DBMS > Google BigQuery vs. PouchDB vs. Realm vs. Yanza

System Properties Comparison Google BigQuery vs. PouchDB vs. Realm vs. Yanza

Please select another system to include it in the comparison.

Editorial information provided by DB-Engines

Name

Yanza seems to be discontinued. Therefore it is excluded from the DB-Engines Ranking.

Description

Large scale data warehouse service with append-only tables

JavaScript DBMS with an API inspired by CouchDB

A DBMS built for use on mobile devices that’s a fast, easy to use alternative to SQLite and Core Data

Time Series DBMS for IoT Applications

Primary database model

Relational DBMS

Document store

Time Series DBMS

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

Score	58.10
Rank	#19	Overall
	#13	Relational DBMS

Score	2.34
Rank	#112	Overall
	#21	Document stores

Score	7.41
Rank	#52	Overall
	#8	Document stores

Website

cloud.google.com/bigquery

pouchdb.com

realm.io

yanza.com

Technical documentation

cloud.google.com/bigquery/docs

pouchdb.com/guides

realm.io/docs

Developer

Google

Apache Software Foundation

Realm, acquired by MongoDB in May 2019

Yanza

Initial release

2010

2012

2014

2015

Current release

7.1.1, June 2019

License

Commercial or Open Source

commercial

Open Source

commercial

free version available

Cloud-based only

Only available as a cloud service

yes

but mainly used as a service provided by Yanza

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

JavaScript

Server operating systems

hosted

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

Android
Backend: server-less
iOS
Windows

Windows

Data scheme

yes

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

yes

SQL

Support of SQL

yes

APIs and other access methods

RESTful HTTP/JSON API

HTTP REST

only for PouchDB Server
JavaScript API

HTTP API

Supported programming languages

.Net
Java
JavaScript
Objective-C
PHP
Python
Ruby

JavaScript

.Net
Java

with Android only
Objective-C
React Native
Swift

any language that supports HTTP calls

Server-side scripts

Stored procedures

user defined functions

in JavaScript

View functions in JavaScript

runs within the applications so server-side scripts are unnecessary

Triggers

yes

Change Listeners

yes

Timer and event based

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

with a proxy-based framework, named couchdb-lounge

none

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication

also with CouchDB databases
Source-replica replication

also with CouchDB databases

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

Transaction concepts

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

Since BigQuery is designed for querying data

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

by using IndexedDB, WebSQL or LevelDB as backend

yes

In-memory capabilities

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

yes

In-Memory realm

User concepts

Access control

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

Google Cloud Identity & Access Management (IAM)

yes

More information provided by the system vendor

We invite representatives of system vendors to contact us for updating and extending the system information,
and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.