DBMS > Databend vs. EsgynDB vs. H2GIS

System Properties Comparison Databend vs. EsgynDB vs. H2GIS

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Editorial information provided by DB-Engines

Name

Description

An open-source, elastic, and workload-aware cloud data warehouse designed to meet businesses' massive-scale analytics needs at low cost and with low complexity

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

Spatial extension of H2

Primary database model

Relational DBMS

Spatial DBMS

Secondary database models

Relational DBMS

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

Score	0.30
Rank	#287	Overall
	#130	Relational DBMS

Score	0.16
Rank	#329	Overall
	#146	Relational DBMS

Score	0.00
Rank	#383	Overall
	#7	Spatial DBMS

Website

github.com/datafuselabs/databend
www.databend.com

www.esgyn.cn

www.h2gis.org

Technical documentation

docs.databend.com

www.h2gis.org/docs/home

Developer

Databend Labs

Esgyn

CNRS

Initial release

2021

2015

2013

Current release

1.0.59, April 2023

License

Commercial or Open Source

Open Source

Apache Version 2.0

commercial

Open Source

LGPL 3.0

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

Rust

C++, Java

Java

Server operating systems

hosted
Linux
macOS

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

yes

APIs and other access methods

CLI Client
JDBC
RESTful HTTP API

ADO.NET
JDBC
ODBC

Supported programming languages

Go
Java
JavaScript (Node.js)
Python
Rust

All languages supporting JDBC/ODBC/ADO.Net

Java

Server-side scripts

Stored procedures

Java Stored Procedures

yes

based on H2

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

none

Multi-source replication between multi datacenters

yes

based on H2

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

yes

ACID

Concurrency

Support for concurrent manipulation of data

yes

yes, multi-version concurrency control (MVCC)

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

Users with fine-grained authorization concept, user roles

fine grained access rights according to SQL-standard

yes

based on H2

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