DBMS > Amazon Neptune vs. Hazelcast vs. Postgres-XL

System Properties Comparison Amazon Neptune vs. Hazelcast vs. Postgres-XL

Please select another system to include it in the comparison.

Editorial information provided by DB-Engines

Name

Description

Fast, reliable graph database built for the cloud

A widely adopted in-memory data grid

Based on PostgreSQL enhanced with MPP and write-scale-out cluster features

Primary database model

Graph DBMS
RDF store

Key-value store

Relational DBMS

Secondary database models

Document store

JSON support with IMDG 3.12

Document store
Spatial DBMS

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

Score	2.20
Rank	#119	Overall
	#9	Graph DBMS
	#5	RDF stores

Score	5.97
Rank	#57	Overall
	#6	Key-value stores

Score	0.49
Rank	#256	Overall
	#117	Relational DBMS

Website

aws.amazon.com/neptune

hazelcast.com

www.postgres-xl.org

Technical documentation

aws.amazon.com/neptune/developer-resources

hazelcast.org/imdg/docs

www.postgres-xl.org/documentation

Developer

Amazon

Hazelcast

Initial release

2017

2008

2014

since 2012, originally named StormDB

Current release

5.3.6, November 2023

10 R1, October 2018

License

Commercial or Open Source

commercial

Open Source

Apache Version 2; commercial licenses available

Open Source

Mozilla public license

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

All OS with a Java VM

Linux
macOS

Data scheme

schema-free

yes

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.

yes

the object must implement a serialization strategy

yes

XML type, but no XML query functionality

Secondary indexes

yes

SQL

Support of SQL

SQL-like query language

yes

distributed, parallel query execution

APIs and other access methods

OpenCypher
RDF 1.1 / SPARQL 1.1
TinkerPop Gremlin

JCache
JPA
Memcached protocol
RESTful HTTP API

ADO.NET
JDBC
native C library
ODBC
streaming API for large objects

Supported programming languages

C#
Go
Java
JavaScript
PHP
Python
Ruby
Scala

.Net
C#
C++
Clojure
Go
Java
JavaScript (Node.js)
Python
Scala

.Net
C
C++
Delphi
Erlang
Java
JavaScript (Node.js)
Perl
PHP
Python
Tcl

Server-side scripts

Stored procedures

yes

Event Listeners, Executor Services

user defined functions

Triggers

yes

Events

yes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

horizontal partitioning

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.

yes

Replicated Map

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Immediate Consistency or Eventual Consistency selectable by user

Raft Consensus Algorithm

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

one or two-phase-commit; repeatable reads; read commited

ACID

MVCC

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)

Role-based access control

fine grained access rights according to SQL-standard

More information provided by the system vendor

We invite representatives of system vendors to contact us for updating and extending the system information,
and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

Related products and services

We invite representatives of vendors of related products to contact us for presenting information about their offerings here.

More resources

Recent citations in the news

Find and link similar entities in a knowledge graph using Amazon Neptune, Part 1: Full-text search | Amazon Web ...
7 May 2024, AWS Blog

Find and link similar entities in a knowledge graph using Amazon Neptune, Part 2: Vector similarity search | Amazon ...
7 May 2024, AWS Blog

AWS announces Amazon Neptune I/O-Optimized
22 February 2024, AWS Blog

Analyze large amounts of graph data to get insights and find trends with Amazon Neptune Analytics | Amazon Web ...
29 November 2023, AWS Blog

Amazon Neptune Analytics is now generally available
29 November 2023, AWS Blog

provided by Google News

Hazelcast Weaves Wider Logic Threads Through The Data Fabric
7 March 2024, Forbes

Hazelcast 5.4 real time data processing platform boosts AI and consistency
17 April 2024, VentureBeat

Hazelcast Achieves Record Year with Leading Brands Choosing Its Platform for Application Modernization, AI Initiatives
22 February 2024, Datanami

Real-Time Data Platform Hazelcast Introduces New Chief Technology Officer Adrian Soars
7 November 2023, Finovate

Hazelcast Versus Redis: A Practical Comparison
4 January 2024, Database Trends and Applications

provided by Google News

Share this page