DBMS > ClickHouse vs. HarperDB vs. Oracle Rdb vs. Sadas Engine vs. SiriDB

System Properties Comparison ClickHouse vs. HarperDB vs. Oracle Rdb vs. Sadas Engine vs. SiriDB

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.

Ultra-low latency distributed database with an intuitive REST API supporting NoSQL and SQL (including joins). Deployment of functions and databases simultaneously with a consolidated node-level architecture.

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

Open Source Time Series DBMS

Primary database model

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	0.55
Rank	#248	Overall
	#38	Document stores

Score	1.08
Rank	#184	Overall
	#85	Relational DBMS

Score	0.00
Rank	#383	Overall
	#158	Relational DBMS

Score	0.00
Rank	#383	Overall
	#41	Time Series DBMS

Website

clickhouse.com

www.harperdb.io

www.oracle.com/database/technologies/related/rdb.html

www.sadasengine.com

siridb.com

Technical documentation

clickhouse.com/docs

docs.harperdb.io/docs

www.oracle.com/database/technologies/related/rdb-doc.html

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

docs.siridb.com

Developer

Clickhouse Inc.

HarperDB

Oracle, originally developed by Digital Equipment Corporation (DEC)

SADAS s.r.l.

Cesbit

Initial release

2016

2017

1984

2006

2017

Current release

v24.4.1.2088-stable, May 2024

3.1, August 2021

7.4.1.1, 2021

8.0

License

Commercial or Open Source

Open Source

Apache 2.0

commercial

free community edition available

commercial

free trial version available

Open Source

MIT License

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++

Node.js

C++

Server operating systems

FreeBSD
Linux
macOS

Linux
OS X

HP Open VMS

AIX
Linux
Windows

Linux

Data scheme

yes

dynamic schema

Flexible Schema (defined schema, partial schema, schema free)

yes

Typing

predefined data types such as float or date

yes

JSON data types

yes

Numeric data

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 data manipulation statements

yes

APIs and other access methods

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

JDBC
ODBC
React Hooks
RESTful HTTP/JSON API
WebSocket

JDBC
ODBC
Proprietary protocol

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#
C++
ColdFusion
D
Dart
Delphi
Erlang
Go
Haskell
Java
JavaScript (Node.js)
Lisp
MatLab
Objective C
Perl
PHP
PowerShell
Prolog
Python
R
Ruby
Rust
Scala
Swift

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

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

Server-side scripts

Stored procedures

yes

Custom Functions

since release 3.1

Triggers

Partitioning methods

Methods for storing different data on different nodes

key based and custom

A table resides as a whole on one (or more) nodes in a cluster

horizontal partitioning

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

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

yes

the nodes on which a table resides can be defined

none

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

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

Atomic execution of specific operations

yes, on a single node

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

yes, using LMDB

yes

In-memory capabilities

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

yes

managed by 'Learn by Usage'

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.

Access rights for users and roles

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

simple rights management via user accounts

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