DBMS > HugeGraph vs. JanusGraph vs. MongoDB vs. Teradata vs. VoltDB

System Properties Comparison HugeGraph vs. JanusGraph vs. MongoDB vs. Teradata vs. VoltDB

Editorial information provided by DB-Engines

Name

Description

A fast-speed and highly-scalable Graph DBMS

A Graph DBMS optimized for distributed clusters

It was forked from the latest code base of Titan in January 2017

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

A hybrid cloud data analytics software platform (Teradata Vantage)

Distributed In-Memory NewSQL RDBMS

Used for OLTP applications with a high frequency of relatively simple transactions, that can hold all their data in memory

Primary database model

Graph DBMS

Document store

Relational DBMS

Secondary database models

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

Document store
Graph DBMS
Spatial DBMS
Time Series DBMS

DB-Engines Ranking measures the popularity of database management systems
Trend Chart

Score	0.13
Rank	#336	Overall
	#32	Graph DBMS

Score	1.94
Rank	#129	Overall
	#12	Graph DBMS

Score	421.65
Rank	#5	Overall
	#1	Document stores

Score	45.33
Rank	#21	Overall
	#15	Relational DBMS

Score	1.44
Rank	#158	Overall
	#73	Relational DBMS

Website

github.com/hugegraph
hugegraph.apache.org

Technical documentation

hugegraph.apache.org/docs

docs.janusgraph.org

www.mongodb.com/docs/manual

docs.teradata.com

docs.voltdb.com

Developer

Baidu

Linux Foundation; originally developed as Titan by Aurelius

MongoDB, Inc

Teradata

VoltDB Inc.

Initial release

2018

2017

2009

1984

2010

Current release

0.9

0.6.3, February 2023

6.0.7, June 2023

Teradata Vantage 1.0 MU2, January 2019

11.3, April 2022

License

Commercial or Open Source

Open Source

Apache Version 2.0

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

Open Source

AGPL for Community Edition, commercial license for Enterprise, AWS, and Pro Editions

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, C++

Server operating systems

Linux
macOS
Unix

Linux
OS X
Unix
Windows

Linux
OS X
Solaris
Windows

hosted
Linux

Linux
OS X

for development

Data scheme

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

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

Secondary indexes

yes

also supports composite index and range index

yes

Join-index to prejoin tables, aggregate index, sparse index, hash index

yes

SQL

Support of SQL

Read-only SQL queries via the MongoDB Atlas SQL Interface

yes

SQL 2016 + extensions

yes

only a subset of SQL 99

APIs and other access methods

Java API
RESTful HTTP API
TinkerPop Gremlin

Java API
TinkerPop Blueprints
TinkerPop Frames
TinkerPop Gremlin
TinkerPop Rexster

GraphQL
HTTP REST
Prisma
proprietary protocol using JSON

.NET Client API
HTTP REST
JDBC
JMS Adapter
ODBC
OLE DB

Java API
JDBC
RESTful HTTP/JSON API

Supported programming languages

Groovy
Java
Python

Clojure
Java
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

C
C++
Cobol
Java (JDBC-ODBC)
Perl
PL/1
Python
R
Ruby

C#
C++
Erlang

not officially supported
Go
Java
JavaScript

Node.js
PHP
Python

Server-side scripts

Stored procedures

asynchronous Gremlin script jobs

yes

JavaScript

yes

UDFs, stored procedures, table functions in parallel

Java

Triggers

yes

in MongoDB Atlas only

yes

Partitioning methods

Methods for storing different data on different nodes

yes

depending on used storage backend, e.g. Cassandra and HBase

yes

depending on the used storage backend (e.g. Cassandra, HBase, BerkeleyDB)

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

Hashing

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes

depending on used storage backend, e.g. Cassandra and HBase

yes

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

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

via hugegraph-spark

yes

via Faunus, a graph analytics engine

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

Eventual Consistency
Immediate Consistency

Eventual Consistency

can be individually decided for each read operation
Immediate Consistency

default behaviour

Immediate Consistency

Foreign keys

Referential integrity

yes

edges in graph

yes

Relationships in graphs

typically not used, however similar functionality with DBRef possible

yes

FOREIGN KEY constraints are not supported

Transaction concepts

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

ACID

Multi-document ACID Transactions with snapshot isolation

ACID

Transactions are executed single-threaded within stored procedures

Concurrency

Support for concurrent manipulation of data

yes

Data access is serialized by the server

Durability

Support for making data persistent

yes

Supports various storage backends: Cassandra, HBase, Berkeley DB, Akiban, Hazelcast

yes

optional, enabled by default

yes

Snapshots and command logging

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

Users, roles and permissions

User authentification and security via Rexster Graph Server

Access rights for users and roles

fine grained access rights according to SQL-standard

Users and roles with access to stored procedures

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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