DBMS > AllegroGraph vs. Drizzle vs. MongoDB vs. Oracle NoSQL vs. Qdrant

System Properties Comparison AllegroGraph vs. Drizzle vs. MongoDB vs. Oracle NoSQL vs. Qdrant

Editorial information provided by DB-Engines

Name

Drizzle has published its last release in September 2012. The open-source project is discontinued and Drizzle is excluded from the DB-Engines ranking.

Description

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

MySQL fork with a pluggable micro-kernel and with an emphasis of performance over compatibility.

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

A multi-model, scalable, distributed NoSQL database, designed to provide highly reliable, flexible, and available data management across a configurable set of storage nodes

A high-performance vector database with neural network or semantic-based matching

Primary database model

Document store

with version 6.5
Graph DBMS
RDF store
Vector DBMS

Relational DBMS

Document store

Document store
Key-value store
Relational DBMS

Vector DBMS

Secondary database models

Spatial 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	1.13
Rank	#179	Overall
	#30	Document stores
	#17	Graph DBMS
	#7	RDF stores
	#7	Vector DBMS

Score	421.08
Rank	#5	Overall
	#1	Document stores

Score	3.05
Rank	#97	Overall
	#17	Document stores
	#16	Key-value stores
	#50	Relational DBMS

Score	1.28
Rank	#167	Overall
	#6	Vector DBMS

Website

allegrograph.com

www.mongodb.com

www.oracle.com/database/nosql/technologies/nosql

github.com/qdrant/qdrant
qdrant.tech

Technical documentation

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

www.mongodb.com/docs/manual

docs.oracle.com/en/database/other-databases/nosql-database/index.html

qdrant.tech/documentation

Developer

Franz Inc.

Drizzle project, originally started by Brian Aker

MongoDB, Inc

Oracle

Qdrant

Initial release

2004

2008

2009

2011

2021

Current release

8.0, December 2023

7.2.4, September 2012

6.0.7, June 2023

24.1, May 2024

License

Commercial or Open Source

commercial

Limited community edition free

Open Source

GNU GPL

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

Proprietary for Enterprise Edition (Oracle Database EE license has Oracle NoSQL database EE covered: details)

Open Source

Apache Version 2.0

Cloud-based only

Only available as a cloud service

MongoDB available as DBaaS (MongoDB Atlas)

DBaaS offerings (sponsored links)

Database as a Service

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

MongoDB Flex @ STACKIT offers managed MongoDB Instances with adjustable CPU, RAM, storage amount and speed, in enterprise grade to perfectly match all application requirements. All services are 100% GDPR-compliant.
MongoDB Atlas: Global multi-cloud database with unmatched data distribution and mobility across AWS, Azure, and Google Cloud, built-in automation for resource and workload optimization, and so much more.

Implementation language

C++

Java

Rust

Server operating systems

Linux
OS X
Windows

FreeBSD
Linux
OS X

Linux
OS X
Solaris
Windows

Linux
Solaris SPARC/x86

Docker
Linux
macOS
Windows

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.

Support Fixed schema and Schema-less deployment with the ability to interoperate between them.

schema-free

Typing

predefined data types such as float or date

yes

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

optional

Numbers, Strings, Geo, Boolean

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

Keywords, numberic ranges, geo, full-text

SQL

Support of SQL

SPARQL is used as query language

yes

with proprietary extensions

Read-only SQL queries via the MongoDB Atlas SQL Interface

SQL-like DML and DDL statements

APIs and other access methods

RESTful HTTP API
SPARQL

JDBC

GraphQL
HTTP REST
Prisma
proprietary protocol using JSON

RESTful HTTP API

gRPC
OpenAPI 3.0
RESTful HTTP/JSON API

OpenAPI 3.0

Supported programming languages

C#
Clojure
Java
Lisp
Perl
Python
Ruby
Scala

C
C++
Java
PHP

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

C
C#
Go
Java
JavaScript (Node.js)
Python

.Net
Go
Java
JavaScript (Node.js)
Python
Rust

Server-side scripts

Stored procedures

yes

JavaScript or Common Lisp

JavaScript

Triggers

yes

hooks for callbacks inside the server can be used.

yes

in MongoDB Atlas only

Partitioning methods

Methods for storing different data on different nodes

with Federation

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

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

Electable source-replica replication per shard. Support distributed global deployment with Multi-region table feature

Collection-level replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

with Hadoop integration

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency or Eventual Consistency depending on configuration

Eventual Consistency

can be individually decided for each read operation
Immediate Consistency

default behaviour

Eventual Consistency
Immediate Consistency

depending on configuration

Eventual Consistency, tunable consistency

Foreign keys

Referential integrity

yes

typically not used, however similar functionality with DBRef possible

Transaction concepts

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

ACID

Multi-document ACID Transactions with snapshot isolation

configurable

ACID within a storage node (=shard)

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

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

In-memory storage engine introduced with MongoDB version 3.2

yes

off heap cache

yes

User concepts

Access control

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

Pluggable authentication mechanisms

e.g. LDAP, HTTP

Access rights for users and roles

Key-based authentication

More information provided by the system vendor

Specific characteristics

Knowledge Graph Platform Leader FedShard - Designed for Entity-Event Knowledge Graph...
» more

MongoDB provides an integrated suite of cloud database and data services to accelerate...
» more

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...
» more

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

We invite representatives of system vendors to contact us for updating and extending the system information,
and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.