DBMS > ClickHouse vs. GeoMesa vs. HugeGraph vs. NuoDB vs. Quasardb

System Properties Comparison ClickHouse vs. GeoMesa vs. HugeGraph vs. NuoDB vs. Quasardb

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.

GeoMesa is a distributed spatio-temporal DBMS based on various systems as storage layer.

A fast-speed and highly-scalable Graph DBMS

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

Distributed, high-performance timeseries database

Primary database model

Secondary database models

Time Series DBMS

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

Score	15.55
Rank	#38	Overall
	#23	Relational DBMS

Score	0.86
Rank	#205	Overall
	#4	Spatial DBMS

Score	0.17
Rank	#335	Overall
	#31	Graph DBMS

Score	0.94
Rank	#197	Overall
	#92	Relational DBMS

Score	0.21
Rank	#322	Overall
	#29	Time Series DBMS

Website

clickhouse.com

www.geomesa.org

github.com/hugegraph
hugegraph.apache.org

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

quasar.ai

Technical documentation

clickhouse.com/docs

www.geomesa.org/documentation/stable/user/index.html

hugegraph.apache.org/docs

doc.nuodb.com

doc.quasar.ai/master

Developer

Clickhouse Inc.

CCRi and others

Baidu

Dassault Systèmes

originally NuoDB, Inc.

quasardb

Initial release

2016

2014

2018

2013

2009

Current release

v24.4.1.2088-stable, May 2024

5.0.0, May 2024

0.9

3.14.1, January 2024

License

Commercial or Open Source

Open Source

Apache 2.0

Open Source

Apache License 2.0

Open Source

Apache Version 2.0

commercial

limited edition free

commercial

Free community edition, Non-profit organizations and non-commercial usage are eligible for free licenses

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.

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Implementation language

C++

Scala

Java

C++

Server operating systems

FreeBSD
Linux
macOS

Linux
macOS
Unix

hosted

Amazon EC2, Windows Azure, SoftLayer
Linux
OS X
Windows

BSD
Linux
OS X
Windows

Data scheme

yes

schema-free

Typing

predefined data types such as float or date

yes

integer and binary

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

with tags

SQL

Support of SQL

Close to ANSI SQL (SQL/JSON + extensions)

yes

SQL-like query language

APIs and other access methods

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

Java API
RESTful HTTP API
TinkerPop Gremlin

ADO.NET
JDBC
ODBC

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

Groovy
Java
Python

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

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

Server-side scripts

Stored procedures

yes

asynchronous Gremlin script jobs

Java, SQL

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

key based and custom

depending on storage layer

yes

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

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

Sharding

consistent hashing

Replication methods

Methods for redundantly storing data on multiple nodes

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

depending on storage layer

yes

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

yes

Managed transparently by NuoDB

Source-replica replication with selectable replication factor

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

via hugegraph-spark

with Hadoop integration

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

depending on storage layer

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

ACID

Concurrency

Support for concurrent manipulation of data

yes

MVCC

yes

Durability

Support for making data persistent

yes

by using LevelDB

In-memory capabilities

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

yes

depending on storage layer

yes

Temporary table

yes

Transient mode

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.

yes

depending on the DBMS used for storage

Users, roles and permissions

Standard SQL roles/ privileges, Administrative Users

Cryptographically strong user authentication and audit trail

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