DBMS > Apache Pinot vs. chDB vs. EsgynDB

System Properties Comparison Apache Pinot vs. chDB vs. EsgynDB

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Editorial information provided by DB-Engines

Name

Description

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

An embedded SQL OLAP Engine powered by ClickHouse

Enterprise-class SQL-on-Hadoop solution, powered by Apache Trafodion

Primary database model

Relational DBMS

Secondary database models

Time Series DBMS

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

Score	0.35
Rank	#274	Overall
	#128	Relational DBMS

Score	0.05
Rank	#358	Overall
	#152	Relational DBMS

Score	0.15
Rank	#325	Overall
	#144	Relational DBMS

Website

pinot.apache.org

github.com/chdb-io/chdb

www.esgyn.cn

Technical documentation

docs.pinot.apache.org

doc.chdb.io

Developer

Apache Software Foundation and contributors

Esgyn

Initial release

2015

2023

2015

Current release

1.0.0, September 2023

License

Commercial or Open Source

Open Source

Apache Version 2.0

Open Source

Apache Version 2.0

commercial

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

server-less

Linux

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

SQL

Support of SQL

SQL-like query language

Close to ANSI SQL (SQL/JSON + extensions)

yes

APIs and other access methods

JDBC

ADO.NET
JDBC
ODBC

Supported programming languages

Go
Java
Python

Bun
C
C++
Go
JavaScript (Node.js)
Python
Rust

All languages supporting JDBC/ODBC/ADO.Net

Server-side scripts

Stored procedures

Java Stored Procedures

Triggers

Partitioning methods

Methods for storing different data on different nodes

horizontal partitioning

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication between multi datacenters

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

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.

User concepts

Access control

fine grained access rights according to SQL-standard

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More resources

Recent citations in the news

Build a real-time analytics solution with Apache Pinot on AWS
6 August 2024, AWS Blog

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

StarTree broadly enhances Apache Pinot-based analytics platform
8 May 2024, SiliconANGLE News

Open source Apache Pinot advances as StarTree boosts real-time analytics and observability
8 May 2024, VentureBeat

StarTree Makes Observability Case for Apache Pinot Database
8 May 2024, DevOps.com

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