DBMS > Amazon DocumentDB vs. Netezza vs. Trino

System Properties Comparison Amazon DocumentDB vs. Netezza vs. Trino

Please select another system to include it in the comparison.

Editorial information provided by DB-Engines

Name

Description

Fast, scalable, highly available, and fully managed MongoDB-compatible database service

Data warehouse and analytics appliance part of IBM PureSystems

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

Primary database model

Document store

Relational DBMS

Secondary database models

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	1.79
Rank	#125	Overall
	#23	Document stores

Score	6.55
Rank	#52	Overall
	#32	Relational DBMS

Score	5.18
Rank	#60	Overall
	#34	Relational DBMS

Website

aws.amazon.com/documentdb

www.ibm.com/products/netezza

trino.io

Technical documentation

aws.amazon.com/documentdb/resources

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

Developer

IBM

Trino Software Foundation

Initial release

2019

2000

2012

2020 rebranded from PrestoSQL

License

Commercial or Open Source

commercial

Open Source

Apache Version 2.0

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

Java

Server operating systems

hosted

Linux

included in appliance

Linux
macOS

for devlopment

Data scheme

schema-free

yes

Typing

predefined data types such as float or date

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.

Secondary indexes

yes

depending on connected data-source

SQL

Support of SQL

yes

APIs and other access methods

proprietary protocol using JSON (MongoDB compatible)

JDBC
ODBC
OLE DB

JDBC
RESTful HTTP API
Trino CLI

Supported programming languages

Go
Java
JavaScript (Node.js)
PHP
Python

C
C++
Fortran
Java
Lua
Perl
Python
R

Go
Java
JavaScript (Node.js)
Python
R
Ruby

Server-side scripts

Stored procedures

yes

yes, depending on connected data-source

Triggers

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

depending on connected data-source

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-availability zones for high availability, asynchronous replication for up to 15 read replicas

Source-replica replication

depending on connected data-source

MapReduce

Offers an API for user-defined Map/Reduce methods

may be implemented via Amazon Elastic MapReduce (Amazon EMR)

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

depending on connected data-source

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

Atomic single-document operations

ACID

depending on connected data-source

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

depending on connected data-source

User concepts

Access control

Access rights for users and roles

Users with fine-grained authorization concept

SQL standard access control

More information provided by the system vendor

News

73: Wrapping Trino packages with a bow
9 April 2025

Core Principles and Design Practices of OLAP Engines
27 March 2025

72: Keeping the lake clean
17 March 2025

Twenty four
3 March 2025

71: Fake it real good
27 February 2025

We invite representatives of system vendors to contact us for updating and extending the system information,
and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

Related products and services

We invite representatives of vendors of related products to contact us for presenting information about their offerings here.

More resources

Recent citations in the news

Powering a Generative AI Platform Using Amazon DocumentDB with tresle.ai | Amazon Web Services
18 April 2025, Amazon Web Services

Amazon DocumentDB Quick Start: Zero Setup with AWS CloudShell
14 March 2025, Amazon Web Services

Use IAM authentication with Amazon DocumentDB (with MongoDB compatibility)
17 October 2024, Amazon Web Services

Optimizing costs on Amazon DocumentDB using event-driven architecture and the AWS EventBridge Terraform module
23 August 2024, Amazon Web Services

Build containerized applications for Amazon DocumentDB that run on Amazon ECS on AWS Fargate
23 October 2024, Amazon Web Services

provided by Google News

Netezza and IBM Cloud Pak for Data: A knockout combo for tough data
15 January 2025, IBM

How to use Netezza Performance Server query data in Amazon Simple Storage Service (S3)
20 December 2024, IBM

How to migrate a large data warehouse from IBM Netezza to Amazon Redshift with no downtime
21 August 2019, Amazon Web Services (AWS)

IBM Completes Acquisition of Netezza
26 October 2017, PR Newswire

Unify and share data across Netezza and watsonx.data for new generative AI applications
21 June 2024, IBM

provided by Google News

The Perfect AI Storage: Trino From Facebook And Iceberg From Netflix?
30 April 2024, The Next Platform

A look at Presto, Trino SQL query engines
9 August 2022, TechTarget

Query big data with resilience using Trino in Amazon EMR with Amazon EC2 Spot Instances for less cost
4 October 2023, Amazon Web Services (AWS)

Trino: The Open-source Data Query Engine That Split from Facebook
30 March 2022, HackerNoon

Trino turns 10: Starburst celebrates a decade of its open source query engine
11 August 2022, VentureBeat

provided by Google News

Share this page