DBMS > FeatureBase vs. Firebase Realtime Database vs. Graph Engine vs. Transbase

System Properties Comparison FeatureBase vs. Firebase Realtime Database vs. Graph Engine vs. Transbase

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Editorial information provided by DB-Engines

Name

Description

Real-time database platform that powers real-time analytics and machine learning applications by simultaneously executing low-latency, high-throughput, and highly concurrent workloads.

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

A distributed in-memory data processing engine, underpinned by a strongly-typed RAM store and a general distributed computation engine

A resource-optimized, high-performance, universally applicable RDBMS

Primary database model

Relational DBMS

Document store

Graph DBMS
Key-value store

Relational DBMS

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

Score	0.22
Rank	#309	Overall
	#139	Relational DBMS

Score	14.29
Rank	#39	Overall
	#6	Document stores

Score	0.61
Rank	#240	Overall
	#21	Graph DBMS
	#35	Key-value stores

Score	0.11
Rank	#341	Overall
	#150	Relational DBMS

Website

www.featurebase.com

firebase.google.com/products/realtime-database

www.graphengine.io

www.transaction.de/en/products/transbase.html

Technical documentation

docs.featurebase.com

firebase.google.com/docs/database

www.graphengine.io/docs/manual

www.transaction.de/en/products/transbase/features.html

Developer

Molecula and Pilosa Open Source Contributors

Google

acquired by Google 2014

Microsoft

Transaction Software GmbH

Initial release

2017

2012

2010

1987

Current release

2022, May 2022

Transbase 8.3, 2022

License

Commercial or Open Source

commercial

Open Source

MIT License

commercial

free development license

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

.NET and C

C and C++

Server operating systems

Linux
macOS

hosted

.NET

FreeBSD
Linux
macOS
Solaris
Windows

Data scheme

yes

schema-free

yes

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

SQL queries

yes

APIs and other access methods

gRPC
JDBC
Kafka Connector
ODBC

Android
iOS
JavaScript API
RESTful HTTP API

RESTful HTTP API

ADO.NET
JDBC
ODBC
Proprietary native API

Supported programming languages

Java
Python

Java
JavaScript
Objective-C

C#
C++
F#
Visual Basic

C
C#
C++
Java
JavaScript
Kotlin
Objective-C
PHP
Python

Server-side scripts

Stored procedures

limited functionality with using 'rules'

yes

Triggers

Callbacks are triggered when data changes

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Source-replica replication

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

Foreign keys

Referential integrity

yes

Transaction concepts

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

yes

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes, using Linux fsync

yes

optional: either by committing a write-ahead log (WAL) to the local persistent storage or by dumping the memory to a persistent storage

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

fine grained access rights according to SQL-standard

More information provided by the system vendor

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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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