DBMS > ClickHouse vs. Datomic vs. MySQL vs. Splunk

System Properties Comparison ClickHouse vs. Datomic vs. MySQL vs. Splunk

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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.

Datomic builds on immutable values, supports point-in-time queries and uses 3rd party systems for durability

Widely used open source RDBMS

Analytics Platform for Big Data

Primary database model

Relational DBMS

Key/Value like access via memcached API

Search engine

Secondary database models

Time Series DBMS

Document store
Spatial DBMS

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

Score	15.88
Rank	#37	Overall
	#22	Relational DBMS

Score	1.55
Rank	#144	Overall
	#67	Relational DBMS

Score	1029.49
Rank	#2	Overall
	#2	Relational DBMS

Score	93.02
Rank	#13	Overall
	#2	Search engines

Website

Technical documentation

clickhouse.com/docs

docs.datomic.com

dev.mysql.com/doc

docs.splunk.com/Documentation/Splunk

Developer

Clickhouse Inc.

Cognitect

Oracle

since 2010, originally MySQL AB, then Sun

Splunk Inc.

Initial release

2016

2012

1995

2003

Current release

v24.6.2.17-stable, July 2024

1.0.7180, July 2024

9.0.0, July 2024

License

Commercial or Open Source

Open Source

Apache 2.0

commercial

limited edition free

Open Source

GPL version 2. Commercial licenses with extended functionallity are available

commercial

Limited free edition and free developer edition available

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.

Implementation language

C++

Java, Clojure

C and C++

Server operating systems

FreeBSD
Linux
macOS

All OS with a Java VM

FreeBSD
Linux
OS X
Solaris
Windows

Linux
OS X
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

Secondary indexes

yes

SQL

Support of SQL

Close to ANSI SQL (SQL/JSON + extensions)

yes

with proprietary extensions

Splunk Search Processing Language for search commands

APIs and other access methods

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

RESTful HTTP API

ADO.NET
JDBC
ODBC
Proprietary native API

HTTP REST

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

Clojure
Java

Ada
C
C#
C++
D
Delphi
Eiffel
Erlang
Haskell
Java
JavaScript (Node.js)
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl

C#
Java
JavaScript
PHP
Python
Ruby

Server-side scripts

Stored procedures

yes

Transaction Functions

yes

proprietary syntax

yes

Triggers

By using transaction functions

yes

Partitioning methods

Methods for storing different data on different nodes

key based and custom

none

But extensive use of caching in the application peers

horizontal partitioning, sharding with MySQL Cluster or MySQL Fabric

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

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

none

But extensive use of caching in the application peers

Multi-source replication
Source-replica replication

Multi-source replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

Foreign keys

Referential integrity

yes

not for MyISAM storage engine

Transaction concepts

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

ACID

not for MyISAM storage engine

A 'Transaction' in Splunk has a different meaning: grouping related events into a single one for later searching

Concurrency

Support for concurrent manipulation of data

yes

table locks or row locks depending on storage engine

yes

Durability

Support for making data persistent

yes

using external storage systems (e.g. Cassandra, DynamoDB, PostgreSQL, Couchbase and others)

yes

In-memory capabilities

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

yes

recommended only for testing and development

yes

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.

Users with fine-grained authorization concept

no user groups or roles

Access rights for users and roles

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