DBMS > Blazegraph vs. Firebolt vs. GigaSpaces

System Properties Comparison Blazegraph vs. Firebolt vs. GigaSpaces

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Editorial information provided by DB-Engines

Name

Amazon has acquired Blazegraph's domain and (probably) product. It is said that Amazon Neptune is based on Blazegraph.

Description

High-performance graph database supporting Semantic Web (RDF/SPARQL) and Graph Database (tinkerpop3, blueprints, vertex-centric) APIs with scale-out and High Availability.

Highly scalable cloud data warehouse and analytics product

Forked from Clickhouse

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

Primary database model

Graph DBMS
RDF store

Relational DBMS

Document store
Object oriented DBMS

Values are user defined objects

Secondary database models

Graph DBMS
Search engine

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

Score	0.75
Rank	#213	Overall
	#18	Graph DBMS
	#7	RDF stores

Score	0.84
Rank	#206	Overall
	#96	Relational DBMS

Score	1.14
Rank	#169	Overall
	#27	Document stores
	#6	Object oriented DBMS

Website

blazegraph.com

www.firebolt.io

www.gigaspaces.com

Technical documentation

wiki.blazegraph.com

docs.firebolt.io

docs.gigaspaces.com/latest/landing.html

Developer

Blazegraph

Firebolt Analytics Inc.

Gigaspaces Technologies

Initial release

2006

2020

2000

Current release

2.1.5, March 2019

15.5, September 2020

License

Commercial or Open Source

Open Source

extended commercial license available

commercial

Open Source

Apache Version 2; Commercial licenses 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

Java

Java, C++, .Net

Server operating systems

Linux
OS X
Windows

hosted

Linux
macOS
Solaris
Windows

Data scheme

schema-free

yes

schema-free

Typing

predefined data types such as float or date

yes

RDF literal types

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

Secondary indexes

yes

SQL

Support of SQL

SPARQL is used as query language

yes

SQL-99 for query and DML statements

APIs and other access methods

Java API
RESTful HTTP API
SPARQL QUERY
SPARQL UPDATE
TinkerPop 3

.Net
ODBC
RESTful HTTP API

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

Supported programming languages

.Net
C
C++
Java
JavaScript
PHP
Python
Ruby

Go
JavaScript (Node.js)
Python

.Net
C++
Java
Python
Scala

Server-side scripts

Stored procedures

yes

Triggers

yes, event driven architecture

Partitioning methods

Methods for storing different data on different nodes

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes

depending on storage layer

Multi-source replication

synchronous or asynchronous
Source-replica replication

synchronous or asynchronous

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Map-Reduce pattern can be built with XAP task executors

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency or Eventual Consistency depending on configuration

Immediate Consistency

Consistency level configurable: ALL, QUORUM, ANY

Foreign keys

Referential integrity

yes

Relationships in Graphs

Transaction concepts

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

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

Security and Authentication via Web Application Container (Tomcat, Jetty)

Role-based access control

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More resources

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provided by Google News

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