DBMS > Blazegraph vs. Oracle vs. Quasardb vs. SiteWhere vs. Spark SQL

System Properties Comparison Blazegraph vs. Oracle vs. Quasardb vs. SiteWhere vs. Spark SQL

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.

Widely used RDBMS

Distributed, high-performance timeseries database

M2M integration platform for persisting/querying time series data

Spark SQL is a component on top of 'Spark Core' for structured data processing

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

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

Score	0.77
Rank	#222	Overall
	#20	Graph DBMS
	#8	RDF stores

Score	1234.27
Rank	#1	Overall
	#1	Relational DBMS

Score	0.19
Rank	#327	Overall
	#30	Time Series DBMS

Score	0.06
Rank	#367	Overall
	#36	Time Series DBMS

Score	19.15
Rank	#33	Overall
	#20	Relational DBMS

Website

blazegraph.com

www.oracle.com/database

quasar.ai

github.com/sitewhere/sitewhere

spark.apache.org/sql

Technical documentation

wiki.blazegraph.com

docs.oracle.com/en/database

doc.quasar.ai/master

sitewhere1.sitewhere.io/index.html

spark.apache.org/docs/latest/sql-programming-guide.html

Developer

Blazegraph

Oracle

quasardb

SiteWhere

Apache Software Foundation

Initial release

2006

1980

2009

2010

2014

Current release

2.1.5, March 2019

23c, September 2023

3.14.1, January 2024

3.5.0 ( 2.13), September 2023

License

Commercial or Open Source

Open Source

extended commercial license available

commercial

restricted free version is available

commercial

Free community edition, Non-profit organizations and non-commercial usage are eligible for free licenses

Open Source

Common Public Attribution License Version 1.0

Open Source

Apache 2.0

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

Java

C and C++

C++

Java

Scala

Server operating systems

Linux
OS X
Windows

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

BSD
Linux
OS X
Windows

Linux
OS X
Windows

Data scheme

schema-free

yes

Schemaless in JSON and XML columns

schema-free

predefined scheme

yes

Typing

predefined data types such as float or date

yes

RDF literal types

yes

integer and binary

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

with tags

SQL

Support of SQL

SPARQL is used as query language

yes

with proprietary extensions

SQL-like query language

SQL-like DML and DDL statements

APIs and other access methods

Java API
RESTful HTTP API
SPARQL QUERY
SPARQL UPDATE
TinkerPop 3

JDBC
ODBC
ODP.NET
Oracle Call Interface (OCI)

HTTP API

HTTP REST

JDBC
ODBC

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
C
C#
C++
Go
Java
JavaScript (Node.js)
PHP
Python
R

Java
Python
R
Scala

Server-side scripts

Stored procedures

yes

PL/SQL

also stored procedures in Java possible

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

Sharding, horizontal partitioning

Sharding

consistent hashing

Sharding

based on HBase

yes, utilizing Spark Core

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Multi-source replication
Source-replica replication

Source-replica replication with selectable replication factor

selectable replication factor

based on HBase

none

MapReduce

Offers an API for user-defined Map/Reduce methods

can be realized in PL/SQL

with Hadoop integration

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency or Eventual Consistency depending on configuration

Immediate 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

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

by using LevelDB

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

Transient mode

User concepts

Access control

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

fine grained access rights according to SQL-standard

Cryptographically strong user authentication and audit trail

Users with fine-grained authorization concept

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