DBMS > ClickHouse vs. Microsoft Access vs. OrientDB vs. Snowflake

System Properties Comparison ClickHouse vs. Microsoft Access vs. OrientDB vs. Snowflake

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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.

Microsoft Access combines a backend RDBMS (JET / ACE Engine) with a GUI frontend for data manipulation and queries.

The Access frontend is often used for accessing other datasources (DBMS, Excel, etc.)

Multi-model DBMS (Document, Graph, Key/Value)

Cloud-based data warehousing service for structured and semi-structured data

Primary database model

Relational DBMS

Document store
Graph DBMS
Key-value store

Relational DBMS

Secondary database models

Time Series DBMS

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

Score	16.20
Rank	#37	Overall
	#23	Relational DBMS

Score	105.40
Rank	#11	Overall
	#8	Relational DBMS

Score	3.27
Rank	#97	Overall
	#16	Document stores
	#6	Graph DBMS
	#15	Key-value stores

Score	123.20
Rank	#9	Overall
	#6	Relational DBMS

Website

clickhouse.com

www.microsoft.com/en-us/microsoft-365/access

orientdb.org

www.snowflake.com

Technical documentation

clickhouse.com/docs

developer.microsoft.com/en-us/access

www.orientdb.com/docs/last/index.html

docs.snowflake.net/manuals/index.html

Developer

Clickhouse Inc.

Microsoft

OrientDB LTD; CallidusCloud; SAP

Snowflake Computing Inc.

Initial release

2016

1992

2010

2014

Current release

v24.3.2.23-lts, April 2024

1902 (16.0.11328.20222), March 2019

3.2.29, March 2024

License

Commercial or Open Source

Open Source

Apache 2.0

commercial

Bundled with Microsoft Office

Open Source

Apache version 2

commercial

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

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Aiven for Clickhouse: Managed cloud data warehousing with high-speed analytics.
DoubleCloud: Fully managed ClickHouse alongside best-in-class managed open-source services to build analytics at scale.

Implementation language

C++

Java

Server operating systems

FreeBSD
Linux
macOS

Windows

Not a real database server, but making use of DLLs

All OS with a Java JDK (>= JDK 6)

hosted

Data scheme

yes

schema-free

Schema can be enforced for whole record ("schema-full") or for some fields only ("schema-hybrid")

yes

support of semi-structured data formats (JSON, XML, Avro)

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

but not compliant to any SQL standard

SQL-like query language, no joins

yes

APIs and other access methods

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

ADO.NET
DAO
ODBC
OLE DB

Tinkerpop technology stack with Blueprints, Gremlin, Pipes
Java API
RESTful HTTP/JSON API

CLI Client
JDBC
ODBC

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

C
C#
C++
Delphi
Java (JDBC-ODBC)
VBA
Visual Basic.NET

.Net
C
C#
C++
Clojure
Java
JavaScript
JavaScript (Node.js)
PHP
Python
Ruby
Scala

JavaScript (Node.js)
Python

Server-side scripts

Stored procedures

yes

since Access 2010 using the ACE-engine

Java, Javascript

user defined functions

Triggers

yes

since Access 2010 using the ACE-engine

Hooks

similar concept for controling cloud resources

Partitioning methods

Methods for storing different data on different nodes

key based and custom

none

Sharding

yes

Replication methods

Methods for redundantly storing data on multiple nodes

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

none

Multi-source replication

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

could be achieved with distributed queries

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Foreign keys

Referential integrity

yes

relationship in graphs

yes

Transaction concepts

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

ACID

but no files for transaction logging

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

but no files for transaction logging

yes

In-memory capabilities

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

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.

a simple user-level security was built in till version Access 2003

Access rights for users and roles; record level security configurable

Users with fine-grained authorization concept, user roles and pluggable authentication

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