DBMS > HEAVY.AI vs. MongoDB vs. Oracle NoSQL

System Properties Comparison HEAVY.AI vs. MongoDB vs. Oracle NoSQL

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Editorial information provided by DB-Engines

Name

Description

A high performance, column-oriented RDBMS, specifically developed to harness the massive parallelism of modern CPU and GPU hardware

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

A multi-model, scalable, distributed NoSQL database, designed to provide highly reliable, flexible, and available data management across a configurable set of storage nodes

Primary database model

Relational DBMS

Document store

Document store
Key-value store
Relational DBMS

Secondary database models

Spatial DBMS

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	1.48
Rank	#146	Overall
	#70	Relational DBMS

Score	477.66
Rank	#5	Overall
	#1	Document stores

Score	4.38
Rank	#86	Overall
	#16	Document stores
	#14	Key-value stores
	#45	Relational DBMS

Website

github.com/heavyai/heavydb
www.heavy.ai

www.mongodb.com

www.oracle.com/database/technologies/related/nosql.html

Technical documentation

docs.heavy.ai

docs.mongodb.com/manual

docs.oracle.com/en/database/other-databases/nosql-database/index.html

Developer

HEAVY.AI, Inc.

MongoDB, Inc

Oracle

Initial release

2016

2009

2011

Current release

5.10, January 2022

6.0.0, July 2022

22.1, May 2022

License

Commercial or Open Source

Open Source

Apache Version 2; enterprise edition 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.

Open Source

Proprietary for Enterprise Edition (Oracle Database EE license has Oracle NoSQL database EE covered: details)

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 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.
ScaleGrid for MongoDB: Fully managed hosting for MongoDB database on AWS, Azure and DigitalOcean with high availability and SSH access on the #1 multi-cloud DBaaS.

Implementation language

C++ and CUDA

C++

Java

Server operating systems

Linux

Linux
OS X
Solaris
Windows

Linux
Solaris SPARC/x86

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.

Support Fixed schema and Schema-less deployment with the ability to interoperate between them.

Typing

predefined data types such as float or date

yes

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

optional

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

Read-only SQL queries via the MongoDB Connector for BI

SQL-like DML and DDL statements

APIs and other access methods

JDBC
ODBC
Thrift
Vega

proprietary protocol using JSON

RESTful HTTP API

Supported programming languages

All languages supporting JDBC/ODBC/Thrift
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
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#
Go
Java
JavaScript (Node.js)
Python

Server-side scripts

Stored procedures

JavaScript

Triggers

yes

in MongoDB Atlas only

Partitioning methods

Methods for storing different data on different nodes

Sharding

Round robin

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

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication

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

Electable source-replica replication per shard. Support distributed global deployment with Multi-region table feature

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

with Hadoop integration

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency
Immediate Consistency

can be individually decided for each write operation

Eventual Consistency
Immediate Consistency

depending on configuration

Foreign keys

Referential integrity

typically not used, however similar functionality with DBRef possible

Transaction concepts

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

Multi-document ACID Transactions with snapshot isolation

configurable

ACID within a storage node (=shard)

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

yes

off heap cache

User concepts

Access control

fine grained access rights according to SQL-standard

Access rights for users and roles

More information provided by the system vendor

Specific characteristics

Optimizes memory and compute layers to deliver unprecedented performance. Natively...
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MongoDB’s application data platform provides developers a unified interface to power...
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Competitive advantages

Only HEAVY.AI allows users to visually and interactively discover high-value patterns,...
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The MongoDB platform can be used by developers building transactional, operational,...
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Typical application scenarios

Advanced analytics, geospatial and time-series analytics, accelerated data science,...
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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...
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Licensing and pricing models

HEAVY.AI Free (Free Forever), Foundations ($2k/month), and Enterprise Licensure (Inquire...
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MongoDB database server: Server-Side Public License (SSPL) . Commercial licenses...
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