DBMS > AllegroGraph vs. BigObject vs. Cachelot.io vs. GeoSpock vs. VoltDB

System Properties Comparison AllegroGraph vs. BigObject vs. Cachelot.io vs. GeoSpock vs. VoltDB

Editorial information provided by DB-Engines

Name

GeoSpock seems to be discontinued. Therefore it will be excluded from the DB-Engines ranking.

Description

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

Analytic DBMS for real-time computations and queries

In-memory caching system

Spatial and temporal data processing engine for extreme data scale

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

Document store

with version 6.5
Graph DBMS
RDF store
Vector DBMS

Relational DBMS

a hierachical model (tree) can be imposed

Key-value store

Relational DBMS

Secondary database models

Spatial DBMS

Time Series 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	0.13
Rank	#333	Overall
	#147	Relational DBMS

Score	0.00
Rank	#383	Overall
	#60	Key-value stores

Score	1.44
Rank	#158	Overall
	#73	Relational DBMS

Website

geospock.com

Technical documentation

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

docs.bigobject.io

docs.voltdb.com

Developer

Franz Inc.

BigObject, Inc.

GeoSpock

VoltDB Inc.

Initial release

2004

2015

2010

Current release

8.0, December 2023

2.0, September 2019

11.3, April 2022

License

Commercial or Open Source

commercial

Limited community edition free

commercial

free community edition available

Open Source

Simplified BSD License

commercial

Open Source

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

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++

Java, Javascript

Java, C++

Server operating systems

Linux
OS X
Windows

Linux

distributed as a docker-image
OS X

distributed as a docker-image (boot2docker)
Windows

distributed as a docker-image (boot2docker)

FreeBSD
Linux
OS X

hosted

Linux
OS X

for development

Data scheme

yes

RDF schemas

yes

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

temporal, categorical

yes

SQL

Support of SQL

SPARQL is used as query language

SQL-like DML and DDL statements

ANSI SQL for query only (using Presto)

yes

only a subset of SQL 99

APIs and other access methods

RESTful HTTP API
SPARQL

fluentd
ODBC
RESTful HTTP API

Memcached protocol

JDBC

Java API
JDBC
RESTful HTTP/JSON API

Supported programming languages

C#
Clojure
Java
Lisp
Perl
Python
Ruby
Scala

.Net
C
C++
ColdFusion
Erlang
Java
Lisp
Lua
OCaml
OCaml
Perl
PHP
Python
Ruby

C#
C++
Erlang

not officially supported
Go
Java
JavaScript

Node.js
PHP
Python

Server-side scripts

Stored procedures

yes

JavaScript or Common Lisp

Lua

Java

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

with Federation

none

Automatic sharding

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication
Source-replica replication

none

Multi-source replication
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

none

Immediate Consistency

Foreign keys

Referential integrity

yes

automatically between fact table and dimension tables

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

Read/write lock on objects (tables, trees)

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.

yes

User concepts

Access control

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

Access rights for users can be defined per table

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

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17 April 2024

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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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