DBMS > ClickHouse vs. Dgraph vs. Graph Engine vs. NSDb vs. NuoDB

System Properties Comparison ClickHouse vs. Dgraph vs. Graph Engine vs. NSDb vs. NuoDB

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.

Distributed and scalable native Graph DBMS

A distributed in-memory data processing engine, underpinned by a strongly-typed RAM store and a general distributed computation engine

Scalable, High-performance Time Series DBMS designed for Real-time Analytics on top of Kubernetes

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

Primary database model

Relational DBMS

Graph DBMS

Graph DBMS
Key-value store

Time Series 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	1.45
Rank	#156	Overall
	#15	Graph DBMS

Score	0.61
Rank	#240	Overall
	#21	Graph DBMS
	#35	Key-value stores

Score	0.00
Rank	#383	Overall
	#41	Time Series DBMS

Score	0.89
Rank	#198	Overall
	#92	Relational DBMS

Website

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

Technical documentation

clickhouse.com/docs

dgraph.io/docs

www.graphengine.io/docs/manual

nsdb.io/Architecture

doc.nuodb.com

Developer

Clickhouse Inc.

Dgraph Labs, Inc.

Microsoft

Dassault Systèmes

originally NuoDB, Inc.

Initial release

2016

2010

2017

2013

Current release

v24.4.1.2088-stable, May 2024

License

Commercial or Open Source

Open Source

Apache 2.0

Open Source

Apache 2.0

Open Source

MIT License

Open Source

Apache Version 2.0

commercial

limited edition free

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++

.NET and C

Java, Scala

C++

Server operating systems

FreeBSD
Linux
macOS

Linux
OS X
Windows

.NET

Linux
macOS

hosted

Amazon EC2, Windows Azure, SoftLayer
Linux
OS X
Windows

Data scheme

yes

schema-free

yes

Typing

predefined data types such as float or date

yes

yes: int, bigint, decimal, string

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

all fields are automatically indexed

yes

SQL

Support of SQL

Close to ANSI SQL (SQL/JSON + extensions)

SQL-like query language

yes

APIs and other access methods

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

GraphQL query language
gRPC (using protocol buffers) API
HTTP API

RESTful HTTP API

gRPC
HTTP REST
WebSocket

ADO.NET
JDBC
ODBC

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 (Node.js)
PHP
Python
Ruby

C#
C++
F#
Visual Basic

Java
Scala

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

Server-side scripts

Stored procedures

yes

Java, SQL

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

key based and custom

yes

horizontal partitioning

Sharding

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

Replication methods

Methods for redundantly storing data on multiple nodes

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

Synchronous replication via Raft

yes

Managed transparently by NuoDB

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

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

Concurrency

Support for concurrent manipulation of data

yes

MVCC

Durability

Support for making data persistent

yes

optional: either by committing a write-ahead log (WAL) to the local persistent storage or by dumping the memory to a persistent storage

Using Apache Lucene

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.

Planned for future releases

Standard SQL roles/ privileges, Administrative Users

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