DBMS > Lovefield vs. Machbase vs. MongoDB

System Properties Comparison Lovefield vs. Machbase vs. MongoDB

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Editorial information provided by DB-Engines

Name

Description

Embeddable relational database for web apps written in pure JavaScript

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

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	0.23
Rank	#286	Overall
	#134	Relational DBMS

Score	0.01
Rank	#358	Overall
	#32	Time Series DBMS

Score	480.73
Rank	#5	Overall
	#1	Document stores

Website

google.github.io/lovefield

www.machbase.com

www.mongodb.com

Technical documentation

github.com/google/lovefield/blob/master/docs/spec_index.md

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

docs.mongodb.com/manual

Developer

Google

Machbase

MongoDB, Inc

Initial release

2014

2013

2009

Current release

2.1.12, February 2017

V6.5, August 2021

5.0.9, May 2022

License

Commercial or Open Source

Open Source

Apache 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

JavaScript

C++

Server operating systems

server-less, requires a JavaScript environment (browser, Node.js)

tested with Chrome, Firefox, IE, Safari

Linux
Windows

Linux
OS X
Solaris
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.

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

SQL-like query language

via JavaScript builder pattern

SQL-like query language

Read-only SQL queries via the MongoDB Connector for BI

APIs and other access methods

HTTP REST
JDBC
ODBC

proprietary protocol using JSON

Supported programming languages

JavaScript

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

JavaScript

Triggers

Using read-only observers

yes

in MongoDB Atlas only

Partitioning methods

Methods for storing different data on different nodes

none

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

none

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

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, by using IndexedDB or the cloud service Firebase Realtime Database

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

using MemoryDB

yes

volatile and lookup table

yes

In-memory storage engine introduced with MongoDB version 3.2

User concepts

Access control

simple password-based access control

Access rights for users and roles

More information provided by the system vendor

Specific characteristics

MongoDB’s application data platform provides developers a unified interface to power...
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Competitive advantages

The MongoDB platform can be used by developers building transactional, operational,...
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Typical application scenarios

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

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

200+ million downloads, over 1.5M Atlas database clusters under management handling...
» more

Licensing and pricing models

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

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