DBMS > AllegroGraph vs. Apache Phoenix vs. Graph Engine vs. MongoDB vs. Snowflake

System Properties Comparison AllegroGraph vs. Apache Phoenix vs. Graph Engine vs. MongoDB vs. Snowflake

Editorial information provided by DB-Engines

Name

Description

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

A scale-out RDBMS with evolutionary schema built on Apache HBase

A distributed in-memory data processing engine, underpinned by a strongly-typed RAM store and a general distributed computation engine

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

Cloud-based data warehousing service for structured and semi-structured data

Primary database model

Document store

with version 6.5
Graph DBMS
RDF store
Vector DBMS

Relational DBMS

Graph DBMS
Key-value store

Document store

Relational 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	1.06
Rank	#187	Overall
	#30	Document stores
	#17	Graph DBMS
	#7	RDF stores
	#7	Vector DBMS

Score	1.97
Rank	#126	Overall
	#59	Relational DBMS

Score	0.61
Rank	#240	Overall
	#21	Graph DBMS
	#35	Key-value stores

Score	421.65
Rank	#5	Overall
	#1	Document stores

Score	121.33
Rank	#9	Overall
	#6	Relational DBMS

Website

Technical documentation

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

phoenix.apache.org

www.graphengine.io/docs/manual

www.mongodb.com/docs/manual

docs.snowflake.net/manuals/index.html

Developer

Franz Inc.

Apache Software Foundation

Microsoft

MongoDB, Inc

Snowflake Computing Inc.

Initial release

2004

2014

2010

2009

2014

Current release

8.0, December 2023

5.0-HBase2, July 2018 and 4.15-HBase1, December 2019

6.0.7, June 2023

License

Commercial or Open Source

commercial

Limited community edition free

Open Source

Apache Version 2.0

Open Source

MIT License

Open Source

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

commercial

Cloud-based only

Only available as a cloud service

MongoDB available as DBaaS (MongoDB Atlas)

yes

DBaaS offerings (sponsored links)

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Implementation language

Java

.NET and C

C++

Server operating systems

Linux
OS X
Windows

Linux
Unix
Windows

.NET

Linux
OS X
Solaris
Windows

hosted

Data scheme

yes

RDF schemas

yes

late-bound, schema-on-read capabilities

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.

yes

support of semi-structured data formats (JSON, XML, Avro)

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

yes

Secondary indexes

yes

SQL

Support of SQL

SPARQL is used as query language

yes

Read-only SQL queries via the MongoDB Atlas SQL Interface

yes

APIs and other access methods

RESTful HTTP API
SPARQL

JDBC

RESTful HTTP API

GraphQL
HTTP REST
Prisma
proprietary protocol using JSON

CLI Client
JDBC
ODBC

Supported programming languages

C#
Clojure
Java
Lisp
Perl
Python
Ruby
Scala

C
C#
C++
Go
Groovy
Java
PHP
Python
Scala

C#
C++
F#
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

JavaScript (Node.js)
Python

Server-side scripts

Stored procedures

yes

JavaScript or Common Lisp

user defined functions

yes

JavaScript

user defined functions

Triggers

yes

in MongoDB Atlas only

similar concept for controling cloud resources

Partitioning methods

Methods for storing different data on different nodes

with Federation

Sharding

horizontal partitioning

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.

yes

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

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

Hadoop integration

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency or Eventual Consistency depending on configuration

Immediate Consistency or Eventual Consistency

Eventual Consistency

can be individually decided for each read operation
Immediate Consistency

default behaviour

Immediate Consistency

Foreign keys

Referential integrity

typically not used, however similar functionality with DBRef possible

yes

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

optional: either by committing a write-ahead log (WAL) to the local persistent storage or by dumping the memory to a persistent storage

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

User concepts

Access control

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

Access Control Lists (using HBase ACL) for RBAC, integration with Apache Ranger for RBAC & ABAC, multi-tenancy

Access rights for users and roles

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

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