DBMS > Databend vs. EsgynDB vs. Microsoft Azure SQL Database vs. Oracle Coherence

System Properties Comparison Databend vs. EsgynDB vs. Microsoft Azure SQL Database vs. Oracle Coherence

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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

Database as a Service offering with high compatibility to Microsoft SQL Server

Oracles in-memory data grid solution

Primary database model

Relational DBMS

Key-value store

Secondary database models

Document store
Graph DBMS
Spatial DBMS

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

Score	0.34
Rank	#283	Overall
	#130	Relational DBMS

Score	0.25
Rank	#312	Overall
	#138	Relational DBMS

Score	76.78
Rank	#16	Overall
	#11	Relational DBMS

Score	1.97
Rank	#129	Overall
	#22	Key-value stores

Website

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

www.esgyn.cn

azure.microsoft.com/en-us/products/azure-sql/database

www.oracle.com/java/coherence

Technical documentation

docs.databend.com

docs.microsoft.com/en-us/azure/azure-sql

docs.oracle.com/en/middleware/standalone/coherence

Developer

Databend Labs

Esgyn

Microsoft

Oracle

Initial release

2021

2015

2010

2007

Current release

1.0.59, April 2023

V12

14.1, August 2023

License

Commercial or Open Source

Open Source

Apache Version 2.0

commercial

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.

Implementation language

Rust

C++, Java

C++

Java

Server operating systems

hosted
Linux
macOS

Linux

hosted

All OS with a Java VM

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.

yes

Secondary indexes

yes

SQL

Support of SQL

yes

APIs and other access methods

CLI Client
JDBC
RESTful HTTP API

ADO.NET
JDBC
ODBC

JCache
JPA
RESTful HTTP API

Supported programming languages

Go
Java
JavaScript (Node.js)
Python
Rust

All languages supporting JDBC/ODBC/ADO.Net

.Net
C#
Java
JavaScript (Node.js)
PHP
Python
Ruby

.Net
C++
Java

Server-side scripts

Stored procedures

Java Stored Procedures

Transact SQL

Triggers

yes

Live Events

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

none

Multi-source replication between multi datacenters

yes, with always 3 replicas available

yes, with selectable consistency 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
Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

yes

ACID

configurable

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

optionally

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

authentification to access the cache via certificates or http basic authentication

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More resources

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