DBMS > MongoDB vs. Tibero vs. TigerGraph

System Properties Comparison MongoDB vs. Tibero vs. TigerGraph

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Editorial information provided by DB-Engines

Name

Description

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

A secure RDBMS, designed for easy portability from Oracle

A complete, distributed, parallel graph computing platform supporting web-scale data analytics in real-time

Primary database model

Document store

Relational DBMS

Graph 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

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

Score	425.36
Rank	#5	Overall
	#1	Document stores

Score	2.34
Rank	#143	Overall
	#68	Relational DBMS

Score	2.20
Rank	#149	Overall
	#11	Graph DBMS

Website

www.mongodb.com

www.tmaxsoft.com/products/tibero

www.tigergraph.com

Technical documentation

docs.mongodb.com/manual

technet.tmaxsoft.com/upload/download/online/tibero/pver-20150504-000002/index.html

docs.tigergraph.com

Developer

MongoDB, Inc

TmaxSoft

Initial release

2009

2003

2017

Current release

6.0.5, March 2023

6, April 2015

License

Commercial or Open Source

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)

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

ScaleGrid for MongoDB Database: Fully managed hosting for MongoDB Database on a wide variety of cloud providers and On-Premises. Automate your management, scaling and backups through one centralized platform.
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

C++

C and Assembler

C++

Server operating systems

Linux
OS X
Solaris
Windows

AIX
HP-UX
Linux
Solaris
Windows

Linux

Data scheme

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

SQL

Support of SQL

Read-only SQL queries via the MongoDB Connector for BI

yes

SQL-like query language (GSQL)

APIs and other access methods

proprietary protocol using JSON

JDBC
ODBC
ODP.NET
Oracle Call Interface (OCI)
Tibero CLI

GSQL (TigerGraph Query Language)
Kafka
RESTful HTTP/JSON API

Supported programming languages

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
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#
C++
Cobol
Java
Objective-C
Perl
PHP
Python
Ruby
Visual Basic

C++
Java

Server-side scripts

Stored procedures

JavaScript

Persistent Stored Procedure (PSM)

yes

Triggers

yes

in MongoDB Atlas only

yes

Partitioning methods

Methods for storing different data on different nodes

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.

horizontal partitioning

by range, hash, list or composite

Replication methods

Methods for redundantly storing data on multiple nodes

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

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency
Immediate Consistency

can be individually decided for each write operation

Immediate Consistency

Foreign keys

Referential integrity

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

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

planned for next version

User concepts

Access control

Access rights for users and roles

fine grained access rights according to SQL-standard (SQL 92, SQL 99)

Role-based access control

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

Internet of Things and Time Series (Bosch, GE Healthcare, Jaguar Land Rover) Mobile...
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Key customers

ADP, Adobe, Amadeus, AstraZeneca, Auto Trader, Barclays, BBVA, Bosch, Cisco, CERN,...
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Market metrics

365+ million downloads, over 150,000+ Atlas clusters provisioned every month handling...
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Licensing and pricing models

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