DBMS > Blazegraph vs. Blueflood vs. Oracle vs. Solr

System Properties Comparison Blazegraph vs. Blueflood vs. Oracle vs. Solr

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.

Scalable TimeSeries DBMS based on Cassandra

Widely used RDBMS

A widely used distributed, scalable search engine based on Apache Lucene

Primary database model

Secondary database models

Document store
Graph DBMS

with Oracle Spatial and Graph
RDF store

with Oracle Spatial and Graph
Spatial DBMS

with Oracle Spatial and Graph
Vector DBMS

since Oracle 23

Spatial DBMS

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	0.06
Rank	#353	Overall
	#34	Time Series DBMS

Score	1236.29
Rank	#1	Overall
	#1	Relational DBMS

Score	42.91
Rank	#24	Overall
	#3	Search engines

Website

blazegraph.com

blueflood.io

www.oracle.com/database

solr.apache.org

Technical documentation

wiki.blazegraph.com

github.com/rax-maas/blueflood/wiki

docs.oracle.com/en/database

solr.apache.org/resources.html

Developer

Blazegraph

Rackspace

Oracle

Apache Software Foundation

Initial release

2006

2013

1980

2006

Current release

2.1.5, March 2019

23c, September 2023

9.6.0, April 2024

License

Commercial or Open Source

Open Source

extended commercial license available

Open Source

Apache 2.0

commercial

restricted free version is available

Open Source

Apache Version 2

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 and C++

Java

Server operating systems

Linux
OS X
Windows

Linux
OS X

AIX
HP-UX
Linux
OS X
Solaris
Windows
z/OS

All OS with a Java VM

runs as a servlet in servlet container (e.g. Tomcat, Jetty is included)

Data scheme

schema-free

predefined scheme

yes

Schemaless in JSON and XML columns

yes

Dynamic Fields enables on-the-fly addition of new fields

Typing

predefined data types such as float or date

yes

RDF literal types

yes

supports customizable data types and automatic typing

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

All search fields are automatically indexed

SQL

Support of SQL

SPARQL is used as query language

yes

with proprietary extensions

Solr Parallel SQL Interface

APIs and other access methods

Java API
RESTful HTTP API
SPARQL QUERY
SPARQL UPDATE
TinkerPop 3

HTTP REST

JDBC
ODBC
ODP.NET
Oracle Call Interface (OCI)

Java API
RESTful HTTP/JSON API

Supported programming languages

.Net
C
C++
Java
JavaScript
PHP
Python
Ruby

C
C#
C++
Clojure
Cobol
Delphi
Eiffel
Erlang
Fortran
Groovy
Haskell
Java
JavaScript
Lisp
Objective C
OCaml
Perl
PHP
Python
R
Ruby
Scala
Tcl
Visual Basic

.Net
Erlang
Java
JavaScript
any language that supports sockets and either XML or JSON
Perl
PHP
Python
Ruby
Scala

Server-side scripts

Stored procedures

yes

PL/SQL

also stored procedures in Java possible

Java plugins

Triggers

yes

User configurable commands triggered on index changes

Partitioning methods

Methods for storing different data on different nodes

Sharding

based on Cassandra

Sharding, horizontal partitioning

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes

selectable replication factor

based on Cassandra

Multi-source replication
Source-replica replication

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

can be realized in PL/SQL

spark-solr: github.com/lucidworks/spark-solr and streaming expressions to reduce

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency or Eventual Consistency depending on configuration

Eventual Consistency

based on Cassandra
Immediate Consistency

based on Cassandra

Immediate Consistency

Eventual Consistency

Foreign keys

Referential integrity

yes

Relationships in Graphs

yes

Transaction concepts

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

ACID

isolation level can be parameterized

optimistic locking

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

Version 12c introduced the new option 'Oracle Database In-Memory'

yes

User concepts

Access control

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

fine grained access rights according to SQL-standard

yes

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.