DBMS > Blazegraph vs. InfinityDB vs. searchxml

System Properties Comparison Blazegraph vs. InfinityDB vs. searchxml

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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.

A Java embedded Key-Value Store which extends the Java Map interface

DBMS for structured and unstructured content wrapped with an application server

Primary database model

Graph DBMS
RDF store

Key-value store

Native XML DBMS
Search engine

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

Score	0.75
Rank	#219	Overall
	#19	Graph DBMS
	#8	RDF stores

Score	0.00
Rank	#378	Overall
	#57	Key-value stores

Score	0.00
Rank	#383	Overall
	#7	Native XML DBMS
	#25	Search engines

Website

blazegraph.com

boilerbay.com

www.searchxml.net/category/products

Technical documentation

wiki.blazegraph.com

boilerbay.com/infinitydb/manual

www.searchxml.net/support/handouts

Developer

Blazegraph

Boiler Bay Inc.

informationpartners gmbh

Initial release

2006

2002

2015

Current release

2.1.5, March 2019

4.0

1.0

License

Commercial or Open Source

Open Source

extended commercial license available

commercial

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

Java

C++

Server operating systems

Linux
OS X
Windows

All OS with a Java VM

Windows

Data scheme

schema-free

yes

nested virtual Java Maps, multi-value, logical â€˜tuple spaceâ€™ runtime Schema upgrade

schema-free

Typing

predefined data types such as float or date

yes

RDF literal types

yes

all Java primitives, Date, CLOB, BLOB, huge sparse arrays

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.

yes

Secondary indexes

yes

manual creation possible, using inversions based on multi-value capability

yes

SQL

Support of SQL

SPARQL is used as query language

APIs and other access methods

Java API
RESTful HTTP API
SPARQL QUERY
SPARQL UPDATE
TinkerPop 3

Access via java.util.concurrent.ConcurrentNavigableMap Interface
Proprietary API to InfinityDB ItemSpace (boilerbay.com/docs/ItemSpaceDataStructures.htm)

RESTful HTTP API
WebDAV
XQuery
XSLT

Supported programming languages

.Net
C
C++
Java
JavaScript
PHP
Python
Ruby

Java

C++

most other programming languages supported via APIs

Server-side scripts

Stored procedures

yes

on the application server

Triggers

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes

none

yes

sychronisation to multiple collections

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency or Eventual Consistency depending on configuration

Immediate Consistency

READ-COMMITTED or SERIALIZED

Immediate Consistency

Foreign keys

Referential integrity

yes

Relationships in Graphs

manual creation possible, using inversions based on multi-value capability

Transaction concepts

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

ACID

Optimistic locking for transactions; no isolation for bulk loads

multiple readers, single writer

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.

User concepts

Access control

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

Domain, group and role-based access control at the document level and for application services

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More resources

Recent citations in the news

Harnessing GPUs Delivers a Big Speedup for Graph Analytics
15 December 2015, Datanami

Back to the future: Does graph database success hang on query language?
5 March 2018, ZDNet

This AI Paper Introduces A Comprehensive RDF Dataset With Over 26 Billion Triples Covering Scholarly Data Across All Scientific Disciplines
19 August 2023, MarkTechPost

Representation Learning on RDF* and LPG Knowledge Graphs
24 September 2020, Towards Data Science

Faster with GPUs: 5 turbocharged databases
26 September 2016, InfoWorld

provided by Google News

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