DBMS > Atos Standard Common Repository vs. IRONdb vs. Microsoft Access vs. Microsoft Azure Synapse Analytics vs. MySQL

System Properties Comparison Atos Standard Common Repository vs. IRONdb vs. Microsoft Access vs. Microsoft Azure Synapse Analytics vs. MySQL

Editorial information provided by DB-Engines

Name

This system has been discontinued and will be removed from the DB-Engines ranking.

IRONdb seems to be discontinued. Therefore it is excluded from the DB-Engines Ranking.

Description

Highly scalable database system, designed for managing session and subscriber data in modern mobile communication networks

A distributed Time Series DBMS with a focus on scalability, fault tolerance and operational simplicity

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.)

Elastic, large scale data warehouse service leveraging the broad eco-system of SQL Server

Widely used open source RDBMS

Primary database model

Document store
Key-value store

Time Series DBMS

Relational DBMS

Key/Value like access via memcached API

Secondary database models

Document store
Spatial DBMS

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

Score	104.92
Rank	#11	Overall
	#8	Relational DBMS

Score	20.56
Rank	#31	Overall
	#19	Relational DBMS

Score	1083.74
Rank	#2	Overall
	#2	Relational DBMS

Website

atos.net/en/convergence-creators/portfolio/standard-common-repository

www.circonus.com/solutions/time-series-database/

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

azure.microsoft.com/services/synapse-analytics

www.mysql.com

Technical documentation

docs.circonus.com/irondb/category/getting-started

developer.microsoft.com/en-us/access

docs.microsoft.com/azure/synapse-analytics

dev.mysql.com/doc

Developer

Atos Convergence Creators

Circonus LLC.

Microsoft

Oracle

since 2010, originally MySQL AB, then Sun

Initial release

2016

2017

1992

2016

1995

Current release

1703

V0.10.20, January 2018

1902 (16.0.11328.20222), March 2019

8.4.0, April 2024

License

Commercial or Open Source

commercial

Bundled with Microsoft Office

commercial

Open Source

GPL version 2. Commercial licenses with extended functionallity are available

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.

Aiven for MySQL: Fully managed MySQL, deployable in the cloud of your choice, with seamless integrations and lightning-fast setup.

Implementation language

Java

C and C++

C++

C and C++

Server operating systems

Linux

Windows

Not a real database server, but making use of DLLs

hosted

FreeBSD
Linux
OS X
Solaris
Windows

Data scheme

Schema and schema-less with LDAP views

schema-free

yes

Typing

predefined data types such as float or date

optional

yes

text, numeric, histograms

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

SQL-like query language (Circonus Analytics Query Language: CAQL)

yes

but not compliant to any SQL standard

yes

with proprietary extensions

APIs and other access methods

LDAP

HTTP API

ADO.NET
DAO
ODBC
OLE DB

ADO.NET
JDBC
ODBC

ADO.NET
JDBC
ODBC
Proprietary native API

Supported programming languages

All languages with LDAP bindings

.Net
C
C++
Clojure
Erlang
Go
Haskell
Java
JavaScript
JavaScript (Node.js)
Lisp
Lua
Perl
PHP
Python
R
Ruby
Rust
Scala

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

C#
Java
PHP

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

Server-side scripts

Stored procedures

yes, in Lua

yes

since Access 2010 using the ACE-engine

Transact SQL

yes

proprietary syntax

Triggers

yes

since Access 2010 using the ACE-engine

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

cell division

Automatic, metric affinity per node

none

Sharding, horizontal partitioning

horizontal partitioning, sharding with MySQL Cluster or MySQL Fabric

Replication methods

Methods for redundantly storing data on multiple nodes

yes

configurable replication factor, datacenter aware

none

yes

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 or Eventual Consistency depending on configuration

Immediate consistency per node, eventual consistency across nodes

Immediate Consistency

Foreign keys

Referential integrity

yes

docs.microsoft.com/en-us/azure/synapse-analytics/sql-data-warehouse/sql-data-warehouse-table-constraints

yes

not for MyISAM storage engine

Transaction concepts

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

Atomic execution of specific operations

ACID

but no files for transaction logging

ACID

not for MyISAM storage engine

Concurrency

Support for concurrent manipulation of data

yes

table locks or row locks depending on storage engine

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

LDAP bind authentication

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

yes

Users with fine-grained authorization concept

no user groups or roles

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