DBMS > Apache Hive vs. Apache Pinot vs. Trino

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

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Editorial information provided by DB-Engines

Name

Description

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

Realtime distributed OLAP datastore, designed to answer OLAP queries with low latency

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	75.77
Rank	#16	Overall
	#11	Relational DBMS

Score	0.50
Rank	#248	Overall
	#117	Relational DBMS

Score	5.34
Rank	#60	Overall
	#34	Relational DBMS

Website

hive.apache.org

pinot.apache.org

trino.io

Technical documentation

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

docs.pinot.apache.org

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

Developer

Apache Software Foundation

initially developed by Facebook

Apache Software Foundation and contributors

Trino Software Foundation

Initial release

2012

2015

2012

2020 rebranded from PrestoSQL

Current release

3.1.3, April 2022

1.0.0, September 2023

License

Commercial or Open Source

Open Source

Apache Version 2

Open Source

Apache Version 2.0

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

All OS with a Java VM

All OS with a Java JDK11 or higher

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

SQL-like query language

yes

APIs and other access methods

JDBC
ODBC
Thrift

JDBC

JDBC
RESTful HTTP API
Trino CLI

Supported programming languages

C++
Java
PHP
Python

Go
Java
Python

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

horizontal partitioning

depending on connected data-source

Replication methods

Methods for redundantly storing data on multiple nodes

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

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

User concepts

Access control

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

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Hive Tutorial: Working with Data in Hadoop
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7 May 2025, SC Media

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

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30 April 2024, The Next Platform

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

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provided by Google News

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