DBMS > AllegroGraph vs. Datomic vs. Microsoft Azure AI Search vs. MongoDB vs. OrientDB

System Properties Comparison AllegroGraph vs. Datomic vs. Microsoft Azure AI Search vs. MongoDB vs. OrientDB

Editorial information provided by DB-Engines

Name

Description

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

Datomic builds on immutable values, supports point-in-time queries and uses 3rd party systems for durability

Search-as-a-service for web and mobile app development

One of the most popular document stores available both as a fully managed cloud service and for deployment on self-managed infrastructure

Multi-model DBMS (Document, Graph, Key/Value)

Primary database model

Document store

with version 6.5
Graph DBMS
RDF store
Vector DBMS

Relational DBMS

Search engine

Document store

Document store
Graph DBMS
Key-value store

Secondary database models

Spatial DBMS

Vector DBMS

Spatial DBMS
Search engine

integrated Lucene index, currently in MongoDB Atlas only.
Time Series DBMS

Time Series Collections introduced in Release 5.0
Vector DBMS

currently available in the MongoDB Atlas cloud service only

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	1.59
Rank	#150	Overall
	#69	Relational DBMS

Score	5.59
Rank	#63	Overall
	#7	Search engines

Score	421.65
Rank	#5	Overall
	#1	Document stores

Score	3.19
Rank	#93	Overall
	#16	Document stores
	#7	Graph DBMS
	#14	Key-value stores

Website

allegrograph.com

www.datomic.com

azure.microsoft.com/en-us/services/search

www.mongodb.com

orientdb.org

Technical documentation

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

docs.datomic.com

learn.microsoft.com/en-us/azure/search

www.mongodb.com/docs/manual

www.orientdb.com/docs/last/index.html

Developer

Franz Inc.

Cognitect

Microsoft

MongoDB, Inc

OrientDB LTD; CallidusCloud; SAP

Initial release

2004

2012

2015

2009

2010

Current release

8.0, December 2023

1.0.6735, June 2023

6.0.7, June 2023

3.2.29, March 2024

License

Commercial or Open Source

commercial

Limited community edition free

commercial

limited edition free

commercial

Open Source

MongoDB Inc.'s Server Side Public License v1. Prior versions were published under GNU AGPL v3.0. Commercial licenses are also available.

Open Source

Apache version 2

Cloud-based only

Only available as a cloud service

yes

MongoDB available as DBaaS (MongoDB Atlas)

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

Java, Clojure

C++

Java

Server operating systems

Linux
OS X
Windows

All OS with a Java VM

hosted

Linux
OS X
Solaris
Windows

All OS with a Java JDK (>= JDK 6)

Data scheme

yes

RDF schemas

yes

schema-free

Although schema-free, documents of the same collection often follow the same structure. Optionally impose all or part of a schema by defining a JSON schema.

schema-free

Schema can be enforced for whole record ("schema-full") or for some fields only ("schema-hybrid")

Typing

predefined data types such as float or date

yes

string, integer, double, decimal, boolean, date, object_id, geospatial

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

Read-only SQL queries via the MongoDB Atlas SQL Interface

SQL-like query language, no joins

APIs and other access methods

RESTful HTTP API
SPARQL

RESTful HTTP API

GraphQL
HTTP REST
Prisma
proprietary protocol using JSON

Tinkerpop technology stack with Blueprints, Gremlin, Pipes
Java API
RESTful HTTP/JSON API

Supported programming languages

C#
Clojure
Java
Lisp
Perl
Python
Ruby
Scala

Clojure
Java

C#
Java
JavaScript
Python

Actionscript

unofficial driver
C
C#
C++
Clojure

unofficial driver
ColdFusion

unofficial driver
D

unofficial driver
Dart

unofficial driver
Delphi

unofficial driver
Erlang
Go
Groovy

unofficial driver
Haskell
Java
JavaScript
Kotlin
Lisp

unofficial driver
Lua

unofficial driver
MatLab

unofficial driver
Perl
PHP
PowerShell

unofficial driver
Prolog

unofficial driver
Python
R

unofficial driver
Ruby
Rust
Scala
Smalltalk

unofficial driver
Swift

.Net
C
C#
C++
Clojure
Java
JavaScript
JavaScript (Node.js)
PHP
Python
Ruby
Scala

Server-side scripts

Stored procedures

yes

JavaScript or Common Lisp

yes

Transaction Functions

JavaScript

Java, Javascript

Triggers

yes

By using transaction functions

yes

in MongoDB Atlas only

Hooks

Partitioning methods

Methods for storing different data on different nodes

with Federation

none

But extensive use of caching in the application peers

Sharding

Implicit feature of the cloud service

Sharding

Partitioned by hashed, ranged, or zoned sharding keys. Live resharding allows users to change their shard keys as an online operation with zero downtime.

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication
Source-replica replication

none

But extensive use of caching in the application peers

yes

Implicit feature of the cloud service

Multi-Source deployments with MongoDB Atlas Global Clusters
Source-replica replication

Multi-source replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

could be achieved with distributed queries

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency or Eventual Consistency depending on configuration

Immediate Consistency

Eventual Consistency

can be individually decided for each read operation
Immediate Consistency

default behaviour

Foreign keys

Referential integrity

typically not used, however similar functionality with DBRef possible

yes

relationship in graphs

Transaction concepts

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

ACID

Multi-document ACID Transactions with snapshot isolation

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

using external storage systems (e.g. Cassandra, DynamoDB, PostgreSQL, Couchbase and others)

yes

optional, enabled by default

yes

In-memory capabilities

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

yes

recommended only for testing and development

yes

In-memory storage engine introduced with MongoDB version 3.2

User concepts

Access control

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

yes

using Azure authentication

Access rights for users and roles

Access rights for users and roles; record level security configurable

More information provided by the system vendor

Specific characteristics

Knowledge Graph Platform Leader FedShard - Designed for Entity-Event Knowledge Graph...
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MongoDB provides an integrated suite of cloud database and data services to accelerate...
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Competitive advantages

AllegroGraph is uniquely suited to support adhoc queries through SPARQL, Prolog and...
» more

Built around the flexible document data model and unified API, MongoDB is a developer...
» more

Typical application scenarios

AI-enriched intelligent apps (Continental, Telefonica, Iron Mountain) Internet of...
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Key customers

ADP, Adobe, Amadeus, AstraZeneca, Auto Trader, Barclays, BBVA, Bosch, Cisco, CERN,...
» more

Market metrics

Hundreds of millions downloads, over 150,000+ Atlas clusters provisioned every month...
» more

Licensing and pricing models

MongoDB database server: Server-Side Public License (SSPL) . Commercial licenses...
» more

News

How a Neuro-Symbolic AI Approach Can Improve Trust in AI Apps
23 May 2024

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

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and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.