DBMS > Firebase Realtime Database vs. Google BigQuery vs. ObjectBox vs. TimesTen vs. Yanza

System Properties Comparison Firebase Realtime Database vs. Google BigQuery vs. ObjectBox vs. TimesTen vs. Yanza

Editorial information provided by DB-Engines

Name

Yanza 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.

Large scale data warehouse service with append-only tables

Extremely fast embedded database for small devices, IoT and Mobile

In-Memory RDBMS compatible to Oracle

Time Series DBMS for IoT Applications

Primary database model

Secondary database models

Time Series DBMS

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

Score	13.64
Rank	#39	Overall
	#6	Document stores

Score	58.10
Rank	#19	Overall
	#13	Relational DBMS

Score	1.29
Rank	#166	Overall
	#5	Object oriented DBMS

Score	1.36
Rank	#161	Overall
	#75	Relational DBMS

Website

firebase.google.com/products/realtime-database

cloud.google.com/bigquery

objectbox.io

www.oracle.com/database/technologies/related/timesten.html

yanza.com

Technical documentation

firebase.google.com/docs/database

cloud.google.com/bigquery/docs

docs.objectbox.io

docs.oracle.com/database/timesten-18.1

Developer

Google

acquired by Google 2014

Google

ObjectBox Limited

Oracle, TimesTen Performance Software, HP

originally founded in HP Labs it was acquired by Oracle in 2005

Yanza

Initial release

2012

2010

2017

1998

2015

Current release

11 Release 2 (11.2.2.8.0)

License

Commercial or Open Source

commercial

Open Source

Apache License 2.0

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

C and C++

Server operating systems

hosted

Android
iOS
Linux
macOS
Windows

AIX
HP-UX
Linux
OS X
Solaris SPARC/x86
Windows

Windows

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

SQL

Support of SQL

yes

APIs and other access methods

Android
iOS
JavaScript API
RESTful HTTP API

RESTful HTTP/JSON API

Proprietary native API

JDBC
ODBC
ODP.NET
Oracle Call Interface (OCI)

HTTP API

Supported programming languages

Java
JavaScript
Objective-C

.Net
Java
JavaScript
Objective-C
PHP
Python
Ruby

C
C++
Dart
Go
Java
JavaScript

planned (as of Jan 2019)
Kotlin
Python

planned (as of Jan 2019)
Swift

C
C++
Java
PL/SQL

any language that supports HTTP calls

Server-side scripts

Stored procedures

limited functionality with using 'rules'

user defined functions

in JavaScript

PL/SQL

Triggers

Callbacks are triggered when data changes

yes

Timer and event based

Partitioning methods

Methods for storing different data on different nodes

none

Replication methods

Methods for redundantly storing data on multiple nodes

online/offline synchronization between client and server

Multi-source replication
Source-replica replication

none

MapReduce

Offers an API for user-defined Map/Reduce methods

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

Immediate Consistency or Eventual Consistency depending on configuration

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

yes

Since BigQuery is designed for querying data

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

by means of logfiles and checkpoints

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

yes, based on authentication and database rules

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

Google Cloud Identity & Access Management (IAM)

yes

fine grained access rights according to SQL-standard

More information provided by the system vendor

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