DB-EnginesextremeDB - Data management wherever you need itEnglish
Deutsch
Knowledge Base of Relational and NoSQL Database Management Systemsprovided by Redgate Software

DBMS > Apache Hive vs. Apache Pinot vs. ClickHouse

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

Please select another system to include it in the comparison.

Editorial information provided by DB-Engines
NameApache Hive  Xexclude from comparisonApache Pinot  Xexclude from comparisonClickHouse  Xexclude from comparison
Descriptiondata warehouse software for querying and managing large distributed datasets, built on HadoopRealtime distributed OLAP datastore, designed to answer OLAP queries with low latencyA high-performance, column-oriented SQL DBMS for online analytical processing (OLAP) that uses all available system resources to their full potential to process each analytical query as fast as possible. It is available as both an open-source software and a cloud offering.
Primary database modelRelational DBMSRelational DBMSRelational DBMS
Secondary database modelsTime Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score75.77
Rank#16  Overall
#11  Relational DBMS
Score0.50
Rank#248  Overall
#117  Relational DBMS
Score18.77
Rank#31  Overall
#19  Relational DBMS
Websitehive.apache.orgpinot.apache.orgclickhouse.com
Technical documentationcwiki.apache.org/­confluence/­display/­Hive/­Homedocs.pinot.apache.orgclickhouse.com/­docs
DeveloperApache Software Foundation infoinitially developed by FacebookApache Software Foundation and contributorsClickhouse Inc.
Initial release201220152016
Current release3.1.3, April 20221.0.0, September 2023v24.6.2.17-stable, July 2024
License infoCommercial or Open SourceOpen Source infoApache Version 2Open Source infoApache Version 2.0Open Source infoApache 2.0
Cloud-based only infoOnly available as a cloud servicenonono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaJavaC++
Server operating systemsAll OS with a Java VMAll OS with a Java JDK11 or higherFreeBSD
Linux
macOS
Data schemeyesyesyes
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.no
Secondary indexesyesyes
SQL infoSupport of SQLSQL-like DML and DDL statementsSQL-like query languageClose to ANSI SQL (SQL/JSON + extensions)
APIs and other access methodsJDBC
ODBC
Thrift
JDBCgRPC
HTTP REST
JDBC
MySQL wire protocol
ODBC
PostgreSQL wire protocol
Proprietary protocol
Supported programming languagesC++
Java
PHP
Python
Go
Java
Python
C# info3rd party library
C++
Elixir info3rd party library
Go info3rd party library
Java info3rd party library
JavaScript (Node.js) info3rd party library
Kotlin info3rd party library
Nim info3rd party library
Perl info3rd party library
PHP info3rd party library
Python info3rd party library
R info3rd party library
Ruby info3rd party library
Rust
Scala info3rd party library
Server-side scripts infoStored proceduresyes infouser defined functions and integration of map-reduceyes
Triggersnono
Partitioning methods infoMethods for storing different data on different nodesShardinghorizontal partitioningkey based and custom
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factorAsynchronous and synchronous physical replication; geographically distributed replicas; support for object storages.
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infoquery execution via MapReduceno
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual ConsistencyImmediate Consistency
Foreign keys infoReferential integritynono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanono
Concurrency infoSupport for concurrent manipulation of datayesyes
Durability infoSupport for making data persistentyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yes
User concepts infoAccess controlAccess rights for users, groups and rolesAccess rights for users and roles. Column and row based policies. Quotas and resource limits. Pluggable authentication with LDAP and Kerberos. Password based, X.509 certificate, and SSH key authentication.

More information provided by the system vendor

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
Apache HiveApache PinotClickHouse
DB-Engines blog posts

DB-Engines shares Q1 2025 database industry rankings and top climbers: Snowflake and PostgreSQL trending
1 May 2025, DB-Engines

show all

Recent citations in the news

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

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

What Is Apache Iceberg?
18 December 2024, IBM

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

Mastering Hadoop, Part 3: Hadoop Ecosystem: Get the most out of your cluster
14 March 2025, Towards Data Science

provided by Google News

Deploy real-time analytics with StarTree for managed Apache Pinot on AWS
13 March 2025, Amazon Web Services

Microsoft Warns of Attackers Exploiting Misconfigured Apache Pinot Installations
6 May 2025, SecurityWeek

Misconfigured Apache Pinot instances under attack
7 May 2025, SC Media

Serving Millions of Apache Pinotâ„¢ Queries with Neutrino
11 December 2024, Uber

Apache Pinot Brings Real Time Analysis to Columnar Data
13 December 2024, The New Stack

provided by Google News

Wiz Research Uncovers Exposed DeepSeek Database Leaking Sensitive Information, Including Chat History
29 January 2025, wiz.io

Snowflake Challenger ClickHouse Targets $6 Billion Valuation
9 May 2025, The Information

DeepSeek Exposed Database Leaks Sensitive Data
30 January 2025, Infosecurity Magazine

DeepSeek AI Database Exposed: Over 1 Million Log Lines, Secret Keys Leaked
30 January 2025, The Hacker News

ClickHouse Acquires HyperDX to Accelerate the Future of Observability
13 March 2025, Business Wire

provided by Google News



Share this page

Featured Products

Milvus logo

Vector database designed for GenAI, fully equipped for enterprise implementation.
Try Managed Milvus for Free

Neo4j logo

See for yourself how a graph database can make your life easier.
Use Neo4j online for free.

RaimaDB logo

RaimaDB, embedded database for mission-critical applications. When performance, footprint and reliability matters.
Try RaimaDB for free.

SingleStore logo

The data platform to build your intelligent applications.
Try it free.

Datastax Astra logo

Bring all your data to Generative AI applications with vector search enabled by the most scalable
vector database available.
Try for Free

Present your product here