DBMS > Atos Standard Common Repository vs. Firebase Realtime Database vs. IBM Db2 Event Store vs. Realm vs. Snowflake

System Properties Comparison Atos Standard Common Repository vs. Firebase Realtime Database vs. IBM Db2 Event Store vs. Realm 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

Cloud-hosted realtime document store. iOS, Android, and JavaScript clients share one Realtime Database instance and automatically receive updates with the newest data.

Distributed Event Store optimized for Internet of Things use cases

A DBMS built for use on mobile devices that’s a fast, easy to use alternative to SQLite and Core Data

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

Primary database model

Document store
Key-value store

Document store

Event Store
Time Series DBMS

Document store

Relational DBMS

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

Score	13.64
Rank	#39	Overall
	#6	Document stores

Score	0.27
Rank	#309	Overall
	#2	Event Stores
	#28	Time Series DBMS

Score	7.41
Rank	#52	Overall
	#8	Document stores

Score	130.36
Rank	#8	Overall
	#5	Relational DBMS

Website

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

firebase.google.com/products/realtime-database

www.ibm.com/products/db2-event-store

realm.io

www.snowflake.com

Technical documentation

firebase.google.com/docs/database

www.ibm.com/docs/en/db2-event-store

realm.io/docs

docs.snowflake.net/manuals/index.html

Developer

Atos Convergence Creators

Google

acquired by Google 2014

IBM

Realm, acquired by MongoDB in May 2019

Snowflake Computing Inc.

Initial release

2016

2012

2017

2014

Current release

1703

2.0

License

Commercial or Open Source

commercial

free developer edition available

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 and C++

Server operating systems

Linux

hosted

Linux

Linux, macOS, Windows for the developer addition

Android
Backend: server-less
iOS
Windows

hosted

Data scheme

Schema and schema-less with LDAP views

schema-free

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

through the embedded Spark runtime

yes

APIs and other access methods

LDAP

Android
iOS
JavaScript API
RESTful HTTP API

ADO.NET
DB2 Connect
JDBC
ODBC
RESTful HTTP API

CLI Client
JDBC
ODBC

Supported programming languages

All languages with LDAP bindings

Java
JavaScript
Objective-C

C
C#
C++
Cobol
Delphi
Fortran
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Ruby
Scala
Visual Basic

.Net
Java

with Android only
Objective-C
React Native
Swift

JavaScript (Node.js)
Python

Server-side scripts

Stored procedures

limited functionality with using 'rules'

yes

runs within the applications so server-side scripts are unnecessary

user defined functions

Triggers

yes

Callbacks are triggered when data changes

yes

Change Listeners

similar concept for controling cloud resources

Partitioning methods

Methods for storing different data on different nodes

Sharding

cell division

Sharding

none

yes

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Active-active shard replication

none

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

Eventual Consistency

if the client is offline
Immediate Consistency

if the client is online

Eventual Consistency

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

yes

ACID

Concurrency

Support for concurrent manipulation of data

yes

No - written data is immutable

yes

Durability

Support for making data persistent

yes

Yes - Synchronous writes to local disk combined with replication and asynchronous writes in parquet format to permanent shared storage

yes

In-memory capabilities

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

yes

In-Memory realm

User concepts

Access control

LDAP bind authentication

yes, based on authentication and database rules

fine grained access rights according to SQL-standard

yes

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

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