DBMS > ClickHouse vs. EsgynDB vs. GeoMesa vs. Netezza

System Properties Comparison ClickHouse vs. EsgynDB vs. GeoMesa vs. Netezza

Please select another system to include it in the comparison.

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

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

Data warehouse and analytics appliance part of IBM PureSystems

Primary database model

Relational DBMS

Spatial DBMS

Relational DBMS

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	0.25
Rank	#312	Overall
	#138	Relational DBMS

Score	0.86
Rank	#205	Overall
	#4	Spatial DBMS

Score	8.59
Rank	#45	Overall
	#29	Relational DBMS

Website

clickhouse.com

www.esgyn.cn

www.geomesa.org

www.ibm.com/products/netezza

Technical documentation

clickhouse.com/docs

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

Developer

Clickhouse Inc.

Esgyn

CCRi and others

IBM

Initial release

2016

2015

2014

2000

Current release

v24.4.2.141-stable, June 2024

5.0.0, May 2024

License

Commercial or Open Source

Open Source

Apache 2.0

commercial

Open Source

Apache License 2.0

commercial

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++

C++, Java

Scala

Server operating systems

FreeBSD
Linux
macOS

Linux

included in appliance

Data scheme

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

SQL

Support of SQL

Close to ANSI SQL (SQL/JSON + extensions)

yes

APIs and other access methods

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

ADO.NET
JDBC
ODBC

JDBC
ODBC
OLE DB

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

C
C++
Fortran
Java
Lua
Perl
Python
R

Server-side scripts

Stored procedures

yes

Java Stored Procedures

yes

Triggers

Partitioning methods

Methods for storing different data on different nodes

key based and custom

Sharding

depending on storage layer

Sharding

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

depending on storage layer

Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

depending on storage layer

Foreign keys

Referential integrity

yes

Transaction concepts

Support to ensure data integrity after non-atomic manipulations of data

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

In-memory capabilities

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

yes

depending on storage layer

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

depending on the DBMS used for storage

Users with fine-grained authorization concept

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.