DBMS > AnzoGraph DB vs. Blazegraph vs. FileMaker vs. Oracle vs. Spark SQL

System Properties Comparison AnzoGraph DB vs. Blazegraph vs. FileMaker vs. Oracle 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

Scalable graph database built for online analytics and data harmonization with MPP scaling, high-performance analytical algorithms and reasoning, and virtualization

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

FileMaker is a cross-platform RDBMS that includes a GUI frontend.

Widely used RDBMS

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

Primary database model

Graph DBMS
RDF store

Relational DBMS

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	0.29
Rank	#303	Overall
	#25	Graph DBMS
	#14	RDF stores

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

Score	47.91
Rank	#20	Overall
	#14	Relational DBMS

Score	1244.08
Rank	#1	Overall
	#1	Relational DBMS

Score	18.04
Rank	#33	Overall
	#20	Relational DBMS

Website

cambridgesemantics.com/anzograph

blazegraph.com

www.claris.com/filemaker

www.oracle.com/database

spark.apache.org/sql

Technical documentation

docs.cambridgesemantics.com/anzograph/userdoc/home.htm

wiki.blazegraph.com

www.claris.com/resources/documentation

docs.oracle.com/en/database

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

Developer

Cambridge Semantics

Blazegraph

Claris

a subsidiary of Apple

Oracle

Apache Software Foundation

Initial release

2018

2006

1983

1980

2014

Current release

2.3, January 2021

2.1.5, March 2019

19.4.1, November 2021

23c, September 2023

3.5.0 ( 2.13), September 2023

License

Commercial or Open Source

commercial

free trial version available

Open Source

extended commercial license available

commercial

restricted free version is available

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++

Scala

Server operating systems

Linux

Linux
OS X
Windows

iOS

client part only
Linux
OS X
Windows

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

Linux
OS X
Windows

Data scheme

Schema-free and OWL/RDFS-schema support

schema-free

yes

Schemaless in JSON and XML columns

yes

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.

yes

A http query request can return the data in XML format

yes

Secondary indexes

yes

SQL

Support of SQL

SPARQL and SPARQL* as primary query language. Cypher preview.

SPARQL is used as query language

yes

via plugins

yes

with proprietary extensions

SQL-like DML and DDL statements

APIs and other access methods

Apache Mule
gRPC
JDBC
Kafka
OData access for BI tools
OpenCypher
RESTful HTTP API
SPARQL

Java API
RESTful HTTP API
SPARQL QUERY
SPARQL UPDATE
TinkerPop 3

Filemaker WebDirect
JDBC
ODBC

JDBC
ODBC
ODP.NET
Oracle Call Interface (OCI)

JDBC
ODBC

Supported programming languages

C++
Java
Python

.Net
C
C++
Java
JavaScript
PHP
Python
Ruby

PHP

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

Java
Python
R
Scala

Server-side scripts

Stored procedures

user defined functions and aggregates

yes

PL/SQL

also stored procedures in Java possible

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Automatic sharding

Sharding

none

Sharding, horizontal partitioning

yes, utilizing Spark Core

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication in MPP-Cluster

yes

Source-replica replication, warm standby

since Version 14

Multi-source replication
Source-replica replication

none

MapReduce

Offers an API for user-defined Map/Reduce methods

Kerberos/HDFS data loading

can be realized in PL/SQL

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency in MPP-Cluster

Immediate Consistency or Eventual Consistency depending on configuration

Immediate Consistency

Foreign keys

Referential integrity

not needed in graphs

yes

Relationships in Graphs

yes

Transaction concepts

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

ACID

isolation level can be parameterized

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'

User concepts

Access control

Access rights for users and roles

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

simple rights management via user accounts and connection to external directory services

fine grained access rights according to SQL-standard

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