound, schema-on-read capabilities

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

Secondary indexes

yes

restricted

yes

SQL

Support of SQL

SPARQL is used as query language

yes

yes, limited

APIs and other access methods

RESTful HTTP API
SPARQL

JDBC

HTTP API
Native Erlang Interface

.Net

Supported programming languages

C#
Clojure
Java
Lisp
Perl
Python
Ruby
Scala

C
C#
C++
Go
Groovy
Java
PHP
Python
Scala

unofficial client library
C#
C++

unofficial client library
Clojure

unofficial client library
Dart

unofficial client library
Erlang
Go

unofficial client library
Groovy

unofficial client library
Haskell

unofficial client library
Java
JavaScript

unofficial client library
Lisp

unofficial client library
Perl

unofficial client library
PHP
Python
Ruby
Scala

unofficial client library
Smalltalk

unofficial client library

.Net

Server-side scripts

Stored procedures

yes

JavaScript or Common Lisp

user defined functions

Erlang

Triggers

yes

pre-commit hooks and post-commit hooks

Callbacks are triggered when data changes

Partitioning methods

Methods for storing different data on different nodes

with Federation

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication
Source-replica replication

selectable replication factor

MapReduce

Offers an API for user-defined Map/Reduce methods

Hadoop integration

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency or Eventual Consistency depending on configuration

Immediate Consistency or Eventual Consistency

Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

links between datasets can be stored

Transaction concepts

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

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.

yes

User concepts

Access control

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

Access Control Lists (using HBase ACL) for RBAC, integration with Apache Ranger for RBAC & ABAC, multi-tenancy

Based on Windows 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

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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