DBMS > AllegroGraph vs. Couchbase vs. Google Cloud Datastore vs. Realm

System Properties Comparison AllegroGraph vs. Couchbase vs. Google Cloud Datastore vs. Realm

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Editorial information provided by DB-Engines

Name

Description

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

A distributed document store with integrated cache, a powerful search engine, in-built operational and analytical capabilities, and an embedded mobile database

Automatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud Platform

A DBMS built for use on mobile devices that’s a fast, easy to use alternative to SQLite and Core Data

Primary database model

Document store

with version 6.5
Graph DBMS
RDF store
Vector DBMS

Document store

Secondary database models

Spatial DBMS

Key-value store

originating from the former Membase product and supporting the Memcached protocol
Spatial DBMS

using the Geocouch extension
Search engine
Time Series DBMS
Vector 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	16.59
Rank	#36	Overall
	#5	Document stores

Score	4.36
Rank	#72	Overall
	#12	Document stores

Score	7.41
Rank	#52	Overall
	#8	Document stores

Website

allegrograph.com

www.couchbase.com

cloud.google.com/datastore

realm.io

Technical documentation

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

docs.couchbase.com

cloud.google.com/datastore/docs

realm.io/docs

Developer

Franz Inc.

Couchbase, Inc.

Google

Realm, acquired by MongoDB in May 2019

Initial release

2004

2011

2008

2014

Current release

8.0, December 2023

Server: 7.2, June 2023; Mobile: 3.1, March 2022; Couchbase Capella (DBaaS), June 2023

License

Commercial or Open Source

commercial

Limited community edition free

Open Source

Business Source License (BSL 1.1); Commercial licenses also available

commercial

Open Source

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, C++, Go and Erlang

Server operating systems

Linux
OS X
Windows

hosted

Android
Backend: server-less
iOS
Windows

Data scheme

yes

RDF schemas

schema-free

yes

Typing

predefined data types such as float or date

yes

yes, details here

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

SQL

Support of SQL

SPARQL is used as query language

SQL++, extends ANSI SQL to JSON for operational, transactional, and analytic use cases

SQL-like query language (GQL)

APIs and other access methods

RESTful HTTP API
SPARQL

CLI Client
HTTP REST
Kafka Connector
Native language bindings for CRUD, Query, Search and Analytics APIs
Spark Connector
Spring Data

gRPC (using protocol buffers) API
RESTful HTTP/JSON API

Supported programming languages

C#
Clojure
Java
Lisp
Perl
Python
Ruby
Scala

.Net
C
Go
Java
JavaScript

Node.js
Kotlin
PHP
Python
Ruby
Scala

.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby

.Net
Java

with Android only
Objective-C
React Native
Swift

Server-side scripts

Stored procedures

yes

JavaScript or Common Lisp

Functions and timers in JavaScript and UDFs in Java, Python, SQL++

using Google App Engine

runs within the applications so server-side scripts are unnecessary

Triggers

yes

via the TAP protocol

Callbacks using the Google Apps Engine

yes

Change Listeners

Partitioning methods

Methods for storing different data on different nodes

with Federation

Automatic Sharding

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication
Source-replica replication

Multi-source replication

including cross data center replication
Source-replica replication

Multi-source replication using Paxos

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

using Google Cloud Dataflow

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency or Eventual Consistency depending on configuration

Eventual Consistency
Immediate Consistency

selectable on a per-operation basis

Immediate Consistency or Eventual Consistency depending on type of query and configuration

Strong Consistency is default for entity lookups and queries within an Entity Group (but can instead be made eventually consistent). Other queries are always eventual consistent.

Immediate Consistency

Foreign keys

Referential integrity

yes

via ReferenceProperties or Ancestor paths

Transaction concepts

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

ACID

Serializable Isolation within Transactions, Read Committed outside of Transactions

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

Ephemeral buckets

yes

In-Memory realm

User concepts

Access control

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

User and Administrator separation with password-based and LDAP integrated Authentication. Role-base access control.

Access rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)

yes

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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23 May 2024

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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

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