DBMS > Atos Standard Common Repository vs. FileMaker vs. Google BigQuery vs. Microsoft Azure Synapse Analytics

System Properties Comparison Atos Standard Common Repository vs. FileMaker vs. Google BigQuery vs. Microsoft Azure Synapse Analytics

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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

FileMaker is a cross-platform RDBMS that includes a GUI frontend.

Large scale data warehouse service with append-only tables

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

Primary database model

Document store
Key-value store

Relational DBMS

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

Score	48.20
Rank	#20	Overall
	#14	Relational DBMS

Score	60.38
Rank	#19	Overall
	#13	Relational DBMS

Score	20.56
Rank	#31	Overall
	#19	Relational DBMS

Website

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

www.claris.com/filemaker

cloud.google.com/bigquery

azure.microsoft.com/services/synapse-analytics

Technical documentation

www.claris.com/resources/documentation

cloud.google.com/bigquery/docs

docs.microsoft.com/azure/synapse-analytics

Developer

Atos Convergence Creators

Claris

a subsidiary of Apple

Google

Microsoft

Initial release

2016

1983

2010

2016

Current release

1703

19.4.1, November 2021

License

Commercial or Open Source

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++

Server operating systems

Linux

iOS

client part only
Linux
OS X
Windows

hosted

Data scheme

Schema and schema-less with LDAP views

yes

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

A http query request can return the data in XML format

Secondary indexes

yes

SQL

Support of SQL

yes

via plugins

yes

APIs and other access methods

LDAP

Filemaker WebDirect
JDBC
ODBC

RESTful HTTP/JSON API

ADO.NET
JDBC
ODBC

Supported programming languages

All languages with LDAP bindings

PHP

.Net
Java
JavaScript
Objective-C
PHP
Python
Ruby

C#
Java
PHP

Server-side scripts

Stored procedures

yes

user defined functions

in JavaScript

Transact SQL

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

cell division

none

Sharding, horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Source-replica replication, warm standby

since Version 14

yes

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

Foreign keys

Referential integrity

yes

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

Transaction concepts

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

Atomic execution of specific operations

Since BigQuery is designed for querying data

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

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

simple rights management via user accounts and connection to external directory services

Access privileges (owner, writer, reader) on dataset, table or view level

Google Cloud Identity & Access Management (IAM)

yes

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