DBMS > ClickHouse vs. DolphinDB vs. Oracle NoSQL vs. RDF4J vs. TimescaleDB

System Properties Comparison ClickHouse vs. DolphinDB vs. Oracle NoSQL vs. RDF4J vs. TimescaleDB

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.

DolphinDB is a high performance Time Series DBMS. It is integrated with an easy-to-use fully featured programming language and a high-volume high-velocity streaming analytics system. It offers operational simplicity, scalability, fault tolerance, and concurrency.

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

RDF4J is a Java framework for processing RDF data, supporting both memory-based and a disk-based storage.

A time series DBMS optimized for fast ingest and complex queries, based on PostgreSQL

Primary database model

Relational DBMS

Time Series DBMS

Document store
Key-value store
Relational DBMS

RDF store

Time Series DBMS

Secondary database models

Time Series DBMS

Relational DBMS

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

Score	15.55
Rank	#38	Overall
	#23	Relational DBMS

Score	4.03
Rank	#78	Overall
	#6	Time Series DBMS

Score	3.05
Rank	#97	Overall
	#17	Document stores
	#16	Key-value stores
	#50	Relational DBMS

Score	0.74
Rank	#222	Overall
	#9	RDF stores

Score	4.46
Rank	#71	Overall
	#5	Time Series DBMS

Website

clickhouse.com

www.dolphindb.com

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

rdf4j.org

www.timescale.com

Technical documentation

clickhouse.com/docs

docs.dolphindb.cn/en/help200/index.html

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

rdf4j.org/documentation

docs.timescale.com

Developer

Clickhouse Inc.

DolphinDB, Inc

Oracle

Since 2016 officially forked into an Eclipse project, former developer was Aduna Software.

Timescale

Initial release

2016

2018

2011

2004

2017

Current release

v24.4.1.2088-stable, May 2024

v2.00.4, January 2022

24.1, May 2024

2.15.0, May 2024

License

Commercial or Open Source

Open Source

Apache 2.0

commercial

free community version available

Open Source

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

Open Source

Eclipse Distribution License (EDL), v1.0.

Open Source

Apache 2.0

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.

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.
Aiven for Clickhouse: Managed cloud data warehousing with high-speed analytics.

Implementation language

C++

Java

Server operating systems

FreeBSD
Linux
macOS

Linux
Windows

Linux
Solaris SPARC/x86

Linux
OS X
Unix
Windows

Linux
OS X
Windows

Data scheme

yes

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

yes

RDF Schemas

yes

Typing

predefined data types such as float or date

yes

optional

yes

numerics, strings, booleans, arrays, JSON blobs, geospatial dimensions, currencies, binary data, other complex data types

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

Close to ANSI SQL (SQL/JSON + extensions)

SQL-like query language

SQL-like DML and DDL statements

yes

full PostgreSQL SQL syntax

APIs and other access methods

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

JDBC
JSON over HTTP
Kafka
MQTT (Message Queue Telemetry Transport)
ODBC
OPC DA
OPC UA
RabbitMQ
WebSocket

RESTful HTTP API

Java API
RIO

RDF Input/Output
Sail API
SeRQL

Sesame RDF Query Language
Sesame REST HTTP Protocol
SPARQL

ADO.NET
JDBC
native C library
ODBC
streaming API for large objects

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

C#
C++
Go
Java
JavaScript
MatLab
Python
R
Rust

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

Java
PHP
Python

.Net
C
C++
Delphi
Java

JDBC
JavaScript
Perl
PHP
Python
R
Ruby
Scheme
Tcl

Server-side scripts

Stored procedures

yes

user defined functions, PL/pgSQL, PL/Tcl, PL/Perl, PL/Python, PL/Java, PL/PHP, PL/R, PL/Ruby, PL/Scheme, PL/Unix shell

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

key based and custom

horizontal partitioning

Sharding

none

yes, across time and space (hash partitioning) attributes

Replication methods

Methods for redundantly storing data on multiple nodes

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

yes

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

none

Source-replica replication with hot standby and reads on replicas

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

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

yes

configurable

ACID within a storage node (=shard)

ACID

Isolation support depends on the API used

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

in-memory storage is supported as well

yes

In-memory capabilities

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

yes

off heap cache

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.

Administrators, Users, Groups

Access rights for users and roles

fine grained access rights according to SQL-standard

More information provided by the system vendor

We invite representatives of system vendors to contact us for updating and extending the system information,
and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.