DBMS > AnzoGraph DB vs. Hazelcast vs. Heroic vs. MongoDB vs. Stardog

System Properties Comparison AnzoGraph DB vs. Hazelcast vs. Heroic vs. MongoDB vs. Stardog

Editorial information provided by DB-Engines

Name

Description

Scalable graph database built for online analytics and data harmonization with MPP scaling, high-performance analytical algorithms and reasoning, and virtualization

A widely adopted in-memory data grid

Time Series DBMS built at Spotify based on Cassandra or Google Cloud Bigtable, and ElasticSearch

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

Enterprise Knowledge Graph platform and graph DBMS with high availability, high performance reasoning, and virtualization

Primary database model

Secondary database models

Document store

JSON support with IMDG 3.12

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	0.29
Rank	#303	Overall
	#25	Graph DBMS
	#14	RDF stores

Score	5.46
Rank	#61	Overall
	#7	Key-value stores

Score	0.46
Rank	#265	Overall
	#22	Time Series DBMS

Score	421.08
Rank	#5	Overall
	#1	Document stores

Score	2.07
Rank	#122	Overall
	#11	Graph DBMS
	#6	RDF stores

Website

cambridgesemantics.com/anzograph

hazelcast.com

github.com/spotify/heroic

www.mongodb.com

www.stardog.com

Technical documentation

docs.cambridgesemantics.com/anzograph/userdoc/home.htm

hazelcast.org/imdg/docs

spotify.github.io/heroic

www.mongodb.com/docs/manual

docs.stardog.com

Developer

Cambridge Semantics

Hazelcast

Spotify

MongoDB, Inc

Stardog-Union

Initial release

2018

2008

2014

2009

2010

Current release

2.3, January 2021

5.3.6, November 2023

6.0.7, June 2023

7.3.0, May 2020

License

Commercial or Open Source

commercial

free trial version available

Open Source

Apache Version 2; commercial licenses available

Open Source

Apache 2.0

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

60-day fully-featured trial license; 1-year fully-featured non-commercial use license for academics/students

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

Java

C++

Java

Server operating systems

Linux

All OS with a Java VM

Linux
OS X
Solaris
Windows

Linux
macOS
Windows

Data scheme

Schema-free and OWL/RDFS-schema support

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 and OWL/RDFS-schema support

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.

yes

the object must implement a serialization strategy

Import/export of XML data possible

Secondary indexes

yes

via Elasticsearch

yes

supports real-time indexing in full-text and geospatial

SQL

Support of SQL

SPARQL and SPARQL* as primary query language. Cypher preview.

SQL-like query language

Read-only SQL queries via the MongoDB Atlas SQL Interface

Yes, compatible with all major SQL variants through dedicated BI/SQL Server

APIs and other access methods

Apache Mule
gRPC
JDBC
Kafka
OData access for BI tools
OpenCypher
RESTful HTTP API
SPARQL

JCache
JPA
Memcached protocol
RESTful HTTP API

HQL (Heroic Query Language, a JSON-based language)
HTTP API

GraphQL
HTTP REST
Prisma
proprietary protocol using JSON

GraphQL query language
HTTP API
Jena RDF API
OWL
RDF4J API
Sesame REST HTTP Protocol
SNARL
SPARQL
Spring Data
Stardog Studio
TinkerPop 3

Supported programming languages

C++
Java
Python

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

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
Clojure
Groovy
Java
JavaScript
Python
Ruby

Server-side scripts

Stored procedures

user defined functions and aggregates

yes

Event Listeners, Executor Services

JavaScript

user defined functions and aggregates, HTTP Server extensions in Java

Triggers

yes

Events

yes

in MongoDB Atlas only

yes

via event handlers

Partitioning methods

Methods for storing different data on different nodes

Automatic sharding

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.

none

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication in MPP-Cluster

yes

Replicated Map

yes

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

Multi-source replication in HA-Cluster

MapReduce

Offers an API for user-defined Map/Reduce methods

Kerberos/HDFS data loading

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency in MPP-Cluster

Immediate Consistency or Eventual Consistency selectable by user

Raft Consensus Algorithm

Eventual Consistency
Immediate Consistency

Eventual Consistency

can be individually decided for each read operation
Immediate Consistency

default behaviour

Immediate Consistency in HA-Cluster

Foreign keys

Referential integrity

not needed in graphs

typically not used, however similar functionality with DBRef possible

yes

relationships in graphs

Transaction concepts

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

ACID

one or two-phase-commit; repeatable reads; read commited

Multi-document ACID Transactions with snapshot isolation

ACID

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

User concepts

Access control

Access rights for users and roles

Role-based access control

Access rights for users and roles

More information provided by the system vendor

Specific characteristics

MongoDB provides an integrated suite of cloud database and data services to accelerate...
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Competitive advantages

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

Hundreds of millions downloads, over 150,000+ Atlas clusters provisioned every month...
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Licensing and pricing models

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