DBMS > chDB vs. EsgynDB vs. Linter

System Properties Comparison chDB vs. EsgynDB vs. Linter

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Editorial information provided by DB-Engines

Name

Description

An embedded SQL OLAP Engine powered by ClickHouse

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

RDBMS for high security requirements

Primary database model

Relational DBMS

Secondary database models

Time Series DBMS

Spatial DBMS

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

Score	0.00
Rank	#383	Overall
	#158	Relational DBMS

Score	0.16
Rank	#329	Overall
	#146	Relational DBMS

Score	0.09
Rank	#346	Overall
	#152	Relational DBMS

Website

github.com/chdb-io/chdb

www.esgyn.cn

linter.ru

Technical documentation

doc.chdb.io

Developer

Esgyn

relex.ru

Initial release

2023

2015

1990

License

Commercial or Open Source

Open Source

Apache Version 2.0

commercial

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

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

Implementation language

C++, Java

C and C++

Server operating systems

server-less

Linux

AIX
Android
BSD
HP Open VMS
iOS
Linux
OS X
VxWorks
Windows

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

Close to ANSI SQL (SQL/JSON + extensions)

yes

APIs and other access methods

ADO.NET
JDBC
ODBC

ADO.NET
JDBC
LINQ
ODBC
OLE DB
Oracle Call Interface (OCI)

Supported programming languages

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

All languages supporting JDBC/ODBC/ADO.Net

C
C#
C++
Java
Perl
PHP
Python
Qt
Ruby
Tcl

Server-side scripts

Stored procedures

Java Stored Procedures

yes

proprietary syntax with the possibility to convert from PL/SQL

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication between multi datacenters

Source-replica replication

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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