DBMS > Apache Impala vs. DuckDB vs. Trino

System Properties Comparison Apache Impala vs. DuckDB vs. Trino

Please select another system to include it in the comparison.

Editorial information provided by DB-Engines

Name

Description

Analytic DBMS for Hadoop

An embeddable, in-process, column-oriented SQL OLAP RDBMS

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

Primary database model

Relational DBMS

Secondary database models

Document store

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	10.39
Rank	#41	Overall
	#25	Relational DBMS

Score	6.17
Rank	#55	Overall
	#33	Relational DBMS

Score	5.38
Rank	#60	Overall
	#35	Relational DBMS

Website

impala.apache.org

duckdb.org

trino.io

Technical documentation

impala.apache.org/impala-docs.html

duckdb.org/docs

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

Developer

Apache Software Foundation

Apache top-level project, originally developed by Cloudera

Trino Software Foundation

Initial release

2013

2018

2012

2020 rebranded from PrestoSQL

Current release

4.1.0, June 2022

1.0.0, June 2024

License

Commercial or Open Source

Open Source

Apache Version 2

Open Source

MIT License

Open Source

Apache Version 2.0

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

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

Implementation language

C++

Java

Server operating systems

Linux

server-less

Linux
macOS

for devlopment

Data scheme

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

SQL-like DML and DDL statements

yes

APIs and other access methods

JDBC
ODBC

Arrow Database Connectivity (ADBC)
CLI Client
JDBC
ODBC

JDBC
RESTful HTTP API
Trino CLI

Supported programming languages

All languages supporting JDBC/ODBC

C
C#

3rd party driver
C++
Crystal

3rd party driver
Go

3rd party driver
Java
Lisp

3rd party driver
Python
R
Ruby

3rd party driver
Rust
Swift
Zig

3rd party driver

Go
Java
JavaScript (Node.js)
Python
R
Ruby

Server-side scripts

Stored procedures

yes

user defined functions and integration of map-reduce

yes, depending on connected data-source

Triggers

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

depending on connected data-source

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

none

depending on connected data-source

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

query execution via MapReduce

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

Immediate Consistency

depending on connected data-source

Foreign keys

Referential integrity

Transaction concepts

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

ACID

depending on connected data-source

Concurrency

Support for concurrent manipulation of data

yes

yes, multi-version concurrency control (MVCC)

yes

Durability

Support for making data persistent

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

User concepts

Access control

Access rights for users, groups and roles

based on Apache Sentry and Kerberos

SQL standard access control

More information provided by the system vendor

News

The long journey to Apache Ranger
2 December 2024

The glorious lineup for Trino Summit 2024
22 November 2024

View the SQL basecamps before Trino Summit
21 November 2024

Trino and Javascript?! YES!
18 November 2024

67: Extra speed with Exasol and Trino
30 October 2024

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

Tabular, the vendor-neutral data store based on Apache Iceberg, raises $26M in funding
19 September 2023, SiliconANGLE News

Apache Iceberg Changes Everything: What's Underneath?
28 August 2023, Spiceworks News and Insights

Apache Doris just 'graduated': Why care about this SQL data warehouse
24 June 2022, InfoWorld

Hudi: Uber Engineering’s Incremental Processing Framework on Apache Hadoop
12 March 2017, Uber

1. Big Data Technology Primer - Architecting Modern Data Platforms [Book]
20 September 2018, oreilly.com

provided by Google News

A Guide to Data Analysis in Python with DuckDB
18 November 2024, KDnuggets

My First Billion (of Rows) in DuckDB
1 May 2024, Towards Data Science

MotherDuck Announces Beta Release of pg_duckdb; Brings DuckDB's Analytics Power to PostgreSQL Users
24 October 2024, PR Newswire

DuckDB inside Postgres!!??
27 October 2024, substack.com

PostgreSQL in line for DuckDB-shaped boost in analytics arena
20 August 2024, The Register

provided by Google News

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

Run Trino queries 2.7 times faster with Amazon EMR 6.15.0
22 March 2024, AWS Blog

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

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

Starburst accelerates Trino to ‘Warp Speed’ to accelerate data querying
8 February 2023, VentureBeat

provided by Google News

Share this page