DBMS > Apache Impala vs. Atos Standard Common Repository vs. Interbase vs. Microsoft Access vs. Microsoft Azure Cosmos DB

System Properties Comparison Apache Impala vs. Atos Standard Common Repository vs. Interbase vs. Microsoft Access vs. Microsoft Azure Cosmos DB

Editorial information provided by DB-Engines

Name

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

Description

Analytic DBMS for Hadoop

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

Light-weight proven RDBMS

originally from Borland

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

Primary database model

Relational DBMS

Document store
Key-value store

Relational DBMS

Document store
Graph DBMS
Key-value store
Wide column store

Secondary database models

Document store

Spatial DBMS

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

Score	12.45
Rank	#40	Overall
	#24	Relational DBMS

Score	4.08
Rank	#75	Overall
	#41	Relational DBMS

Score	101.16
Rank	#11	Overall
	#8	Relational DBMS

Score	27.71
Rank	#27	Overall
	#4	Document stores
	#2	Graph DBMS
	#3	Key-value stores
	#3	Wide column stores

Website

impala.apache.org

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

www.embarcadero.com/products/interbase

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

azure.microsoft.com/services/cosmos-db

Technical documentation

impala.apache.org/impala-docs.html

docs.embarcadero.com/products/interbase

developer.microsoft.com/en-us/access

learn.microsoft.com/azure/cosmos-db

Developer

Apache Software Foundation

Apache top-level project, originally developed by Cloudera

Atos Convergence Creators

Embarcadero

Microsoft

Initial release

2013

2016

1984

1992

2014

Current release

4.1.0, June 2022

1703

InterBase 2020, December 2019

1902 (16.0.11328.20222), March 2019

License

Commercial or Open Source

Open Source

Apache Version 2

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

C++

Java

C++

Server operating systems

Linux

Android
iOS
Linux
OS X
Windows

Windows

Not a real database server, but making use of DLLs

hosted

Data scheme

yes

Schema and schema-less with LDAP views

yes

schema-free

Typing

predefined data types such as float or date

yes

optional

yes

JSON types

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

export as XML data possible

Secondary indexes

yes

All properties auto-indexed by default

SQL

Support of SQL

SQL-like DML and DDL statements

yes

but not compliant to any SQL standard

SQL-like query language

APIs and other access methods

JDBC
ODBC

LDAP

ADO.NET
JDBC
ODBC

ADO.NET
DAO
ODBC
OLE DB

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

Supported programming languages

All languages supporting JDBC/ODBC

All languages with LDAP bindings

.Net
C
C++
Delphi
Java
Object Pascal
PHP
Ruby

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

Server-side scripts

Stored procedures

yes

user defined functions and integration of map-reduce

yes

Interbase procedure and trigger language

yes

since Access 2010 using the ACE-engine

JavaScript

Triggers

yes

since Access 2010 using the ACE-engine

JavaScript

Partitioning methods

Methods for storing different data on different nodes

Sharding

cell division

none

Sharding

Implicit feature of the cloud service

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

yes

Interbase Change Views

none

yes

Implicit feature of the cloud service

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

query execution via MapReduce

with Hadoop integration

Integration with Hadoop/HDInsight on Azure*

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

Immediate Consistency or Eventual Consistency depending on configuration

Immediate Consistency

Bounded Staleness
Consistent Prefix
Eventual Consistency
Immediate Consistency

Consistency level configurable on request level
Session 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

but no files for transaction logging

Multi-item ACID transactions with snapshot isolation within a partition

Concurrency

Support for concurrent manipulation of data

yes

Multiversion concurreny control

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, groups and roles

based on Apache Sentry and Kerberos

LDAP bind authentication

fine grained access rights according to SQL-standard

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

Access rights can be defined down to the item level

More information provided by the system vendor

We invite representatives of system vendors to contact us for updating and extending the system information,
and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.