DBMS > FatDB vs. Google Cloud Firestore vs. Heroic vs. OpenTSDB vs. Tigris

System Properties Comparison FatDB vs. Google Cloud Firestore vs. Heroic vs. OpenTSDB vs. Tigris

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.

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.

Time Series DBMS built at Spotify based on Cassandra or Google Cloud Bigtable, and ElasticSearch

Scalable Time Series DBMS based on HBase

A horizontally scalable, ACID transactional, document database available both as a fully managed cloud service and for deployment on self-managed infrastructure

Primary database model

Document store
Key-value store

Document store

Time Series DBMS

Document store
Key-value store
Search engine
Time Series DBMS

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

Score	6.46
Rank	#54	Overall
	#9	Document stores

Score	0.02
Rank	#365	Overall
	#37	Time Series DBMS

Score	1.58
Rank	#143	Overall
	#12	Time Series DBMS

Score	0.05
Rank	#358	Overall
	#50	Document stores
	#53	Key-value stores
	#23	Search engines
	#36	Time Series DBMS

Website

firebase.google.com/products/firestore

github.com/spotify/heroic

opentsdb.net

www.tigrisdata.com

Technical documentation

firebase.google.com/docs/firestore

spotify.github.io/heroic

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

www.tigrisdata.com/docs

Developer

FatCloud

Google

Spotify

currently maintained by Yahoo and other contributors

Tigris Data, Inc.

Initial release

2012

2017

2014

2011

2022

License

Commercial or Open Source

commercial

Open Source

Apache 2.0

Open Source

LGPL

Open Source

Apache Version 2.0

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

Server operating systems

Windows

hosted

Linux
Windows

Linux
macOS
Windows

Data scheme

schema-free

yes

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.

Secondary indexes

yes

via Elasticsearch

yes

SQL

Support of SQL

Via inetgration in SQL Server

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

HQL (Heroic Query Language, a JSON-based language)
HTTP API

HTTP API
Telnet API

CLI Client
gRPC
RESTful HTTP API

Supported programming languages

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

Erlang
Go
Java
Python
R
Ruby

Go
Java
JavaScript (Node.js)

Server-side scripts

Stored procedures

yes

via applications

yes, Firebase Rules & Cloud Functions

Triggers

yes

via applications

yes, with Cloud Functions

Partitioning methods

Methods for storing different data on different nodes

Sharding

based on HBase

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

Multi-source replication

yes

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

Eventual Consistency
Immediate Consistency

Immediate Consistency

based on HBase

Immediate Consistency

Foreign keys

Referential integrity

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

yes, using FoundationDB

In-memory capabilities

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

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 and roles

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Related products and services

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More resources

DB-Engines blog posts

Cloud-based DBMS's popularity grows at high rates
12 December 2019, Paul Andlinger

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Time Series DBMS are the database category with the fastest increase in popularity
4 July 2016, Matthias Gelbmann

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