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DBMS > Apache Druid vs. Apache Impala vs. Trino

System Properties Comparison Apache Druid vs. Apache Impala vs. Trino

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Editorial information provided by DB-Engines
NameApache Druid  Xexclude from comparisonApache Impala  Xexclude from comparisonTrino  Xexclude from comparison
DescriptionOpen-source analytics data store designed for sub-second OLAP queries on high dimensionality and high cardinality dataAnalytic DBMS for HadoopFast distributed SQL query engine for big data analytics. Forked from Presto and originally named PrestoSQL
Primary database modelRelational DBMS
Time Series DBMS
Relational DBMSRelational DBMS
Secondary database modelsDocument storeDocument store
Key-value store
Spatial DBMS
Search engine
Time Series DBMS
Wide column store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score3.18
Rank#84  Overall
#45  Relational DBMS
#7  Time Series DBMS
Score11.68
Rank#41  Overall
#25  Relational DBMS
Score5.34
Rank#60  Overall
#34  Relational DBMS
Websitedruid.apache.orgimpala.apache.orgtrino.io
Technical documentationdruid.apache.org/­docs/­latest/­designimpala.apache.org/­impala-docs.htmltrino.io/­broadcast
trino.io/­docs/­current
DeveloperApache Software Foundation and contributorsApache Software Foundation infoApache top-level project, originally developed by ClouderaTrino Software Foundation
Initial release201220132012 info2020 rebranded from PrestoSQL
Current release30.0.0, June 20244.1.0, June 2022
License infoCommercial or Open SourceOpen Source infoApache license v2Open Source infoApache Version 2Open Source infoApache Version 2.0
Cloud-based only infoOnly available as a cloud servicenonono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaC++Java
Server operating systemsLinux
OS X
Unix
LinuxLinux
macOS infofor devlopment
Data schemeyes infoschema-less columns are supportedyesyes
Typing infopredefined data types such as float or dateyesyesyes
XML support infoSome form of processing data in XML format, e.g. support for XML data structures, and/or support for XPath, XQuery or XSLT.nonono
Secondary indexesyesyesdepending on connected data-source
SQL infoSupport of SQLSQL for queryingSQL-like DML and DDL statementsyes
APIs and other access methodsJDBC
RESTful HTTP/JSON API
JDBC
ODBC
JDBC
RESTful HTTP API
Trino CLI
Supported programming languagesClojure
JavaScript
PHP
Python
R
Ruby
Scala
All languages supporting JDBC/ODBCGo
Java
JavaScript (Node.js)
Python
R
Ruby
Server-side scripts infoStored proceduresnoyes infouser defined functions and integration of map-reduceyes, depending on connected data-source
Triggersnonono
Partitioning methods infoMethods for storing different data on different nodesSharding infomanual/auto, time-basedShardingdepending on connected data-source
Replication methods infoMethods for redundantly storing data on multiple nodesyes, via HDFS, S3 or other storage enginesselectable replication factordepending on connected data-source
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyes infoquery execution via MapReduceno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual Consistencydepending on connected data-source
Foreign keys infoReferential integritynonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanonodepending on connected data-source
Concurrency infoSupport for concurrent manipulation of datayesyesyes
Durability infoSupport for making data persistentyesyesdepending on connected data-source
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nono
User concepts infoAccess controlRBAC using LDAP or Druid internals for users and groups for read/write by datasource and systemAccess rights for users, groups and roles infobased on Apache Sentry and KerberosSQL standard access control
More information provided by the system vendor
Apache DruidApache ImpalaTrino
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
Apache DruidApache ImpalaTrino
Recent citations in the news

Imply Announces the Availability of Imply Polaris, a Database-as-a-Service Built from Apache Druid, on Microsoft Azure
26 June 2024, Business Wire

How to connect DataGrip to Apache Druid
18 October 2021, Towards Data Science

Apache Druid Takes Its Place In The Pantheon Of Databases
16 June 2022, The Next Platform

Apache Druid 25.0 Delivers Multi-Stage Query Engine and Kubernetes Task Management
19 January 2023, infoq.com

Streaming fast: Druid’s event-based database practices for sub-second trillion row response
21 February 2022, Blocks and Files

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Apache Impala becomes Top-Level Project
28 November 2017, SD Times

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

Cloudera brings Apache Iceberg data lake format to its Data Platform
30 June 2022, SiliconANGLE

Apache Doris Analytical Database Graduates from Apache Incubator
20 June 2022, datanami.com

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

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How to Deploy MinIO and Trino with Kubernetes
23 May 2024, HackerNoon

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

The Perfect AI Storage: Trino From Facebook And Iceberg From Netflix?
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 (AWS)

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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