DBMS > AlaSQL vs. Firebase Realtime Database vs. GigaSpaces vs. Stardog vs. Trafodion

System Properties Comparison AlaSQL vs. Firebase Realtime Database vs. GigaSpaces vs. Stardog vs. Trafodion

Editorial information provided by DB-Engines

Name

Apache Trafodion has been retired in 2021. Therefore it is excluded from the DB-Engines Ranking.

Description

JavaScript DBMS library

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

High performance in-memory data grid platform, powering three products: Smart Cache, Smart ODS (Operational Data Store), Smart Augmented Transactions

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

Transactional SQL-on-Hadoop DBMS

Primary database model

Document store
Relational DBMS

Document store

Document store
Object oriented DBMS

Values are user defined objects

Graph DBMS
RDF store

Relational DBMS

Secondary database models

Graph DBMS
Search engine

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

Score	0.46
Rank	#260	Overall
	#40	Document stores
	#121	Relational DBMS

Score	14.29
Rank	#39	Overall
	#6	Document stores

Score	0.97
Rank	#192	Overall
	#32	Document stores
	#6	Object oriented DBMS

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

Website

alasql.org

firebase.google.com/products/realtime-database

www.gigaspaces.com

www.stardog.com

trafodion.apache.org

Technical documentation

github.com/AlaSQL/alasql

firebase.google.com/docs/database

docs.gigaspaces.com/latest/landing.html

docs.stardog.com

trafodion.apache.org/documentation.html

Developer

Andrey Gershun & Mathias R. Wulff

Google

acquired by Google 2014

Gigaspaces Technologies

Stardog-Union

Apache Software Foundation, originally developed by HP

Initial release

2014

2012

2000

2010

2014

Current release

15.5, September 2020

7.3.0, May 2020

2.3.0, February 2019

License

Commercial or Open Source

Open Source

MIT-License

commercial

Open Source

Apache Version 2; Commercial licenses available

commercial

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

Open Source

Apache 2.0

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

JavaScript

Java, C++, .Net

Java

C++, Java

Server operating systems

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

hosted

Linux
macOS
Solaris
Windows

Linux
macOS
Windows

Linux

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.

XML can be used for describing objects metadata

Import/export of XML data possible

Secondary indexes

yes

supports real-time indexing in full-text and geospatial

yes

SQL

Support of SQL

Close to SQL99, but no user access control, stored procedures and host language bindings.

SQL-99 for query and DML statements

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

yes

APIs and other access methods

JavaScript API

Android
iOS
JavaScript API
RESTful HTTP API

GigaSpaces LRMI
Hibernate
JCache
JDBC
JPA
ODBC
RESTful HTTP API
Spring Data

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

ADO.NET
JDBC
ODBC

Supported programming languages

JavaScript

Java
JavaScript
Objective-C

.Net
C++
Java
Python
Scala

.Net
Clojure
Groovy
Java
JavaScript
Python
Ruby

All languages supporting JDBC/ODBC/ADO.Net

Server-side scripts

Stored procedures

limited functionality with using 'rules'

yes

user defined functions and aggregates, HTTP Server extensions in Java

Java Stored Procedures

Triggers

yes

Callbacks are triggered when data changes

yes, event driven architecture

yes

via event handlers

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

none

Multi-source replication

synchronous or asynchronous
Source-replica replication

synchronous or asynchronous

Multi-source replication in HA-Cluster

yes, via HBase

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Map-Reduce pattern can be built with XAP task executors

yes

via user defined functions and HBase

Consistency concepts

Methods to ensure consistency in a distributed system

none

Eventual Consistency

if the client is offline
Immediate Consistency

if the client is online

Immediate Consistency

Consistency level configurable: ALL, QUORUM, ANY

Immediate Consistency in HA-Cluster

Immediate Consistency

Foreign keys

Referential integrity

yes

relationships in graphs

yes

Transaction concepts

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

yes

only for local storage and DOM-storage

yes

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

by using IndexedDB, SQL.JS or proprietary FileStorage

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

Role-based access control

Access rights for users and roles

fine grained access rights according to SQL-standard

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More resources

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