DBMS > Amazon Neptune vs. Oracle NoSQL vs. RDF4J vs. Splunk

System Properties Comparison Amazon Neptune vs. Oracle NoSQL vs. RDF4J vs. Splunk

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Editorial information provided by DB-Engines

Name

Description

Fast, reliable graph database built for the cloud

A multi-model, scalable, distributed NoSQL database, designed to provide highly reliable, flexible, and available data management across a configurable set of storage nodes

RDF4J is a Java framework for processing RDF data, supporting both memory-based and a disk-based storage.

Analytics Platform for Big Data

Primary database model

Graph DBMS
RDF store

Document store
Key-value store
Relational DBMS

RDF store

Search engine

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

Score	2.20
Rank	#113	Overall
	#9	Graph DBMS
	#5	RDF stores

Score	3.07
Rank	#86	Overall
	#15	Document stores
	#11	Key-value stores
	#47	Relational DBMS

Score	0.72
Rank	#222	Overall
	#9	RDF stores

Score	93.02
Rank	#13	Overall
	#2	Search engines

Website

aws.amazon.com/neptune

www.oracle.com/database/nosql/technologies/nosql

rdf4j.org

www.splunk.com

Technical documentation

aws.amazon.com/neptune/developer-resources

docs.oracle.com/en/database/other-databases/nosql-database/index.html

rdf4j.org/documentation

docs.splunk.com/Documentation/Splunk

Developer

Amazon

Oracle

Since 2016 officially forked into an Eclipse project, former developer was Aduna Software.

Splunk Inc.

Initial release

2017

2011

2004

2003

Current release

24.1, May 2024

License

Commercial or Open Source

commercial

Open Source

Proprietary for Enterprise Edition (Oracle Database EE license has Oracle NoSQL database EE covered: details)

Open Source

Eclipse Distribution License (EDL), v1.0.

commercial

Limited free edition and free developer edition available

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

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

Implementation language

Java

Server operating systems

hosted

Linux
Solaris SPARC/x86

Linux
OS X
Unix
Windows

Linux
OS X
Solaris
Windows

Data scheme

schema-free

Support Fixed schema and Schema-less deployment with the ability to interoperate between them.

yes

RDF Schemas

yes

Typing

predefined data types such as float or date

yes

optional

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

SQL

Support of SQL

SQL-like DML and DDL statements

Splunk Search Processing Language for search commands

APIs and other access methods

OpenCypher
RDF 1.1 / SPARQL 1.1
TinkerPop Gremlin

RESTful HTTP API

Java API
RIO

RDF Input/Output
Sail API
SeRQL

Sesame RDF Query Language
Sesame REST HTTP Protocol
SPARQL

HTTP REST

Supported programming languages

C#
Go
Java
JavaScript
PHP
Python
Ruby
Scala

C
C#
Go
Java
JavaScript (Node.js)
Python

Java
PHP
Python

C#
Java
JavaScript
PHP
Python
Ruby

Server-side scripts

Stored procedures

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-availability zones high availability, asynchronous replication for up to 15 read replicas within a single region. Global database clusters consists of a primary write DB cluster in one region, and up to five secondary read DB clusters in different regions. Each secondary region can have up to 16 reader instances.

Electable source-replica replication per shard. Support distributed global deployment with Multi-region table feature

none

Multi-source replication

MapReduce

Offers an API for user-defined Map/Reduce methods

with Hadoop integration

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency
Immediate Consistency

depending on configuration

Eventual Consistency

Foreign keys

Referential integrity

yes

Relationships in graphs

Transaction concepts

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

ACID

configurable

ACID within a storage node (=shard)

ACID

Isolation support depends on the API used

A 'Transaction' in Splunk has a different meaning: grouping related events into a single one for later searching

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

with encyption-at-rest

yes

in-memory storage is supported as well

yes

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

yes

off heap cache

User concepts

Access control

Access rights for users and roles can be defined via the AWS Identity and Access Management (IAM)

Access rights for users and roles

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More resources

DB-Engines blog posts

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