DBMS > Faircom DB vs. Firebase Realtime Database vs. Google BigQuery vs. LokiJS vs. OpenTSDB

System Properties Comparison Faircom DB vs. Firebase Realtime Database vs. Google BigQuery vs. LokiJS vs. OpenTSDB

Editorial information provided by DB-Engines

Name

Description

Native high-speed multi-model DBMS for relational and key-value store data simultaneously accessible through SQL and NoSQL APIs.

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

Large scale data warehouse service with append-only tables

In-memory JavaScript DBMS

Scalable Time Series DBMS based on HBase

Primary database model

Key-value store
Relational DBMS

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

Score	0.29
Rank	#304	Overall
	#43	Key-value stores
	#136	Relational DBMS

Score	13.64
Rank	#39	Overall
	#6	Document stores

Score	58.10
Rank	#19	Overall
	#13	Relational DBMS

Score	0.49
Rank	#260	Overall
	#42	Document stores

Score	1.68
Rank	#142	Overall
	#12	Time Series DBMS

Website

www.faircom.com/products/faircom-db

firebase.google.com/products/realtime-database

cloud.google.com/bigquery

github.com/techfort/LokiJS

opentsdb.net

Technical documentation

docs.faircom.com/docs/en/UUID-7446ae34-a1a7-c843-c894-d5322e395184.html

firebase.google.com/docs/database

cloud.google.com/bigquery/docs

techfort.github.io/LokiJS

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

Developer

FairCom Corporation

Google

acquired by Google 2014

Google

currently maintained by Yahoo and other contributors

Initial release

1979

2012

2010

2014

2011

Current release

V12, November 2020

License

Commercial or Open Source

commercial

Restricted, free version available

commercial

Open Source

LGPL

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

ANSI C, C++

JavaScript

Java

Server operating systems

AIX
FreeBSD
HP-UX
Linux
NetBSD
OS X
QNX
SCO
Solaris
VxWorks
Windows

easily portable to other OSs

hosted

server-less, requires a JavaScript environment (browser, Node.js)

Linux
Windows

Data scheme

schema free, schema optional, schema required, partial schema,

schema-free

yes

schema-free

Typing

predefined data types such as float or date

yes, ANSI SQL Types, JSON, typed binary structures

yes

numeric data for metrics, strings for tags

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 views

SQL

Support of SQL

yes, ANSI SQL with proprietary extensions

yes

APIs and other access methods

ADO.NET
Direct SQL
JDBC
JPA
ODBC
RESTful HTTP/JSON API
RESTful MQTT/JSON API
RPC

Android
iOS
JavaScript API
RESTful HTTP API

RESTful HTTP/JSON API

JavaScript API

HTTP API
Telnet API

Supported programming languages

.Net
C
C#
C++
Java
JavaScript (Node.js and browser)
PHP
Python
Visual Basic

Java
JavaScript
Objective-C

.Net
Java
JavaScript
Objective-C
PHP
Python
Ruby

JavaScript

Erlang
Go
Java
Python
R
Ruby

Server-side scripts

Stored procedures

yes

.Net, JavaScript, C/C++

limited functionality with using 'rules'

user defined functions

in JavaScript

View functions in JavaScript

Triggers

yes

Callbacks are triggered when data changes

yes

Partitioning methods

Methods for storing different data on different nodes

File partitioning, horizontal partitioning, sharding

Customizable business rules for table partitioning

none

Sharding

based on HBase

Replication methods

Methods for redundantly storing data on multiple nodes

yes, configurable to be parallel or serial, synchronous or asynchronous, uni-directional or bi-directional, ACID-consistent or eventually consistent (with custom conflict resolution).

none

selectable replication factor

based on HBase

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency
Immediate Consistency
Tunable consistency per server, database, table, and transaction

Eventual Consistency

if the client is offline
Immediate Consistency

if the client is online

Immediate Consistency

none

Immediate Consistency

based on HBase

Foreign keys

Referential integrity

yes

Transaction concepts

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

tunable from ACID to Eventually Consistent

yes

Since BigQuery is designed for querying data

atomic operations within a single collection possible

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

Yes, tunable from durable to delayed durability to in-memory

yes

Serialization of a DB in a Node.JS/Cordova/PhoneGap environment. Usage of the IndexedDB-API in a browser.

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

Fine grained access rights according to SQL-standard with additional protections for files

yes, based on authentication and database rules

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

Google Cloud Identity & Access Management (IAM)

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