DBMS > HugeGraph vs. Ingres vs. MongoDB vs. TerarkDB vs. TypeDB

System Properties Comparison HugeGraph vs. Ingres vs. MongoDB vs. TerarkDB vs. TypeDB

Editorial information provided by DB-Engines

Name

Description

A fast-speed and highly-scalable Graph DBMS

Well established RDBMS

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

A key-value store forked from RocksDB with advanced compression algorithms. It can be used standalone or as a storage engine for MySQL and MongoDB

TypeDB is a strongly-typed database with a rich and logical type system and TypeQL as its query language

Primary database model

Graph DBMS
Relational DBMS

Often described as a 'hyper-relational' database, since it implements the 'Entity-Relationship Paradigm' to manage complex data structures and ontologies.

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

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

Score	0.17
Rank	#335	Overall
	#31	Graph DBMS

Score	3.80
Rank	#82	Overall
	#44	Relational DBMS

Score	421.08
Rank	#5	Overall
	#1	Document stores

Score	0.08
Rank	#367	Overall
	#56	Key-value stores

Score	0.70
Rank	#230	Overall
	#20	Graph DBMS
	#106	Relational DBMS

Website

github.com/hugegraph
hugegraph.apache.org

www.actian.com/databases/ingres

www.mongodb.com

github.com/bytedance/terarkdb

typedb.com

Technical documentation

hugegraph.apache.org/docs

docs.actian.com/ingres

www.mongodb.com/docs/manual

bytedance.larkoffice.com/docs/doccnZmYFqHBm06BbvYgjsHHcKc

typedb.com/docs

Developer

Baidu

Actian Corporation

MongoDB, Inc

ByteDance, originally Terark

Vaticle

Initial release

2018

1974

originally developed at University Berkely in early 1970s

2009

2016

Current release

0.9

11.2, May 2022

6.0.7, June 2023

2.26.3, January 2024

License

Commercial or Open Source

Open Source

Apache Version 2.0

commercial

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

restricted open source version available

Open Source

GPL Version 3, commercial licenses available

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

Java

C++

Java

Server operating systems

Linux
macOS
Unix

AIX
HP Open VMS
HP-UX
Linux
Solaris
Windows

Linux
OS X
Solaris
Windows

Linux
OS X
Windows

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.

schema-free

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.

but tools for importing/exporting data from/to XML-files available

Secondary indexes

yes

also supports composite index and range index

yes

SQL

Support of SQL

yes

Read-only SQL queries via the MongoDB Atlas SQL Interface

APIs and other access methods

Java API
RESTful HTTP API
TinkerPop Gremlin

.NET Client API
JDBC
ODBC
proprietary protocol (OpenAPI)

GraphQL
HTTP REST
Prisma
proprietary protocol using JSON

C++ API
Java API

gRPC protocol
TypeDB Console (shell)
TypeDB Studio (Visualisation software- previously TypeDB Workbase)

Supported programming languages

Groovy
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++
Java

All JVM based languages
Groovy
Java
JavaScript (Node.js)
Python
Scala

Server-side scripts

Stored procedures

asynchronous Gremlin script jobs

yes

JavaScript

Triggers

yes

in MongoDB Atlas only

Partitioning methods

Methods for storing different data on different nodes

yes

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

horizontal partitioning

Ingres Star to access multiple databases simultaneously

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

Sharding

by using Cassandra

Replication methods

Methods for redundantly storing data on multiple nodes

yes

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

Ingres Replicator

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

none

Multi-source replication

by using Cassandra

MapReduce

Offers an API for user-defined Map/Reduce methods

via hugegraph-spark

yes

by using Apache Kafka and Apache Zookeeper

Consistency concepts

Methods to ensure consistency in a distributed system

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

typically not used, however similar functionality with DBRef possible

substituted by the relationship feature

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

MVCC

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

Users, roles and permissions

fine grained access rights according to SQL-standard

Access rights for users and roles

yes

at REST API level; other APIs in progress

More information provided by the system vendor

Specific characteristics

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

TypeDB is a polymorphic database with a conceptual data model, a strong subtyping...
» more

Competitive advantages

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

TypeDB provides a new level of expressivity, extensibility, interoperability, and...
» more

Typical application scenarios

AI-enriched intelligent apps (Continental, Telefonica, Iron Mountain) Internet of...
» more

Life sciences : TypeDB makes working with biological data much easier and accelerates...
» 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

Apache f or language drivers, and AGPL and Commercial for the database server. The...
» more

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.