DBMS > AgensGraph vs. Machbase vs. MongoDB

System Properties Comparison AgensGraph vs. Machbase vs. MongoDB

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Editorial information provided by DB-Engines

Name

Description

Multi-model database supporting relational and graph data models and built upon PostgreSQL

TimeSeries DBMS for AIoT and BigData

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

Primary database model

Graph DBMS
Relational DBMS

Time Series DBMS

Document store

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	0.07
Rank	#377	Overall
	#37	Graph DBMS
	#156	Relational DBMS

Score	0.33
Rank	#305	Overall
	#24	Time Series DBMS

Score	458.78
Rank	#5	Overall
	#1	Document stores

Website

bitnine.net

www.machbase.com

www.mongodb.com

Technical documentation

bitnine.net/documentation

machbase.atlassian.net/wiki/spaces/MAN/overview

docs.mongodb.com/manual

Developer

Bitnine Global Inc.

Machbase

MongoDB, Inc

Initial release

2016

2013

2009

Current release

2.1, December 2018

V6.5, August 2021

6.0.1, August 2022

License

Commercial or Open Source

Open Source

Apache License 2.0

commercial

free test version available

Open Source

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

Cloud-based only

Only available as a cloud service

MongoDB available as DBaaS (MongoDB Atlas)

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

C++

Server operating systems

Linux
OS X
Windows

Linux
Windows

Linux
OS X
Solaris
Windows

Data scheme

depending on used data model

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.

Typing

predefined data types such as float or date

yes

string, integer, double, decimal, boolean, date, object_id, geospatial

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.

Secondary indexes

yes

SQL

Support of SQL

yes

SQL-like query language

Read-only SQL queries via the MongoDB Connector for BI

APIs and other access methods

Cypher Query Language
JDBC

HTTP REST
JDBC
ODBC

proprietary protocol using JSON

Supported programming languages

C
Java
JavaScript
Python

C
C#
C++
Java
JavaScript
PHP

via ODBC
Python
R

via ODBC
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
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

Server-side scripts

Stored procedures

yes

JavaScript

Triggers

yes

in MongoDB Atlas only

Partitioning methods

Methods for storing different data on different nodes

no, but can be realized using table inheritance

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.

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

selectable replication factor

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

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency
Immediate Consistency

can be individually decided for each write operation

Foreign keys

Referential integrity

yes

typically not used, however similar functionality with DBRef possible

Transaction concepts

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

ACID

Multi-document ACID Transactions with snapshot isolation

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

optional, enabled by default

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

yes

volatile and lookup table

yes

In-memory storage engine introduced with MongoDB version 3.2

User concepts

Access control

fine grained access rights according to SQL-standard

simple password-based access control

Access rights for users and roles

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