DBMS > Firebase Realtime Database vs. Geode vs. Google BigQuery vs. Hawkular Metrics vs. LokiJS

System Properties Comparison Firebase Realtime Database vs. Geode vs. Google BigQuery vs. Hawkular Metrics vs. LokiJS

Editorial information provided by DB-Engines

Name

Description

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

Geode is a distributed data container, pooling memory, CPU, network resources, and optionally local disk across multiple processes

Large scale data warehouse service with append-only tables

Hawkular metrics is the metric storage of the Red Hat sponsored Hawkular monitoring system. It is based on Cassandra.

In-memory JavaScript DBMS

Primary database model

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

Score	14.29
Rank	#39	Overall
	#6	Document stores

Score	1.92
Rank	#131	Overall
	#23	Key-value stores

Score	60.38
Rank	#19	Overall
	#13	Relational DBMS

Score	0.00
Rank	#379	Overall
	#40	Time Series DBMS

Score	0.43
Rank	#264	Overall
	#42	Document stores

Website

firebase.google.com/products/realtime-database

geode.apache.org

cloud.google.com/bigquery

www.hawkular.org

github.com/techfort/LokiJS

Technical documentation

firebase.google.com/docs/database

geode.apache.org/docs

cloud.google.com/bigquery/docs

www.hawkular.org/hawkular-metrics/docs/user-guide

techfort.github.io/LokiJS

Developer

Google

acquired by Google 2014

Originally developed by Gemstone. They outsourced the project to Apache in 2015 but still deliver a commercial version as Gemfire.

Google

Community supported by Red Hat

Initial release

2012

2002

2010

2014

Current release

1.1, February 2017

License

Commercial or Open Source

commercial

Open Source

Apache Version 2; commercial licenses available as Gemfire

commercial

Open Source

Apache 2.0

Open Source

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

JavaScript

Server operating systems

hosted

All OS with a Java VM

the JDK (8 or later) is also required

hosted

Linux
OS X
Windows

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

Data scheme

schema-free

yes

schema-free

Typing

predefined data types such as float or date

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 views

SQL

Support of SQL

SQL-like query language (OQL)

yes

APIs and other access methods

Android
iOS
JavaScript API
RESTful HTTP API

Java Client API
Memcached protocol
RESTful HTTP API

RESTful HTTP/JSON API

HTTP REST

JavaScript API

Supported programming languages

Java
JavaScript
Objective-C

.Net
All JVM based languages
C++
Groovy
Java
Scala

.Net
Java
JavaScript
Objective-C
PHP
Python
Ruby

Go
Java
Python
Ruby

JavaScript

Server-side scripts

Stored procedures

limited functionality with using 'rules'

user defined functions

in JavaScript

View functions in JavaScript

Triggers

Callbacks are triggered when data changes

yes

Cache Event Listeners

yes

via Hawkular Alerting

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

Sharding

based on Cassandra

none

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication

selectable replication factor

based on Cassandra

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

if the client is offline
Immediate Consistency

if the client is online

Eventual Consistency

Immediate Consistency

Eventual Consistency

based on Cassandra
Immediate Consistency

based on Cassandra

none

Foreign keys

Referential integrity

Transaction concepts

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

yes

yes, on a single node

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

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

In-memory capabilities

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

yes

User concepts

Access control

yes, based on authentication and database rules

Access rights per client and object definable

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

Google Cloud Identity & Access Management (IAM)

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