DBMS > Apache Drill vs. ClickHouse vs. HugeGraph vs. NuoDB

System Properties Comparison Apache Drill vs. ClickHouse vs. HugeGraph vs. NuoDB

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Editorial information provided by DB-Engines

Name

Description

Schema-free SQL Query Engine for Hadoop, NoSQL and Cloud Storage

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 fast-speed and highly-scalable Graph DBMS

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

Primary database model

Document store
Relational DBMS

Relational DBMS

Graph DBMS

Relational DBMS

Secondary database models

Time Series DBMS

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

Score	1.95
Rank	#127	Overall
	#23	Document stores
	#60	Relational DBMS

Score	16.34
Rank	#38	Overall
	#23	Relational DBMS

Score	0.13
Rank	#336	Overall
	#32	Graph DBMS

Score	0.89
Rank	#198	Overall
	#92	Relational DBMS

Website

drill.apache.org

clickhouse.com

github.com/hugegraph
hugegraph.apache.org

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

Technical documentation

drill.apache.org/docs

clickhouse.com/docs

hugegraph.apache.org/docs

doc.nuodb.com

Developer

Apache Software Foundation

Clickhouse Inc.

Baidu

Dassault Systèmes

originally NuoDB, Inc.

Initial release

2012

2016

2018

2013

Current release

1.20.3, January 2023

v24.4.1.2088-stable, May 2024

0.9

License

Commercial or Open Source

Open Source

Apache Version 2

Open Source

Apache 2.0

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

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Implementation language

C++

Java

C++

Server operating systems

Linux
OS X
Windows

FreeBSD
Linux
macOS

Linux
macOS
Unix

hosted

Amazon EC2, Windows Azure, SoftLayer
Linux
OS X
Windows

Data scheme

schema-free

yes

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

also supports composite index and range index

yes

SQL

Support of SQL

SQL SELECT statement is SQL:2003 compliant

Close to ANSI SQL (SQL/JSON + extensions)

yes

APIs and other access methods

JDBC
ODBC
RESTful HTTP API

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

Java API
RESTful HTTP API
TinkerPop Gremlin

ADO.NET
JDBC
ODBC

Supported programming languages

C++

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

Groovy
Java
Python

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

Server-side scripts

Stored procedures

user defined functions

yes

asynchronous Gremlin script jobs

Java, SQL

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

key based and custom

yes

depending on used storage backend, e.g. Cassandra and HBase

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.

yes

depending on used storage backend, e.g. Cassandra and HBase

yes

Managed transparently by NuoDB

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

via hugegraph-spark

Consistency concepts

Methods to ensure consistency in a distributed system

none

Immediate Consistency

Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

edges in graph

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

Depending on the underlying data source

yes

In-memory capabilities

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

Depending on the underlying data source

yes

Temporary table

User concepts

Access control

Depending on the underlying data source

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.

Users, roles and permissions

Standard SQL roles/ privileges, Administrative Users

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