DBMS > ClickHouse vs. Datomic vs. Oracle NoSQL vs. Sadas Engine

System Properties Comparison ClickHouse vs. Datomic vs. Oracle NoSQL vs. Sadas Engine

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Editorial information provided by DB-Engines

Name

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.

Datomic builds on immutable values, supports point-in-time queries and uses 3rd party systems for durability

A multi-model, scalable, distributed NoSQL database, designed to provide highly reliable, flexible, and available data management across a configurable set of storage nodes

SADAS Engine is a columnar DBMS specifically designed for high performance in data warehouse environments

Primary database model

Relational DBMS

Document store
Key-value store
Relational DBMS

Relational DBMS

Secondary database models

Time Series DBMS

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

Score	16.34
Rank	#38	Overall
	#23	Relational DBMS

Score	1.59
Rank	#150	Overall
	#69	Relational DBMS

Score	2.95
Rank	#100	Overall
	#17	Document stores
	#17	Key-value stores
	#50	Relational DBMS

Score	0.00
Rank	#383	Overall
	#158	Relational DBMS

Website

clickhouse.com

www.datomic.com

www.oracle.com/database/nosql/technologies/nosql

www.sadasengine.com

Technical documentation

clickhouse.com/docs

docs.datomic.com

docs.oracle.com/en/database/other-databases/nosql-database/index.html

www.sadasengine.com/en/sadas-engine-download-free-trial-and-documentation/#documentation

Developer

Clickhouse Inc.

Cognitect

Oracle

SADAS s.r.l.

Initial release

2016

2012

2011

2006

Current release

v24.4.1.2088-stable, May 2024

1.0.6735, June 2023

23.3, December 2023

8.0

License

Commercial or Open Source

Open Source

Apache 2.0

commercial

limited edition free

Open Source

Proprietary for Enterprise Edition (Oracle Database EE license has Oracle NoSQL database EE covered: details)

commercial

free trial version available

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, Clojure

Java

C++

Server operating systems

FreeBSD
Linux
macOS

All OS with a Java VM

Linux
Solaris SPARC/x86

AIX
Linux
Windows

Data scheme

yes

Support Fixed schema and Schema-less deployment with the ability to interoperate between them.

yes

Typing

predefined data types such as float or date

yes

optional

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)

SQL-like DML and DDL statements

yes

APIs and other access methods

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

RESTful HTTP API

JDBC
ODBC
Proprietary protocol

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

Clojure
Java

C
C#
Go
Java
JavaScript (Node.js)
Python

.Net
C
C#
C++
Groovy
Java
PHP
Python

Server-side scripts

Stored procedures

yes

Transaction Functions

Triggers

By using transaction functions

Partitioning methods

Methods for storing different data on different nodes

key based and custom

none

But extensive use of caching in the application peers

Sharding

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

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

none

But extensive use of caching in the application peers

Electable source-replica replication per shard. Support distributed global deployment with Multi-region table feature

none

MapReduce

Offers an API for user-defined Map/Reduce methods

with Hadoop integration

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency
Immediate Consistency

depending on configuration

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

configurable

ACID within a storage node (=shard)

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

using external storage systems (e.g. Cassandra, DynamoDB, PostgreSQL, Couchbase and others)

yes

In-memory capabilities

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

yes

recommended only for testing and development

yes

off heap cache

yes

managed by 'Learn by Usage'

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.

Access rights for users and roles

Access rights for users, groups and roles according to SQL-standard

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