DBMS > ClickHouse vs. Ehcache vs. EsgynDB vs. NuoDB vs. Yanza

System Properties Comparison ClickHouse vs. Ehcache vs. EsgynDB vs. NuoDB vs. Yanza

Editorial information provided by DB-Engines

Name

Yanza seems to be discontinued. Therefore it is excluded from the DB-Engines Ranking.

Description

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.

A widely adopted Java cache with tiered storage options

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

NuoDB is a webscale distributed database that supports SQL and ACID transactions

Time Series DBMS for IoT Applications

Primary database model

Secondary database models

Time Series DBMS

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

Score	15.55
Rank	#38	Overall
	#23	Relational DBMS

Score	4.64
Rank	#68	Overall
	#8	Key-value stores

Score	0.25
Rank	#312	Overall
	#138	Relational DBMS

Score	0.94
Rank	#197	Overall
	#92	Relational DBMS

Website

clickhouse.com

www.ehcache.org

www.esgyn.cn

www.3ds.com/nuodb-distributed-sql-database

yanza.com

Technical documentation

clickhouse.com/docs

www.ehcache.org/documentation

doc.nuodb.com

Developer

Clickhouse Inc.

Terracotta Inc, owned by Software AG

Esgyn

Dassault Systèmes

originally NuoDB, Inc.

Yanza

Initial release

2016

2009

2015

2013

2015

Current release

v24.4.1.2088-stable, May 2024

3.10.0, March 2022

License

Commercial or Open Source

Open Source

Apache 2.0

Open Source

Apache Version 2; commercial licenses available

commercial

limited edition free

commercial

free version available

Cloud-based only

Only available as a cloud service

but mainly used as a service provided by Yanza

DBaaS offerings (sponsored links)

Database as a Service

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

Aiven for Clickhouse: Managed cloud data warehousing with high-speed analytics.
ClickHouse Cloud: Get the performance you love from open source ClickHouse in a serverless offering that takes care of the details so you can spend more time getting insight out of the fastest database on earth.
DoubleCloud: Fully managed ClickHouse alongside best-in-class managed open-source services to build analytics at scale.

Implementation language

C++

Java

C++, Java

C++

Server operating systems

FreeBSD
Linux
macOS

All OS with a Java VM

Linux

hosted

Amazon EC2, Windows Azure, SoftLayer
Linux
OS X
Windows

Windows

Data scheme

yes

schema-free

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

SQL

Support of SQL

Close to ANSI SQL (SQL/JSON + extensions)

yes

APIs and other access methods

gRPC
HTTP REST
JDBC
MySQL wire protocol
ODBC
PostgreSQL wire protocol
Proprietary protocol

JCache

ADO.NET
JDBC
ODBC

HTTP API

Supported programming languages

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

All languages supporting JDBC/ODBC/ADO.Net

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

any language that supports HTTP calls

Server-side scripts

Stored procedures

yes

Java Stored Procedures

Java, SQL

Triggers

yes

Cache Event Listeners

yes

Timer and event based

Partitioning methods

Methods for storing different data on different nodes

key based and custom

Sharding

by using Terracotta Server

Sharding

data is dynamically stored/cached on the nodes where it is read/written

none

Replication methods

Methods for redundantly storing data on multiple nodes

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

yes

by using Terracotta Server

Multi-source replication between multi datacenters

yes

Managed transparently by NuoDB

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Tunable Consistency (Strong, Eventual, Weak)

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

yes

supports JTA and can work as an XA resource

ACID

tunable commit protocol

Concurrency

Support for concurrent manipulation of data

yes

MVCC

yes

Durability

Support for making data persistent

yes

using a tiered cache-storage approach

yes

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

yes

Temporary table

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.

fine grained access rights according to SQL-standard

Standard SQL roles/ privileges, Administrative Users

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