DBMS > AllegroGraph vs. DuckDB vs. IRONdb vs. KeyDB vs. MongoDB

System Properties Comparison AllegroGraph vs. DuckDB vs. IRONdb vs. KeyDB vs. MongoDB

Editorial information provided by DB-Engines

Name

IRONdb seems to be discontinued. Therefore it is excluded from the DB-Engines Ranking.

Description

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

An embeddable, in-process, column-oriented SQL OLAP RDBMS

A distributed Time Series DBMS with a focus on scalability, fault tolerance and operational simplicity

An ultra-fast, open source Key-value store fully compatible with Redis API, modules, and protocols

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

Primary database model

Document store

with version 6.5
Graph DBMS
RDF store
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	4.63
Rank	#69	Overall
	#37	Relational DBMS

Score	0.70
Rank	#229	Overall
	#32	Key-value stores

Score	421.08
Rank	#5	Overall
	#1	Document stores

Website

allegrograph.com

duckdb.org

www.circonus.com/solutions/time-series-database/

github.com/Snapchat/KeyDB
keydb.dev

www.mongodb.com

Technical documentation

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

duckdb.org/docs

docs.circonus.com/irondb/category/getting-started

docs.keydb.dev

www.mongodb.com/docs/manual

Developer

Franz Inc.

Circonus LLC.

EQ Alpha Technology Ltd.

MongoDB, Inc

Initial release

2004

2018

2017

2019

2009

Current release

8.0, December 2023

1.0.0, June 2024

V0.10.20, January 2018

6.0.7, June 2023

License

Commercial or Open Source

commercial

Limited community edition free

Open Source

MIT License

commercial

Open Source

BSD-3

Open Source

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

Cloud-based only

Only available as a cloud service

MongoDB available as DBaaS (MongoDB Atlas)

DBaaS offerings (sponsored links)

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Implementation language

C++

C and C++

C++

Server operating systems

Linux
OS X
Windows

server-less

Linux

Linux
OS X
Solaris
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.

Typing

predefined data types such as float or date

yes

text, numeric, histograms

partial

Supported data types are strings, hashes, lists, sets and sorted sets, bit arrays, hyperloglogs and geospatial indexes

yes

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

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

by using the Redis Search module

yes

SQL

Support of SQL

SPARQL is used as query language

yes

SQL-like query language (Circonus Analytics Query Language: CAQL)

Read-only SQL queries via the MongoDB Atlas SQL Interface

APIs and other access methods

RESTful HTTP API
SPARQL

Arrow Database Connectivity (ADBC)
CLI Client
JDBC
ODBC

HTTP API

Proprietary protocol

RESP - REdis Serialization Protoco

GraphQL
HTTP REST
Prisma
proprietary protocol using JSON

Supported programming languages

C#
Clojure
Java
Lisp
Perl
Python
Ruby
Scala

C
C#

3rd party driver
C++
Crystal

3rd party driver
Go

3rd party driver
Java
Lisp

3rd party driver
Python
R
Ruby

3rd party driver
Rust
Swift
Zig

3rd party driver

.Net
C
C++
Clojure
Erlang
Go
Haskell
Java
JavaScript
JavaScript (Node.js)
Lisp
Lua
Perl
PHP
Python
R
Ruby
Rust
Scala

C
C#
C++
Clojure
Crystal
D
Dart
Elixir
Erlang
Fancy
Go
Haskell
Haxe
Java
JavaScript (Node.js)
Lisp
Lua
MatLab
Objective-C
OCaml
Pascal
Perl
PHP
Prolog
Pure Data
Python
R
Rebol
Ruby
Rust
Scala
Scheme
Smalltalk
Swift
Tcl
Visual Basic

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

Server-side scripts

Stored procedures

yes

JavaScript or Common Lisp

yes, in Lua

Lua

JavaScript

Triggers

yes

in MongoDB Atlas only

Partitioning methods

Methods for storing different data on different nodes

with Federation

none

Automatic, metric affinity per node

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.

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication
Source-replica replication

none

configurable replication factor, datacenter aware

Multi-source replication
Source-replica replication

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

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency or Eventual Consistency depending on configuration

Immediate Consistency

Immediate consistency per node, eventual consistency across nodes

Eventual Consistency
Strong eventual consistency with CRDTs

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

Transaction concepts

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

ACID

Optimistic locking, atomic execution of commands blocks and scripts

Multi-document ACID Transactions with snapshot isolation

Concurrency

Support for concurrent manipulation of data

yes

yes, multi-version concurrency control (MVCC)

yes

Durability

Support for making data persistent

yes

Configurable mechanisms for persistency via snapshots and/or operations logs

yes

optional, enabled by default

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

User concepts

Access control

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

simple password-based access control and ACL

Access rights for users and roles

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...
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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

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23 May 2024

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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.