DBMS > HEAVY.AI vs. InterSystems IRIS vs. MongoDB vs. ReductStore vs. Tkrzw

System Properties Comparison HEAVY.AI vs. InterSystems IRIS vs. MongoDB vs. ReductStore vs. Tkrzw

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

A containerised multi-model DBMS, interoperability and analytics data platform with wide capabilities for vertical and horizontal scalability

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

Designed to manage unstructured time-series data efficiently, providing unique features such as storing time-stamped blobs with labels, customizable data retention policies, and a straightforward FIFO quota system.

A concept of libraries, allowing an application program to store and query key-value pairs in a file. Successor of Tokyo Cabinet and Kyoto Cabinet

Primary database model

Relational DBMS

Document store
Key-value store
Object oriented DBMS
Relational DBMS

Document store

Time Series DBMS

Key-value store

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
Vector DBMS

currently available in the MongoDB Atlas cloud service only

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

Score	1.64
Rank	#145	Overall
	#67	Relational DBMS

Score	3.54
Rank	#84	Overall
	#14	Document stores
	#10	Key-value stores
	#1	Object oriented DBMS
	#45	Relational DBMS

Score	421.08
Rank	#5	Overall
	#1	Document stores

Score	0.05
Rank	#384	Overall
	#44	Time Series DBMS

Score	0.07
Rank	#372	Overall
	#57	Key-value stores

Website

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

www.intersystems.com/products/intersystems-iris

www.mongodb.com

github.com/reductstore
www.reduct.store

dbmx.net/tkrzw

Technical documentation

docs.heavy.ai

docs.intersystems.com/irislatest/csp/docbook/DocBook.UI.Page.cls

www.mongodb.com/docs/manual

www.reduct.store/docs

Developer

HEAVY.AI, Inc.

InterSystems

MongoDB, Inc

ReductStore LLC

Mikio Hirabayashi

Initial release

2016

2018

2009

2023

2020

Current release

5.10, January 2022

2023.3, June 2023

6.0.7, June 2023

1.9, March 2024

0.9.3, August 2020

License

Commercial or Open Source

Open Source

Apache Version 2; enterprise edition available

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.

Open Source

Business Source License 1.1

Open Source

Apache Version 2.0

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.
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Implementation language

C++ and CUDA

C++

C++, Rust

C++

Server operating systems

Linux

AIX
Linux
macOS
Ubuntu
Windows

Linux
OS X
Solaris
Windows

Docker
Linux
macOS
Windows

Linux
macOS

Data scheme

yes

depending on used data model

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

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.

yes

Secondary indexes

yes

SQL

Support of SQL

yes

Read-only SQL queries via the MongoDB Atlas SQL Interface

APIs and other access methods

JDBC
ODBC
Thrift
Vega

JDBC
ODBC
RESTful HTTP API

GraphQL
HTTP REST
Prisma
proprietary protocol using JSON

HTTP API

Supported programming languages

All languages supporting JDBC/ODBC/Thrift
Python

.Net
C++
Java
JavaScript (Node.js)
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++
JavaScript (Node.js)
Python
Rust

C++
Java
Python
Ruby

Server-side scripts

Stored procedures

yes

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.

none

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication

Source-replica replication

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

none

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

can be individually decided for each read operation
Immediate Consistency

default behaviour

Immediate Consistency

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

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

using specific database classes

User concepts

Access control

fine grained access rights according to SQL-standard

yes

Access rights for users and roles

More information provided by the system vendor

Specific characteristics

InterSystems IRIS is a complete cloud-first data platform which includes a multi-model...
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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

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

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