DBMS > Amazon Neptune vs. Infobright vs. ObjectBox vs. Splunk

System Properties Comparison Amazon Neptune vs. Infobright vs. ObjectBox vs. Splunk

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Editorial information provided by DB-Engines

Name

Description

Fast, reliable graph database built for the cloud

High performant column-oriented DBMS for analytic workloads using MySQL or PostgreSQL as a frontend

Lightweight, fast on-device database for IoT, Mobile and Embedded devices, persisting and synchronising objects and vectors

Analytics Platform for Big Data

Primary database model

Graph DBMS
RDF store

Relational DBMS

Object oriented DBMS
Vector DBMS

Search engine

Secondary database models

Time Series DBMS

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	0.88
Rank	#198	Overall
	#92	Relational DBMS

Score	1.08
Rank	#179	Overall
	#6	Object oriented DBMS
	#9	Vector DBMS

Score	93.02
Rank	#13	Overall
	#2	Search engines

Website

aws.amazon.com/neptune

ignitetech.com/softwarelibrary/infobrightdb

github.com/objectbox
objectbox.io

www.splunk.com

Technical documentation

aws.amazon.com/neptune/developer-resources

docs.objectbox.io

docs.splunk.com/Documentation/Splunk

Developer

Amazon

Ignite Technologies Inc.; formerly InfoBright Inc.

ObjectBox Limited

Splunk Inc.

Initial release

2017

2005

2017

2003

Current release

4.0 (May 2024)

License

Commercial or Open Source

commercial

The open source (GPLv2) version did not support inserts/updates/deletes and was discontinued with July 2016

Bindings are released under Apache 2.0

Apache License 2.0

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

C and C++

Server operating systems

hosted

Linux
Windows

Android
Any POSIX system
Docker
iOS
Linux
macOS
QNX
Windows

Linux
OS X
Solaris
Windows

Data scheme

schema-free

yes

Typing

predefined data types such as float or date

yes

yes, plus "flex" map-like 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

Secondary indexes

Knowledge Grid Technology used instead

yes

SQL

Support of SQL

yes

Splunk Search Processing Language for search commands

APIs and other access methods

OpenCypher
RDF 1.1 / SPARQL 1.1
TinkerPop Gremlin

ADO.NET
JDBC
ODBC

Proprietary native API

HTTP REST

Supported programming languages

C#
Go
Java
JavaScript
PHP
Python
Ruby
Scala

.Net
C
C#
C++
D
Eiffel
Erlang
Haskell
Java
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl

C
C++
Dart (Flutter)
Go
Java
Kotlin
Python
Swift

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

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.

Source-replica replication

Data sync between devices allowing occasional connected databases to work completely offline

Multi-source replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

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

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 capabilities

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

yes

User concepts

Access control

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

fine grained access rights according to SQL-standard

exploiting MySQL or PostgreSQL frontend capabilities

yes

Access rights for users and roles

More information provided by the system vendor

News

MongoDB Realm & Device Sync alternatives – ObjectBox
17 September 2024

Local AI – what it is and why we need it
11 September 2024

First on-device Vector Database (aka Semantic Index) for iOS
24 July 2024

Retrieval Augmented Generation (RAG) with vector databases: Expanding AI Capabilities
18 June 2024

The on-device Vector Database for Android and Java
29 May 2024

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More resources

DB-Engines blog posts

Enterprise Search Engines almost double their popularity in the last 12 months
2 July 2014, Paul Andlinger

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Recent citations in the news

How Amazon stores deliver trustworthy shopping and seller experiences using Amazon Neptune
18 September 2024, AWS Blog

Hydrating the Natural History Museum’s Planetary Knowledge Base with Amazon Neptune and Open Data on AWS
13 September 2024, AWS Blog

Using knowledge graphs to build GraphRAG applications with Amazon Bedrock and Amazon Neptune
1 August 2024, AWS Blog

How Prisma Cloud built Infinity Graph using Amazon Neptune and Amazon OpenSearch Service
27 August 2024, AWS Blog

New Amazon Neptune engine version delivers up to 9 times faster and 10 times higher throughput for openCypher query performance
23 July 2024, AWS Blog

provided by Google News

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