DBMS > FatDB vs. Google Cloud Firestore vs. InterSystems Caché vs. OpenTSDB vs. Snowflake

System Properties Comparison FatDB vs. Google Cloud Firestore vs. InterSystems Caché vs. OpenTSDB vs. Snowflake

Editorial information provided by DB-Engines

Name

FatDB/FatCloud has ceased operations as a company with February 2014. FatDB is discontinued and excluded from the ranking.

Caché is a deprecated database engine which is substituted with InterSystems IRIS. It therefore is removed from the DB-Engines Ranking.

Description

A .NET NoSQL DBMS that can integrate with and extend SQL Server.

Cloud Firestore is an auto-scaling document database for storing, syncing, and querying data for mobile and web apps. It offers seamless integration with other Firebase and Google Cloud Platform products.

A multi-model DBMS and application server

Scalable Time Series DBMS based on HBase

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

Primary database model

Document store
Key-value store

Document store

Key-value store
Object oriented DBMS
Relational DBMS

Time Series DBMS

Relational DBMS

Secondary database models

Document store

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

Score	7.36
Rank	#53	Overall
	#9	Document stores

Score	1.68
Rank	#142	Overall
	#12	Time Series DBMS

Score	130.36
Rank	#8	Overall
	#5	Relational DBMS

Website

firebase.google.com/products/firestore

www.intersystems.com/products/cache

opentsdb.net

www.snowflake.com

Technical documentation

firebase.google.com/docs/firestore

docs.intersystems.com

opentsdb.net/docs/build/html/index.html

docs.snowflake.net/manuals/index.html

Developer

FatCloud

Google

InterSystems

currently maintained by Yahoo and other contributors

Snowflake Computing Inc.

Initial release

2012

2017

1997

2011

2014

Current release

2018.1.4, May 2020

License

Commercial or Open Source

commercial

Open Source

LGPL

commercial

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

Java

Server operating systems

Windows

hosted

AIX
HP Open VMS
HP-UX
Linux
OS X
Solaris
Windows

Linux
Windows

hosted

Data scheme

schema-free

depending on used data model

schema-free

yes

support of semi-structured data formats (JSON, XML, Avro)

Typing

predefined data types such as float or date

yes

numeric data for metrics, strings for tags

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

Via inetgration in SQL Server

yes

APIs and other access methods

.NET Client API
LINQ
RESTful HTTP API
RPC
Windows WCF Bindings

Android
gRPC (using protocol buffers) API
iOS
JavaScript API
RESTful HTTP API

.NET Client API
JDBC
ODBC
RESTful HTTP API

HTTP API
Telnet API

CLI Client
JDBC
ODBC

Supported programming languages

Go
Java
JavaScript
JavaScript (Node.js)
Objective-C
Python

C#
C++
Java

Erlang
Go
Java
Python
R
Ruby

JavaScript (Node.js)
Python

Server-side scripts

Stored procedures

yes

via applications

yes, Firebase Rules & Cloud Functions

yes

user defined functions

Triggers

yes

via applications

yes, with Cloud Functions

yes

similar concept for controling cloud resources

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

Sharding

based on HBase

yes

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

Multi-source replication

Source-replica replication

selectable replication factor

based on HBase

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Using Cloud Dataflow

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency
Immediate Consistency

Immediate Consistency

based on HBase

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

yes

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

Can implement custom security layer via applications

Access rights for users, groups and roles based on Google Cloud Identity and Access Management. Security Rules for 3rd party authentication using Firebase Auth.

Access rights for users, groups and roles

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

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