DBMS > Firebase Realtime Database vs. Hypertable vs. Stardog vs. WakandaDB

System Properties Comparison Firebase Realtime Database vs. Hypertable vs. Stardog vs. WakandaDB

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Editorial information provided by DB-Engines

Name

Hypertable has stopped its further development with March 2016 and is removed 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.

An open source BigTable implementation based on distributed file systems such as Hadoop

Enterprise Knowledge Graph platform and graph DBMS with high availability, high performance reasoning, and virtualization

WakandaDB is embedded in a server that provides a REST API and a server-side javascript engine to access data

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	2.02
Rank	#123	Overall
	#11	Graph DBMS
	#6	RDF stores

Score	0.03
Rank	#364	Overall
	#17	Object oriented DBMS

Website

firebase.google.com/products/realtime-database

www.stardog.com

wakanda.github.io

Technical documentation

firebase.google.com/docs/database

docs.stardog.com

wakanda.github.io/doc

Developer

Google

acquired by Google 2014

Hypertable Inc.

Stardog-Union

Wakanda SAS

Initial release

2012

2009

2010

2012

Current release

0.9.8.11, March 2016

7.3.0, May 2020

2.7.0 (April 29, 2019), April 2019

License

Commercial or Open Source

commercial

Open Source

GNU version 3. Commercial license available

commercial

60-day fully-featured trial license; 1-year fully-featured non-commercial use license for academics/students

Open Source

AGPLv3, extended commercial license available

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

C++

Java

C++, JavaScript

Server operating systems

hosted

Linux
OS X
Windows

an inofficial Windows port is available

Linux
macOS
Windows

Linux
OS X
Windows

Data scheme

schema-free

schema-free and OWL/RDFS-schema support

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.

Import/export of XML data possible

Secondary indexes

yes

restricted

only exact value or prefix value scans

yes

supports real-time indexing in full-text and geospatial

SQL

Support of SQL

Yes, compatible with all major SQL variants through dedicated BI/SQL Server

APIs and other access methods

Android
iOS
JavaScript API
RESTful HTTP API

C++ API
Thrift

GraphQL query language
HTTP API
Jena RDF API
OWL
RDF4J API
Sesame REST HTTP Protocol
SNARL
SPARQL
Spring Data
Stardog Studio
TinkerPop 3

RESTful HTTP API

Supported programming languages

Java
JavaScript
Objective-C

C++
Java
Perl
PHP
Python
Ruby

.Net
Clojure
Groovy
Java
JavaScript
Python
Ruby

JavaScript

Server-side scripts

Stored procedures

limited functionality with using 'rules'

user defined functions and aggregates, HTTP Server extensions in Java

yes

Triggers

Callbacks are triggered when data changes

yes

via event handlers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor on file system level

Multi-source replication in HA-Cluster

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

Immediate Consistency

Immediate Consistency in HA-Cluster

Immediate Consistency

Foreign keys

Referential integrity

yes

relationships in graphs

Transaction concepts

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

yes

ACID

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.

yes

User concepts

Access control

yes, based on authentication and database rules

Access rights for users and roles

yes

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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