DBMS > ClickHouse vs. eXtremeDB vs. GBase vs. Microsoft Access vs. Microsoft Azure Table Storage

System Properties Comparison ClickHouse vs. eXtremeDB vs. GBase vs. Microsoft Access vs. Microsoft Azure Table Storage

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.

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

Widely used RDBMS in China, including analytical, transactional, distributed transactional, and cloud-native data warehousing.

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.)

A Wide Column Store for rapid development using massive semi-structured datasets

Primary database model

Relational DBMS

Relational DBMS
Time Series DBMS

Relational DBMS

Wide column store

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

Score	1.05
Rank	#186	Overall
	#86	Relational DBMS

Score	101.16
Rank	#11	Overall
	#8	Relational DBMS

Score	4.04
Rank	#77	Overall
	#6	Wide column stores

Website

clickhouse.com

www.mcobject.com

www.gbase.cn

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

azure.microsoft.com/en-us/services/storage/tables

Technical documentation

clickhouse.com/docs

www.mcobject.com/docs/extremedb.htm

developer.microsoft.com/en-us/access

Developer

Clickhouse Inc.

McObject

General Data Technology Co., Ltd.

Microsoft

Initial release

2016

2001

2004

1992

2012

Current release

v24.4.1.2088-stable, May 2024

8.2, 2021

GBase 8a, GBase 8s, GBase 8c

1902 (16.0.11328.20222), March 2019

License

Commercial or Open Source

Open Source

Apache 2.0

commercial

Bundled with Microsoft Office

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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Implementation language

C++

C and C++

C, Java, Python

C++

Server operating systems

FreeBSD
Linux
macOS

AIX
HP-UX
Linux
macOS
Solaris
Windows

Linux

Windows

Not a real database server, but making use of DLLs

hosted

Data scheme

yes

schema-free

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.

support of XML interfaces available

yes

Secondary indexes

yes

SQL

Support of SQL

Close to ANSI SQL (SQL/JSON + extensions)

yes

with the option: eXtremeSQL

Standard with numerous extensions

yes

but not compliant to any SQL standard

APIs and other access methods

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

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

ADO.NET
C API
JDBC
ODBC

ADO.NET
DAO
ODBC
OLE DB

RESTful HTTP API

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

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

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

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

Server-side scripts

Stored procedures

yes

user defined functions

yes

since Access 2010 using the ACE-engine

Triggers

yes

by defining events

yes

since Access 2010 using the ACE-engine

Partitioning methods

Methods for storing different data on different nodes

key based and custom

horizontal partitioning / sharding

horizontal partitioning (by range, list and hash) and vertical partitioning

none

Sharding

Implicit feature of the cloud service

Replication methods

Methods for redundantly storing data on multiple nodes

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

yes

none

yes

implicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

but no files for transaction logging

optimistic locking

Concurrency

Support for concurrent manipulation of data

yes

Optimistic (MVCC) and pessimistic (locking) strategies available

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.

yes

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

Access rights based on private key authentication or shared access signatures

More information provided by the system vendor

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Licensing and pricing models

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