DBMS > Blazegraph vs. EJDB vs. Stardog vs. SWC-DB

System Properties Comparison Blazegraph vs. EJDB vs. Stardog vs. SWC-DB

Please select another system to include it in the comparison.

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.

Embeddable document-store database library with JSON representation of queries (in MongoDB style)

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

A high performance, scalable Wide Column DBMS

Primary database model

Secondary database models

Time Series DBMS

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

Score	0.81
Rank	#213	Overall
	#19	Graph DBMS
	#8	RDF stores

Score	0.31
Rank	#296	Overall
	#44	Document stores

Score	2.07
Rank	#122	Overall
	#11	Graph DBMS
	#6	RDF stores

Score	0.08
Rank	#364	Overall
	#13	Wide column stores

Website

blazegraph.com

github.com/Softmotions/ejdb

www.stardog.com

github.com/kashirin-alex/swc-db
www.swcdb.org

Technical documentation

wiki.blazegraph.com

github.com/Softmotions/ejdb/blob/master/README.md

docs.stardog.com

Developer

Blazegraph

Softmotions

Stardog-Union

Alex Kashirin

Initial release

2006

2012

2010

2020

Current release

2.1.5, March 2019

7.3.0, May 2020

0.5, April 2021

License

Commercial or Open Source

Open Source

extended commercial license available

Open Source

GPLv2

commercial

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

Open Source

GPL V3

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

server-less

Linux
macOS
Windows

Linux

Data scheme

schema-free

schema-free and OWL/RDFS-schema support

schema-free

Typing

predefined data types such as float or date

yes

RDF literal types

yes

string, integer, double, bool, date, object_id

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

supports real-time indexing in full-text and geospatial

SQL

Support of SQL

SPARQL is used as query language

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

SQL-like query language

APIs and other access methods

Java API
RESTful HTTP API
SPARQL QUERY
SPARQL UPDATE
TinkerPop 3

in-process shared library

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

Proprietary protocol
Thrift

Supported programming languages

.Net
C
C++
Java
JavaScript
PHP
Python
Ruby

Actionscript
C
C#
C++
Go
Java
JavaScript (Node.js)
Lua
Objective-C
Pike
Python
Ruby

.Net
Clojure
Groovy
Java
JavaScript
Python
Ruby

C++

Server-side scripts

Stored procedures

yes

user defined functions and aggregates, HTTP Server extensions in Java

Triggers

yes

via event handlers

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes

none

Multi-source replication in HA-Cluster

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 in HA-Cluster

Immediate Consistency

Foreign keys

Referential integrity

yes

Relationships in Graphs

typically not needed, however similar functionality with collection joins possible

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

Read/Write Locking

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)

Access rights for users and roles

More information provided by the system vendor

We invite representatives of system vendors to contact us for updating and extending the system information,
and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

Related products and services

We invite representatives of vendors of related products to contact us for presenting information about their offerings here.

More resources

Recent citations in the news

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

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

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

2022 All O-Zone Football Team
17 December 2022, Ozarks Sports Zone

provided by Google News

Share this page