DBMS > Apache Impala vs. Atos Standard Common Repository vs. Microsoft Access vs. Microsoft Azure AI Search vs. MongoDB

System Properties Comparison Apache Impala vs. Atos Standard Common Repository vs. Microsoft Access vs. Microsoft Azure AI Search vs. MongoDB

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

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.)

Search-as-a-service for web and mobile app development

One of the most popular document stores available both as a fully managed cloud service and for deployment on self-managed infrastructure

Primary database model

Relational DBMS

Document store
Key-value store

Relational DBMS

Search engine

Document store

Secondary database models

Document store

Vector DBMS

Spatial DBMS
Search engine

integrated Lucene index, currently in MongoDB Atlas only.
Time Series DBMS

Time Series Collections introduced in Release 5.0
Vector DBMS

currently available in the MongoDB Atlas cloud service only

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

Score	14.03
Rank	#40	Overall
	#24	Relational DBMS

Score	105.40
Rank	#11	Overall
	#8	Relational DBMS

Score	5.71
Rank	#64	Overall
	#8	Search engines

Score	423.96
Rank	#5	Overall
	#1	Document stores

Website

impala.apache.org

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

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

azure.microsoft.com/en-us/services/search

www.mongodb.com

Technical documentation

impala.apache.org/impala-docs.html

developer.microsoft.com/en-us/access

learn.microsoft.com/en-us/azure/search

www.mongodb.com/docs/manual

Developer

Apache Software Foundation

Apache top-level project, originally developed by Cloudera

Atos Convergence Creators

Microsoft

MongoDB, Inc

Initial release

2013

2016

1992

2015

2009

Current release

4.1.0, June 2022

1703

1902 (16.0.11328.20222), March 2019

6.0.7, June 2023

License

Commercial or Open Source

Open Source

Apache Version 2

commercial

Bundled with Microsoft Office

commercial

Open Source

MongoDB Inc.'s Server Side Public License v1. Prior versions were published under GNU AGPL v3.0. Commercial licenses are also available.

Cloud-based only

Only available as a cloud service

yes

MongoDB available as DBaaS (MongoDB Atlas)

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

MongoDB Atlas: Global multi-cloud database with unmatched data distribution and mobility across AWS, Azure, and Google Cloud, built-in automation for resource and workload optimization, and so much more.

Implementation language

C++

Java

C++

Server operating systems

Linux

Windows

Not a real database server, but making use of DLLs

hosted

Linux
OS X
Solaris
Windows

Data scheme

yes

Schema and schema-less with LDAP views

yes

schema-free

Although schema-free, documents of the same collection often follow the same structure. Optionally impose all or part of a schema by defining a JSON schema.

Typing

predefined data types such as float or date

yes

optional

yes

string, integer, double, decimal, boolean, date, object_id, geospatial

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 DML and DDL statements

yes

but not compliant to any SQL standard

Read-only SQL queries via the MongoDB Atlas SQL Interface

APIs and other access methods

JDBC
ODBC

LDAP

ADO.NET
DAO
ODBC
OLE DB

RESTful HTTP API

GraphQL
HTTP REST
Prisma
proprietary protocol using JSON

Supported programming languages

All languages supporting JDBC/ODBC

All languages with LDAP bindings

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

C#
Java
JavaScript
Python

Actionscript

unofficial driver
C
C#
C++
Clojure

unofficial driver
ColdFusion

unofficial driver
D

unofficial driver
Dart

unofficial driver
Delphi

unofficial driver
Erlang
Go
Groovy

unofficial driver
Haskell
Java
JavaScript
Kotlin
Lisp

unofficial driver
Lua

unofficial driver
MatLab

unofficial driver
Perl
PHP
PowerShell

unofficial driver
Prolog

unofficial driver
Python
R

unofficial driver
Ruby
Rust
Scala
Smalltalk

unofficial driver
Swift

Server-side scripts

Stored procedures

yes

user defined functions and integration of map-reduce

yes

since Access 2010 using the ACE-engine

JavaScript

Triggers

yes

since Access 2010 using the ACE-engine

yes

in MongoDB Atlas only

Partitioning methods

Methods for storing different data on different nodes

Sharding

cell division

none

Sharding

Implicit feature of the cloud service

Sharding

Partitioned by hashed, ranged, or zoned sharding keys. Live resharding allows users to change their shard keys as an online operation with zero downtime.

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

yes

none

yes

Implicit feature of the cloud service

Multi-Source deployments with MongoDB Atlas Global Clusters
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

query execution via MapReduce

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

Immediate Consistency or Eventual Consistency depending on configuration

Immediate Consistency

Eventual Consistency

can be individually decided for each read operation
Immediate Consistency

default behaviour

Foreign keys

Referential integrity

yes

typically not used, however similar functionality with DBRef possible

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-document ACID Transactions with snapshot isolation

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

but no files for transaction logging

yes

optional, enabled by default

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

yes

In-memory storage engine introduced with MongoDB version 3.2

User concepts

Access control

Access rights for users, groups and roles

based on Apache Sentry and Kerberos

LDAP bind authentication

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

yes

using Azure authentication

Access rights for users and roles

More information provided by the system vendor

Specific characteristics

MongoDB provides an integrated suite of cloud database and data services to accelerate...
» more

Competitive advantages

Built around the flexible document data model and unified API, MongoDB is a developer...
» more

Typical application scenarios

AI-enriched intelligent apps (Continental, Telefonica, Iron Mountain) Internet of...
» more

Key customers

ADP, Adobe, Amadeus, AstraZeneca, Auto Trader, Barclays, BBVA, Bosch, Cisco, CERN,...
» more

Market metrics

Hundreds of millions downloads, over 150,000+ Atlas clusters provisioned every month...
» more

Licensing and pricing models

MongoDB database server: Server-Side Public License (SSPL) . Commercial licenses...
» more

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.