DBMS > Atos Standard Common Repository vs. Microsoft Access vs. Microsoft Azure Cosmos DB vs. Splice Machine vs. TimesTen

System Properties Comparison Atos Standard Common Repository vs. Microsoft Access vs. Microsoft Azure Cosmos DB vs. Splice Machine vs. TimesTen

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

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.)

Globally distributed, horizontally scalable, multi-model database service

Open-Source SQL RDBMS for Operational and Analytical use cases with native Machine Learning, powered by Hadoop and Spark

In-Memory RDBMS compatible to Oracle

Primary database model

Document store
Key-value store

Relational DBMS

Document store
Graph DBMS
Key-value store
Wide column store

Relational DBMS

Secondary database models

Spatial DBMS

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

Score	104.92
Rank	#11	Overall
	#8	Relational DBMS

Score	29.04
Rank	#27	Overall
	#4	Document stores
	#2	Graph DBMS
	#3	Key-value stores
	#3	Wide column stores

Score	0.54
Rank	#250	Overall
	#114	Relational DBMS

Score	1.31
Rank	#163	Overall
	#74	Relational DBMS

Website

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

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

azure.microsoft.com/services/cosmos-db

splicemachine.com

www.oracle.com/database/technologies/related/timesten.html

Technical documentation

developer.microsoft.com/en-us/access

learn.microsoft.com/azure/cosmos-db

splicemachine.com/how-it-works

docs.oracle.com/database/timesten-18.1

Developer

Atos Convergence Creators

Microsoft

Splice Machine

Oracle, TimesTen Performance Software, HP

originally founded in HP Labs it was acquired by Oracle in 2005

Initial release

2016

1992

2014

1998

Current release

1703

1902 (16.0.11328.20222), March 2019

3.1, March 2021

11 Release 2 (11.2.2.8.0)

License

Commercial or Open Source

commercial

Bundled with Microsoft Office

commercial

Open Source

AGPL 3.0, commercial license available

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

C++

Java

Server operating systems

Linux

Windows

Not a real database server, but making use of DLLs

hosted

Linux
OS X
Solaris
Windows

AIX
HP-UX
Linux
OS X
Solaris SPARC/x86
Windows

Data scheme

Schema and schema-less with LDAP views

yes

schema-free

yes

Typing

predefined data types such as float or date

optional

yes

JSON types

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

All properties auto-indexed by default

yes

SQL

Support of SQL

yes

but not compliant to any SQL standard

SQL-like query language

yes

APIs and other access methods

LDAP

ADO.NET
DAO
ODBC
OLE DB

DocumentDB API
Graph API (Gremlin)
MongoDB API
RESTful HTTP API
Table API

JDBC
Native Spark Datasource
ODBC

JDBC
ODBC
ODP.NET
Oracle Call Interface (OCI)

Supported programming languages

All languages with LDAP bindings

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

.Net
C#
Java
JavaScript
JavaScript (Node.js)
MongoDB client drivers written for various programming languages
Python

C#
C++
Java
JavaScript (Node.js)
Python
R
Scala

C
C++
Java
PL/SQL

Server-side scripts

Stored procedures

yes

since Access 2010 using the ACE-engine

JavaScript

yes

Java

PL/SQL

Triggers

yes

since Access 2010 using the ACE-engine

JavaScript

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

cell division

none

Sharding

Implicit feature of the cloud service

Shared Nothhing Auto-Sharding, Columnar Partitioning

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes

none

yes

Implicit feature of the cloud service

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

with Hadoop integration

Integration with Hadoop/HDInsight on Azure*

Yes, via Full Spark Integration

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency or Eventual Consistency depending on configuration

Bounded Staleness
Consistent Prefix
Eventual Consistency
Immediate Consistency

Consistency level configurable on request level
Session Consistency

Immediate Consistency

Immediate Consistency or Eventual Consistency depending on configuration

Foreign keys

Referential integrity

yes

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

Multi-item ACID transactions with snapshot isolation within a partition

ACID

Concurrency

Support for concurrent manipulation of data

yes

yes, multi-version concurrency control (MVCC)

yes

Durability

Support for making data persistent

yes

but no files for transaction logging

yes

by means of logfiles and checkpoints

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

Access rights can be defined down to the item level

Access rights for users, groups and roles according to SQL-standard

fine grained access rights according to SQL-standard

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