DBMS > Apache Pinot vs. ClickHouse vs. HBase vs. LMDB

System Properties Comparison Apache Pinot vs. ClickHouse vs. HBase vs. LMDB

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Editorial information provided by DB-Engines

Name

Description

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

A 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.

Wide-column store based on Apache Hadoop and on concepts of BigTable

A high performant, light-weight, embedded key-value database library

Primary database model

Relational DBMS

Wide column store

Key-value store

Secondary database models

Time Series DBMS

DB-Engines Ranking measures the popularity of database management systems
Trend Chart

Score	0.38
Rank	#275	Overall
	#126	Relational DBMS

Score	15.55
Rank	#38	Overall
	#23	Relational DBMS

Score	27.97
Rank	#26	Overall
	#2	Wide column stores

Score	2.09
Rank	#121	Overall
	#20	Key-value stores

Website

pinot.apache.org

clickhouse.com

hbase.apache.org

www.symas.com/symas-embedded-database-lmdb

Technical documentation

docs.pinot.apache.org

clickhouse.com/docs

hbase.apache.org/book.html

www.lmdb.tech/doc

Developer

Apache Software Foundation and contributors

Clickhouse Inc.

Apache Software Foundation

Apache top-level project, originally developed by Powerset

Symas

Initial release

2015

2016

2008

2011

Current release

1.0.0, September 2023

v24.4.2.141-stable, June 2024

2.3.4, January 2021

0.9.32, January 2024

License

Commercial or Open Source

Open Source

Apache Version 2.0

Open Source

Apache 2.0

Open Source

Apache version 2

Open Source

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

Java

C++

Java

Server operating systems

All OS with a Java JDK11 or higher

FreeBSD
Linux
macOS

Linux
Unix
Windows

using Cygwin

Linux
Unix
Windows

Data scheme

yes

schema-free, schema definition possible

schema-free

Typing

predefined data types such as float or date

yes

options to bring your own types, AVRO

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

SQL

Support of SQL

SQL-like query language

Close to ANSI SQL (SQL/JSON + extensions)

APIs and other access methods

JDBC

gRPC
HTTP REST
JDBC
MySQL wire protocol
ODBC
PostgreSQL wire protocol
Proprietary protocol

Java API
RESTful HTTP API
Thrift

Supported programming languages

Go
Java
Python

3rd party library
C++
Elixir

3rd party library
Go

3rd party library
Java

3rd party library
JavaScript (Node.js)

3rd party library
Kotlin

3rd party library
Nim

3rd party library
Perl

3rd party library
PHP

3rd party library
Python

3rd party library
R

3rd party library
Ruby

3rd party library
Rust
Scala

3rd party library

C
C#
C++
Groovy
Java
PHP
Python
Scala

.Net
C
C++
Clojure
Go
Haskell
Java
JavaScript (Node.js)
Lisp
Lua
MatLab
Nim
Objective C
OCaml
Perl
PHP
Python
R
Ruby
Rust
Swift
Tcl

Server-side scripts

Stored procedures

yes

Coprocessors in Java

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

horizontal partitioning

key based and custom

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

Asynchronous and synchronous physical replication; geographically distributed replicas; support for object storages.

Multi-source replication
Source-replica replication

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Immediate Consistency or Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

Transaction concepts

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

Single row ACID (across millions of columns)

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

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 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.

Access Control Lists (ACL) for RBAC, integration with Apache Ranger for RBAC & ABAC

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