DBMS > ClickHouse vs. Datomic vs. Microsoft SQL Server vs. SpaceTime vs. TimesTen

System Properties Comparison ClickHouse vs. Datomic vs. Microsoft SQL Server vs. SpaceTime vs. TimesTen

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

Microsofts flagship relational DBMS

SpaceTime is a spatio-temporal DBMS with a focus on performance.

In-Memory RDBMS compatible to Oracle

Primary database model

Relational DBMS

Spatial DBMS

Relational DBMS

Secondary database models

Time Series DBMS

Document store
Graph DBMS
Spatial 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	1.59
Rank	#150	Overall
	#69	Relational DBMS

Score	824.29
Rank	#3	Overall
	#3	Relational DBMS

Score	0.00
Rank	#383	Overall
	#7	Spatial DBMS

Score	1.31
Rank	#163	Overall
	#74	Relational DBMS

Website

clickhouse.com

www.datomic.com

www.microsoft.com/en-us/sql-server

www.mireo.com/spacetime

www.oracle.com/database/technologies/related/timesten.html

Technical documentation

clickhouse.com/docs

docs.datomic.com

learn.microsoft.com/en-US/sql/sql-server

docs.oracle.com/database/timesten-18.1

Developer

Clickhouse Inc.

Cognitect

Microsoft

Mireo

Oracle, TimesTen Performance Software, HP

originally founded in HP Labs it was acquired by Oracle in 2005

Initial release

2016

2012

1989

2020

1998

Current release

v24.3.2.23-lts, April 2024

1.0.6735, June 2023

SQL Server 2022, November 2022

11 Release 2 (11.2.2.8.0)

License

Commercial or Open Source

Open Source

Apache 2.0

commercial

limited edition free

commercial

restricted free version is available

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.
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++

Java, Clojure

C++

Server operating systems

FreeBSD
Linux
macOS

All OS with a Java VM

Linux
Windows

Linux

AIX
HP-UX
Linux
OS X
Solaris SPARC/x86
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

A subset of ANSI SQL is implemented

yes

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
OLE DB
Tabular Data Stream (TDS)

RESTful HTTP API

JDBC
ODBC
ODP.NET
Oracle Call Interface (OCI)

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

C#
C++
Delphi
Go
Java
JavaScript (Node.js)
PHP
Python
R
Ruby
Visual Basic

C#
C++
Python

C
C++
Java
PL/SQL

Server-side scripts

Stored procedures

yes

Transaction Functions

Transact SQL, .NET languages, R, Python and (with SQL Server 2019) Java

PL/SQL

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

tables can be distributed across several files (horizontal partitioning); sharding through federation

Fixed-grid hypercubes

none

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

yes, but depending on the SQL-Server Edition

Real-time block device replication (DRBD)

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Immediate Consistency or Eventual Consistency depending on configuration

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

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

yes

by means of logfiles and checkpoints

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.

fine grained access rights according to SQL-standard

yes

fine grained access rights according to SQL-standard

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