DBMS > Hazelcast vs. MongoDB vs. Trafodion vs. Trino

System Properties Comparison Hazelcast vs. MongoDB vs. Trafodion vs. Trino

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Editorial information provided by DB-Engines

Name

Apache Trafodion has been retired in 2021. Therefore it is excluded from the DB-Engines Ranking.

Description

A widely adopted in-memory data grid

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

Transactional SQL-on-Hadoop DBMS

Fast distributed SQL query engine for big data analytics. Forked from Presto and originally named PrestoSQL

Primary database model

Key-value store

Document store

Relational DBMS

Secondary database models

Document store

JSON support with IMDG 3.12

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

Document store
Key-value store
Spatial DBMS
Search engine
Time Series DBMS
Wide column store

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

Score	5.46
Rank	#61	Overall
	#7	Key-value stores

Score	421.08
Rank	#5	Overall
	#1	Document stores

Score	4.99
Rank	#65	Overall
	#36	Relational DBMS

Website

Technical documentation

hazelcast.org/imdg/docs

www.mongodb.com/docs/manual

trafodion.apache.org/documentation.html

trino.io/broadcast
trino.io/docs/current

Social network pages

Developer

Hazelcast

MongoDB, Inc

Apache Software Foundation, originally developed by HP

Trino Software Foundation

Initial release

2008

2009

2014

2012

2020 rebranded from PrestoSQL

Current release

5.3.6, November 2023

6.0.7, June 2023

2.3.0, February 2019

License

Commercial or Open Source

Open Source

Apache Version 2; commercial licenses 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

Apache 2.0

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 Flex @ STACKIT offers managed MongoDB Instances with adjustable CPU, RAM, storage amount and speed, in enterprise grade to perfectly match all application requirements. All services are 100% GDPR-compliant.
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.

Starburst Galaxy offers a feature-rich user interface to connect all your data sources, manage your Trino clusters, and query your data.

Implementation language

Java

C++

C++, Java

Java

Server operating systems

All OS with a Java VM

Linux
OS X
Solaris
Windows

Linux

Linux
macOS

for devlopment

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

the object must implement a serialization strategy

Secondary indexes

yes

depending on connected data-source

SQL

Support of SQL

SQL-like query language

Read-only SQL queries via the MongoDB Atlas SQL Interface

yes

APIs and other access methods

JCache
JPA
Memcached protocol
RESTful HTTP API

GraphQL
HTTP REST
Prisma
proprietary protocol using JSON

ADO.NET
JDBC
ODBC

JDBC
RESTful HTTP API
Trino CLI

Supported programming languages

.Net
C#
C++
Clojure
Go
Java
JavaScript (Node.js)
Python
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
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

All languages supporting JDBC/ODBC/ADO.Net

Go
Java
JavaScript (Node.js)
Python
R
Ruby

Server-side scripts

Stored procedures

yes

Event Listeners, Executor Services

JavaScript

Java Stored Procedures

yes, depending on connected data-source

Triggers

yes

Events

yes

in MongoDB Atlas only

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.

Sharding

depending on connected data-source

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Replicated Map

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

yes, via HBase

depending on connected data-source

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

via user defined functions and HBase

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency or Eventual Consistency selectable by user

Raft Consensus Algorithm

Eventual Consistency

can be individually decided for each read operation
Immediate Consistency

default behaviour

Immediate Consistency

depending on connected data-source

Foreign keys

Referential integrity

typically not used, however similar functionality with DBRef possible

yes

Transaction concepts

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

one or two-phase-commit; repeatable reads; read commited

Multi-document ACID Transactions with snapshot isolation

ACID

depending on connected data-source

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

optional, enabled by default

yes

depending on connected data-source

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

User concepts

Access control

Role-based access control

Access rights for users and roles

fine grained access rights according to SQL-standard

SQL standard access control

More information provided by the system vendor

Specific characteristics

MongoDB provides an integrated suite of cloud database and data services to accelerate...
» more

Trino is the fastest open source, massively parallel processing SQL query engine...
» more

Competitive advantages

Built around the flexible document data model and unified API, MongoDB is a developer...
» more

High performance analtyics and data processing of very large data sets Powerful ANSI...
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Typical application scenarios

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

Performant analytics query engine for data warehouses, data lakes, and data lakehouses...
» more

Key customers

ADP, Adobe, Amadeus, AstraZeneca, Auto Trader, Barclays, BBVA, Bosch, Cisco, CERN,...
» more

Trino is widely adopted across the globe as freely-available open source software....
» more

Market metrics

Hundreds of millions downloads, over 150,000+ Atlas clusters provisioned every month...
» more

33000+ commits in GitHub 8200+ stargazers in GitHub 1200+ pull requests merged in...
» more

Licensing and pricing models

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

Trino is an open source project and usage is therefore free. Commercial offerings...
» more

News

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22 May 2024

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8 May 2024

59: Querying Trino with Java and jOOQ
24 April 2024

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15 April 2024

Time travel in Delta Lake connector
11 April 2024

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and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.