DBMS > ClickHouse vs. FatDB vs. NuoDB vs. Oracle Coherence

System Properties Comparison ClickHouse vs. FatDB vs. NuoDB vs. Oracle Coherence

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Editorial information provided by DB-Engines

Name

FatDB/FatCloud has ceased operations as a company with February 2014. FatDB is discontinued and excluded from the 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 .NET NoSQL DBMS that can integrate with and extend SQL Server.

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

Oracles in-memory data grid solution

Primary database model

Relational DBMS

Document store
Key-value store

Relational DBMS

Key-value store

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	0.94
Rank	#197	Overall
	#92	Relational DBMS

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

Website

clickhouse.com

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

www.oracle.com/java/coherence

Technical documentation

clickhouse.com/docs

doc.nuodb.com

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

Developer

Clickhouse Inc.

FatCloud

Dassault Systèmes

originally NuoDB, Inc.

Oracle

Initial release

2016

2012

2013

2007

Current release

v24.4.2.141-stable, June 2024

14.1, August 2023

License

Commercial or Open Source

Open Source

Apache 2.0

commercial

limited edition free

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.

DoubleCloud: Fully managed ClickHouse alongside best-in-class managed open-source services to build analytics at scale.
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.

Implementation language

C++

Java

Server operating systems

FreeBSD
Linux
macOS

Windows

hosted

Amazon EC2, Windows Azure, SoftLayer
Linux
OS X
Windows

All OS with a Java VM

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)

Via inetgration in SQL Server

yes

APIs and other access methods

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

.NET Client API
LINQ
RESTful HTTP API
RPC
Windows WCF Bindings

ADO.NET
JDBC
ODBC

JCache
JPA
RESTful 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

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

.Net
C++
Java

Server-side scripts

Stored procedures

yes

via applications

Java, SQL

Triggers

yes

via applications

yes

Live Events

Partitioning methods

Methods for storing different data on different nodes

key based and custom

Sharding

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

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

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

selectable replication factor

yes

Managed transparently by NuoDB

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

Immediate Consistency

Eventual Consistency
Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

tunable commit protocol

configurable

Concurrency

Support for concurrent manipulation of data

yes

MVCC

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

Temporary table

yes

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.

Can implement custom security layer via applications

Standard SQL roles/ privileges, Administrative Users

authentification to access the cache via certificates or http basic authentication

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