DBMS > Amazon Neptune vs. GraphDB vs. OpenSearch

System Properties Comparison Amazon Neptune vs. GraphDB vs. OpenSearch

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Editorial information provided by DB-Engines

Name

Description

Fast, reliable graph database built for the cloud

Enterprise-ready RDF and graph database with efficient reasoning, cluster and external index synchronization support. It supports also SQL JDBC access to Knowledge Graph and GraphQL over SPARQL.

A distributed, RESTful search and analytics engine forked from Elasticsearch and based on Apache Lucene

Primary database model

Graph DBMS
RDF store

Search engine
Vector DBMS

Secondary database models

Vector DBMS

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

Score	2.13
Rank	#111	Overall
	#9	Graph DBMS
	#5	RDF stores

Score	2.59
Rank	#96	Overall
	#7	Graph DBMS
	#3	RDF stores

Score	17.38
Rank	#32	Overall
	#4	Search engines
	#2	Vector DBMS

Website

aws.amazon.com/neptune

www.ontotext.com

github.com/opensearch-project
opensearch.org

Technical documentation

aws.amazon.com/neptune/developer-resources

graphdb.ontotext.com/documentation

opensearch.org/docs/latest

Developer

Amazon

Ontotext

The OpenSearch Software Foundation

Initial release

2017

2000

2021

Current release

10.4, October 2023

2.19, February 2025

License

Commercial or Open Source

commercial

Some plugins of GraphDB Workbench are open sourced

Open Source

Apache Version 2.0

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.

STACKIT OpenSearch offers OpenSearch in a managed version in enterprise grade, 100% GDPR-compliant, for a wide range of applications like analytics, website search, offering scalability and fast data access.

Implementation language

Java

Server operating systems

hosted

All OS with a Java VM
Linux
OS X
Windows

All OS with a Java VM

Data scheme

schema-free

schema-free and OWL/RDFS-schema support; RDF shapes

schema-free

Flexible type definitions. Once a type is defined, it is persistent

Typing

predefined data types such as float or date

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.

Secondary indexes

yes, supports real-time synchronization and indexing in SOLR/Elastic search/Lucene and GeoSPARQL geometry data indexes

yes

All search fields are automatically indexed

SQL

Support of SQL

stored SPARQL accessed as SQL using Apache Calcite through JDBC/ODBC

SQL-like query language

APIs and other access methods

OpenCypher
RDF 1.1 / SPARQL 1.1
TinkerPop Gremlin

GeoSPARQL
GraphQL
GraphQL Federation
Java API
JDBC
RDF4J API
RDFS
RIO
Sail API
Sesame REST HTTP Protocol
SPARQL 1.1

Java API
RESTful HTTP/JSON API

Supported programming languages

C#
Go
Java
JavaScript
PHP
Python
Ruby
Scala

.Net
C#
Clojure
Java
JavaScript (Node.js)
PHP
Python
Ruby
Scala

Go
Java
JavaScript (Node.js)
PHP
Python
Ruby

Elasticsearch client

Server-side scripts

Stored procedures

well-defined plugin interfaces; JavaScript server-side extensibility

yes

Triggers

yes

by using the 'percolation' feature

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.

Multi-source replication

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Immediate Consistency, Eventual consistency (configurable in cluster mode per master or individual client request)

Eventual Consistency

Synchronous doc based replication. Get by ID may show delays up to 1 sec. Configurable write consistency: one, quorum, all

Foreign keys

Referential integrity

yes

Relationships in graphs

yes

Constraint checking

Transaction concepts

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

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

with encyption-at-rest

yes

User concepts

Access control

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

Default Basic authentication through RDF4J client, or via Java when run with cURL, default token-based in the Workbench or via Rest API, optional access through OpenID or Kerberos single sign-on.

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