DBMS > Apache Doris vs. Apache Hive vs. Trino

System Properties Comparison Apache Doris vs. Apache Hive vs. Trino

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Editorial information provided by DB-Engines

Name

Description

An MPP-based analytics DBMS embracing the MySQL protocol

data warehouse software for querying and managing large distributed datasets, built on Hadoop

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
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	0.51
Rank	#244	Overall
	#115	Relational DBMS

Score	72.65
Rank	#18	Overall
	#12	Relational DBMS

Score	5.18
Rank	#60	Overall
	#34	Relational DBMS

Website

doris.apache.org
github.com/apache/doris

hive.apache.org

trino.io

Technical documentation

github.com/apache/doris/wiki

cwiki.apache.org/confluence/display/Hive/Home

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

Developer

Apache Software Foundation, originally contributed from Baidu

Apache Software Foundation

initially developed by Facebook

Trino Software Foundation

Initial release

2017

2012

2020 rebranded from PrestoSQL

Current release

1.2.2, February 2023

3.1.3, April 2022

License

Commercial or Open Source

Open Source

Apache Version 2.0

Open Source

Apache Version 2

Open Source

Apache Version 2.0

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

Java

Server operating systems

Linux

All OS with a Java VM

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

yes

SQL-like DML and DDL statements

yes

APIs and other access methods

JDBC
MySQL client

JDBC
ODBC
Thrift

JDBC
RESTful HTTP API
Trino CLI

Supported programming languages

Java

C++
Java
PHP
Python

Go
Java
JavaScript (Node.js)
Python
R
Ruby

Server-side scripts

Stored procedures

user defined functions

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

horizontal partitioning

Sharding

depending on connected data-source

Replication methods

Methods for redundantly storing data on multiple nodes

none

selectable replication factor

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

Immediate Consistency

Eventual Consistency

depending on connected data-source

Foreign keys

Referential integrity

Transaction concepts

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

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

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

User concepts

Access control

fine grained access rights according to SQL-standard

Access rights for users, groups and roles

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

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More resources

Recent citations in the news

Migrating from ClickHouse to Apache Doris: Boosting OLAP Performance
9 October 2023, HackerNoon

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

Snowflake Releases Polaris Catalog: Transforming Data Interoperability with Open Source Apache Iceberg Integration
4 June 2024, MarkTechPost

How to Digest 15 Billion Logs Per Day and Keep Big Queries Within 1 Second
1 September 2023, KDnuggets

Apache EventMesh Reaches Top Level Status
17 April 2023, i-programmer.info

provided by Google News

Hive Tutorial: Working with Data in Hadoop
2 April 2025, Simplilearn.com

Design patterns for implementing Hive Metastore for Amazon EMR on EKS
28 February 2025, Amazon Web Services

What Is Apache Iceberg?
18 December 2024, IBM

Pinot for Low-Latency Offline Table Analytics
29 August 2024, Uber

Must-Know Techniques for Handling Big Data in Hive
14 August 2024, Towards Data Science

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

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

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