DBMS > Apache Pinot vs. ClickHouse vs. Firebase Realtime Database vs. Hypertable

System Properties Comparison Apache Pinot vs. ClickHouse vs. Firebase Realtime Database vs. Hypertable

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Editorial information provided by DB-Engines

Name

Hypertable has stopped its further development with March 2016 and is removed from the DB-Engines ranking.

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.

Cloud-hosted realtime document store. iOS, Android, and JavaScript clients share one Realtime Database instance and automatically receive updates with the newest data.

An open source BigTable implementation based on distributed file systems such as Hadoop

Primary database model

Relational DBMS

Document store

Wide column 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	13.64
Rank	#39	Overall
	#6	Document stores

Website

pinot.apache.org

clickhouse.com

firebase.google.com/products/realtime-database

Technical documentation

docs.pinot.apache.org

clickhouse.com/docs

firebase.google.com/docs/database

Developer

Apache Software Foundation and contributors

Clickhouse Inc.

Google

acquired by Google 2014

Hypertable Inc.

Initial release

2015

2016

2012

2009

Current release

1.0.0, September 2023

v24.4.2.141-stable, June 2024

0.9.8.11, March 2016

License

Commercial or Open Source

Open Source

Apache Version 2.0

Open Source

Apache 2.0

commercial

Open Source

GNU version 3. Commercial license available

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

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Implementation language

Java

C++

Server operating systems

All OS with a Java JDK11 or higher

FreeBSD
Linux
macOS

hosted

Linux
OS X
Windows

an inofficial Windows port is available

Data scheme

yes

schema-free

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

restricted

only exact value or prefix value scans

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

Android
iOS
JavaScript API
RESTful HTTP API

C++ 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

Java
JavaScript
Objective-C

C++
Java
Perl
PHP
Python
Ruby

Server-side scripts

Stored procedures

yes

limited functionality with using 'rules'

Triggers

Callbacks are triggered when data changes

Partitioning methods

Methods for storing different data on different nodes

horizontal partitioning

key based and custom

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

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

selectable replication factor on file system level

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

if the client is offline
Immediate Consistency

if the client is online

Immediate Consistency

Foreign keys

Referential integrity

Transaction concepts

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

yes

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.

yes, based on authentication and database rules

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