DBMS > ClickHouse vs. EsgynDB vs. H2GIS vs. NuoDB vs. XTDB

System Properties Comparison ClickHouse vs. EsgynDB vs. H2GIS vs. NuoDB vs. XTDB

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.

Enterprise-class SQL-on-Hadoop solution, powered by Apache Trafodion

Spatial extension of H2

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

A general purpose database with bitemporal SQL and Datalog and graph queries

Primary database model

Secondary database models

Time Series DBMS

Relational DBMS

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

Score	16.34
Rank	#38	Overall
	#23	Relational DBMS

Score	0.16
Rank	#329	Overall
	#146	Relational DBMS

Score	0.00
Rank	#383	Overall
	#7	Spatial DBMS

Score	0.89
Rank	#198	Overall
	#92	Relational DBMS

Score	0.11
Rank	#343	Overall
	#46	Document stores

Website

clickhouse.com

www.esgyn.cn

www.h2gis.org

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

github.com/xtdb/xtdb
www.xtdb.com

Technical documentation

clickhouse.com/docs

www.h2gis.org/docs/home

doc.nuodb.com

www.xtdb.com/docs

Developer

Clickhouse Inc.

Esgyn

CNRS

Dassault Systèmes

originally NuoDB, Inc.

Juxt Ltd.

Initial release

2016

2015

2013

2019

Current release

v24.4.1.2088-stable, May 2024

1.19, September 2021

License

Commercial or Open Source

Open Source

Apache 2.0

commercial

Open Source

LGPL 3.0

commercial

limited edition free

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

Implementation language

C++

C++, Java

Java

C++

Clojure

Server operating systems

FreeBSD
Linux
macOS

Linux

hosted

Amazon EC2, Windows Azure, SoftLayer
Linux
OS X
Windows

All OS with a Java 8 (and higher) VM
Linux

Data scheme

yes

schema-free

Typing

predefined data types such as float or date

yes

yes, extensible-data-notation format

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)

yes

limited SQL, making use of Apache Calcite

APIs and other access methods

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

ADO.NET
JDBC
ODBC

HTTP REST
JDBC

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

All languages supporting JDBC/ODBC/ADO.Net

Java

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

Clojure
Java

Server-side scripts

Stored procedures

yes

Java Stored Procedures

yes

based on H2

Java, SQL

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

key based and custom

Sharding

none

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

none

Replication methods

Methods for redundantly storing data on multiple nodes

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

Multi-source replication between multi datacenters

yes

based on H2

yes

Managed transparently by NuoDB

yes, each node contains all data

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

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

ACID

tunable commit protocol

ACID

Concurrency

Support for concurrent manipulation of data

yes

yes, multi-version concurrency control (MVCC)

yes

MVCC

yes

Durability

Support for making data persistent

yes

yes, flexibel persistency by using storage technologies like Apache Kafka, RocksDB or LMDB

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.

fine grained access rights according to SQL-standard

yes

based on H2

Standard SQL roles/ privileges, Administrative Users

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