DBMS > Brytlyt vs. ClickHouse vs. EXASOL vs. eXtremeDB vs. GeoMesa

System Properties Comparison Brytlyt vs. ClickHouse vs. EXASOL vs. eXtremeDB vs. GeoMesa

Editorial information provided by DB-Engines

Name

Description

Scalable GPU-accelerated RDBMS for very fast analytic and streaming workloads, leveraging PostgreSQL

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.

High-performance, in-memory, MPP database specifically designed for in-memory analytics.

Natively in-memory DBMS with options for persistency, high-availability and clustering

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

Primary database model

Relational DBMS

Relational DBMS
Time Series DBMS

Spatial DBMS

Secondary database models

Time Series DBMS

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

Score	0.38
Rank	#276	Overall
	#127	Relational DBMS

Score	15.55
Rank	#38	Overall
	#23	Relational DBMS

Score	1.76
Rank	#139	Overall
	#62	Relational DBMS

Score	0.80
Rank	#214	Overall
	#99	Relational DBMS
	#18	Time Series DBMS

Score	0.86
Rank	#205	Overall
	#4	Spatial DBMS

Website

Technical documentation

docs.brytlyt.io

clickhouse.com/docs

www.exasol.com/resources

www.mcobject.com/docs/extremedb.htm

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

Developer

Brytlyt

Clickhouse Inc.

Exasol

McObject

CCRi and others

Initial release

2016

2000

2001

2014

Current release

5.0, August 2023

v24.4.1.2088-stable, May 2024

8.2, 2021

5.0.0, May 2024

License

Commercial or Open Source

commercial

Open Source

Apache 2.0

commercial

Open Source

Apache License 2.0

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++ and CUDA

C++

C and C++

Scala

Server operating systems

Linux
OS X
Windows

FreeBSD
Linux
macOS

AIX
HP-UX
Linux
macOS
Solaris
Windows

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.

yes

specific XML-type available, but no XML query functionality.

support of XML interfaces available

Secondary indexes

yes

SQL

Support of SQL

yes

Close to ANSI SQL (SQL/JSON + extensions)

yes

with the option: eXtremeSQL

APIs and other access methods

ADO.NET
JDBC
native C library
ODBC
streaming API for large objects

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

.Net
JDBC
ODBC
WebSocket

.NET Client API
JDBC
JNI
ODBC
Proprietary protocol
RESTful HTTP API

Supported programming languages

.Net
C
C++
Delphi
Java
Perl
Python
Tcl

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

Java
Lua
Python
R

.Net
C
C#
C++
Java
Lua
Python
Scala

Server-side scripts

Stored procedures

user defined functions

in PL/pgSQL

yes

user defined functions

yes

Triggers

yes

by defining events

Partitioning methods

Methods for storing different data on different nodes

key based and custom

Sharding

horizontal partitioning / sharding

depending on storage layer

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

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

Active Replication Fabric™ for IoT
Multi-source replication

by means of eXtremeDB Cluster option
Source-replica replication

by means of eXtremeDB High Availability option

depending on storage layer

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Hadoop integration

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

Optimistic (MVCC) and pessimistic (locking) strategies available

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

fine grained access rights according to SQL-standard

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.

Access rights for users, groups and roles according to SQL-standard

yes

depending on the DBMS used for storage

More information provided by the system vendor

Specific characteristics

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Competitive advantages

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Typical application scenarios

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Key customers

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Market metrics

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Licensing and pricing models

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