DBMS > Atos Standard Common Repository vs. Datomic vs. MarkLogic vs. Microsoft Access vs. Snowflake

System Properties Comparison Atos Standard Common Repository vs. Datomic vs. MarkLogic vs. Microsoft Access vs. Snowflake

Editorial information provided by DB-Engines

Name

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

Description

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

Datomic builds on immutable values, supports point-in-time queries and uses 3rd party systems for durability

Operational and transactional Enterprise NoSQL database

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.)

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

Primary database model

Document store
Key-value store

Relational DBMS

Document store
Native XML DBMS
RDF store

as of version 7
Search engine

Relational DBMS

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

Score	1.55
Rank	#144	Overall
	#67	Relational DBMS

Score	4.15
Rank	#70	Overall
	#11	Document stores
	#1	Native XML DBMS
	#1	RDF stores
	#8	Search engines

Score	93.76
Rank	#12	Overall
	#8	Relational DBMS

Score	133.72
Rank	#7	Overall
	#5	Relational DBMS

Website

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

www.datomic.com

www.progress.com/marklogic

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

www.snowflake.com

Technical documentation

docs.datomic.com

www.progress.com/marklogic/documentation

developer.microsoft.com/en-us/access

docs.snowflake.net/manuals/index.html

Developer

Atos Convergence Creators

Cognitect

MarkLogic Corp.

Microsoft

Snowflake Computing Inc.

Initial release

2016

2012

2001

1992

2014

Current release

1703

1.0.7180, July 2024

11.0, December 2022

1902 (16.0.11328.20222), March 2019

License

Commercial or Open Source

commercial

limited edition free

commercial

restricted free version is available

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.

Implementation language

Java

Java, Clojure

C++

Server operating systems

Linux

All OS with a Java VM

Linux
OS X
Windows

Windows

Not a real database server, but making use of DLLs

hosted

Data scheme

Schema and schema-less with LDAP views

yes

schema-free

Schema can be enforced

yes

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

Typing

predefined data types such as float or date

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

SQL92

yes

but not compliant to any SQL standard

yes

APIs and other access methods

LDAP

RESTful HTTP API

Java API
Node.js Client API
ODBC
proprietary Optic API

Proprietary Query API, introduced with version 9
RESTful HTTP API
SPARQL
WebDAV
XDBC
XQuery
XSLT

ADO.NET
DAO
ODBC
OLE DB

CLI Client
JDBC
ODBC

Supported programming languages

All languages with LDAP bindings

Clojure
Java

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

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

JavaScript (Node.js)
Python

Server-side scripts

Stored procedures

yes

Transaction Functions

yes

via XQuery or JavaScript

yes

since Access 2010 using the ACE-engine

user defined functions

Triggers

yes

By using transaction functions

yes

since Access 2010 using the ACE-engine

similar concept for controling cloud resources

Partitioning methods

Methods for storing different data on different nodes

Sharding

cell division

none

But extensive use of caching in the application peers

Sharding

none

yes

Replication methods

Methods for redundantly storing data on multiple nodes

yes

none

But extensive use of caching in the application peers

yes

none

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

via Hadoop Connector, HDFS Direct Access and in-database MapReduce jobs

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency or Eventual Consistency depending on configuration

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

Atomic execution of specific operations

ACID

can act as a resource manager in an XA/JTA transaction

ACID

but no files for transaction logging

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

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

recommended only for testing and development

yes, with Range Indexes

User concepts

Access control

LDAP bind authentication

Role-based access control at the document and subdocument levels

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

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

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