DBMS > Firebase Realtime Database vs. Google Cloud Datastore vs. Hyprcubd

System Properties Comparison Firebase Realtime Database vs. Google Cloud Datastore vs. Hyprcubd

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Editorial information provided by DB-Engines

Name

Hyprcubd seems to be discontinued. Therefore it is excluded from the DB-Engines ranking.

Description

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

Automatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud Platform

Serverless Time Series DBMS

Primary database model

Document store

Time Series DBMS

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

Score	15.00
Rank	#39	Overall
	#6	Document stores

Score	4.49
Rank	#79	Overall
	#12	Document stores

Website

firebase.google.com/products/realtime-database

cloud.google.com/datastore

hyprcubd.com (offline)

Technical documentation

firebase.google.com/docs/database

cloud.google.com/datastore/docs

Developer

Google

acquired by Google 2014

Google

Hyprcubd, Inc.

Initial release

2012

2008

License

Commercial or 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

Server operating systems

hosted

Data scheme

schema-free

yes

Typing

predefined data types such as float or date

yes

yes, details here

yes

time, int, uint, float, string

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

SQL

Support of SQL

SQL-like query language (GQL)

SQL-like query language

APIs and other access methods

Android
iOS
JavaScript API
RESTful HTTP API

gRPC (using protocol buffers) API
RESTful HTTP/JSON API

gRPC (https)

Supported programming languages

Java
JavaScript
Objective-C

.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby

Server-side scripts

Stored procedures

limited functionality with using 'rules'

using Google App Engine

Triggers

Callbacks are triggered when data changes

Callbacks using the Google Apps Engine

Partitioning methods

Methods for storing different data on different nodes

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication using Paxos

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

using Google Cloud Dataflow

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

if the client is offline
Immediate Consistency

if the client is online

Immediate Consistency or Eventual Consistency depending on type of query and configuration

Strong Consistency is default for entity lookups and queries within an Entity Group (but can instead be made eventually consistent). Other queries are always eventual consistent.

Eventual Consistency

Foreign keys

Referential integrity

yes

via ReferenceProperties or Ancestor paths

Transaction concepts

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

yes

ACID

Serializable Isolation within Transactions, Read Committed outside of Transactions

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.

User concepts

Access control

yes, based on authentication and database rules

Access rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)

token access

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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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