DBMS > Microsoft Access vs. MySQL vs. Oracle NoSQL vs. QuestDB vs. SAP HANA

System Properties Comparison Microsoft Access vs. MySQL vs. Oracle NoSQL vs. QuestDB vs. SAP HANA

Editorial information provided by DB-Engines

Name

Description

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.)

Widely used open source RDBMS

A multi-model, scalable, distributed NoSQL database, designed to provide highly reliable, flexible, and available data management across a configurable set of storage nodes

A high performance open source SQL database for time series data

In-memory, column based data store. Available as appliance or cloud service

Primary database model

Relational DBMS

Key/Value like access via memcached API

Document store
Key-value store
Relational DBMS

Time Series DBMS

Relational DBMS

Secondary database models

Document store
Spatial DBMS

Relational DBMS

Document store
Graph DBMS

with SAP Hana, Enterprise Edition
Spatial DBMS

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

Score	101.16
Rank	#11	Overall
	#8	Relational DBMS

Score	1061.34
Rank	#2	Overall
	#2	Relational DBMS

Score	3.05
Rank	#97	Overall
	#17	Document stores
	#16	Key-value stores
	#50	Relational DBMS

Score	2.70
Rank	#105	Overall
	#8	Time Series DBMS

Score	44.27
Rank	#23	Overall
	#16	Relational DBMS

Website

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

www.mysql.com

www.oracle.com/database/nosql/technologies/nosql

questdb.io

www.sap.com/products/hana.html

Technical documentation

developer.microsoft.com/en-us/access

dev.mysql.com/doc

docs.oracle.com/en/database/other-databases/nosql-database/index.html

questdb.io/docs

help.sap.com/hana

Developer

Microsoft

Oracle

since 2010, originally MySQL AB, then Sun

Oracle

QuestDB Technology Inc

SAP

Initial release

1992

1995

2011

2014

2010

Current release

1902 (16.0.11328.20222), March 2019

8.4.0, April 2024

23.3, December 2023

2.0 SPS07 (April 4, 2023), April 2023

License

Commercial or Open Source

commercial

Bundled with Microsoft Office

Open Source

GPL version 2. Commercial licenses with extended functionallity are available

Open Source

Proprietary for Enterprise Edition (Oracle Database EE license has Oracle NoSQL database EE covered: details)

Open Source

Apache 2.0

commercial

Cloud-based only

Only available as a cloud service

also available as a cloud based service

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++

Java

Java (Zero-GC), C++, Rust

Server operating systems

Windows

Not a real database server, but making use of DLLs

FreeBSD
Linux
OS X
Solaris
Windows

Linux
Solaris SPARC/x86

Linux
macOS
Windows

Appliance or cloud-service

Data scheme

yes

Support Fixed schema and Schema-less deployment with the ability to interoperate between them.

yes

schema-free via InfluxDB Line Protocol

yes

Typing

predefined data types such as float or date

yes

optional

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

yes

but not compliant to any SQL standard

yes

with proprietary extensions

SQL-like DML and DDL statements

SQL with time-series extensions

yes

APIs and other access methods

ADO.NET
DAO
ODBC
OLE DB

ADO.NET
JDBC
ODBC
Proprietary native API

RESTful HTTP API

HTTP REST
InfluxDB Line Protocol (TCP/UDP)
JDBC
PostgreSQL wire protocol

JDBC
ODBC

Supported programming languages

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

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

C
C#
Go
Java
JavaScript (Node.js)
Python

PostgreSQL driver
C++
Go
Java
JavaScript (Node.js)
Python
Rust

over HTTP

Server-side scripts

Stored procedures

yes

since Access 2010 using the ACE-engine

yes

proprietary syntax

SQLScript, R

Triggers

yes

since Access 2010 using the ACE-engine

yes

Partitioning methods

Methods for storing different data on different nodes

none

horizontal partitioning, sharding with MySQL Cluster or MySQL Fabric

Sharding

horizontal partitioning (by timestamps)

yes

Replication methods

Methods for redundantly storing data on multiple nodes

none

Multi-source replication
Source-replica replication

Electable source-replica replication per shard. Support distributed global deployment with Multi-region table feature

Source-replica replication with eventual consistency

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

with Hadoop integration

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency
Immediate Consistency

depending on configuration

Immediate Consistency

Foreign keys

Referential integrity

yes

not for MyISAM storage engine

yes

Transaction concepts

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

ACID

but no files for transaction logging

ACID

not for MyISAM storage engine

configurable

ACID within a storage node (=shard)

ACID for single-table writes

ACID

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

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

off heap cache

yes

through memory mapped files

yes

User concepts

Access control

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

Users with fine-grained authorization concept

no user groups or roles

Access rights for users and roles

yes

More information provided by the system vendor

Specific characteristics

Relational model with native time series support Column-based storage and time partitioned...
» more

Competitive advantages

High ingestion throughput: peak of 4M rows/sec (TSBS Benchmark) Code optimizations...
» more

Typical application scenarios

Financial tick data Industrial IoT Application Metrics Monitoring
» more

Key customers

Banks & Hedge funds, Yahoo, OKX, Airbus, Aquis Exchange, Net App, Cloudera, Airtel,...
» more

Licensing and pricing models

Open source Apache 2.0 QuestDB Enterprise QuestDB Cloud
» more

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