DBMS > Amazon Neptune vs. Hawkular Metrics vs. Ingres vs. LeanXcale

System Properties Comparison Amazon Neptune vs. Hawkular Metrics vs. Ingres vs. LeanXcale

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

Hawkular metrics is the metric storage of the Red Hat sponsored Hawkular monitoring system. It is based on Cassandra.

Well established RDBMS

A highly scalable full ACID SQL database with fast NoSQL data ingestion and GIS capabilities

Primary database model

Graph DBMS
RDF store

Time Series DBMS

Relational DBMS

Key-value store
Relational 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	0.01
Rank	#377	Overall
	#39	Time Series DBMS

Score	3.63
Rank	#79	Overall
	#43	Relational DBMS

Score	0.28
Rank	#286	Overall
	#41	Key-value stores
	#130	Relational DBMS

Website

aws.amazon.com/neptune

www.hawkular.org

www.actian.com/databases/ingres

www.leanxcale.com

Technical documentation

aws.amazon.com/neptune/developer-resources

www.hawkular.org/hawkular-metrics/docs/user-guide

docs.actian.com/ingres

Developer

Amazon

Community supported by Red Hat

Actian Corporation

LeanXcale

Initial release

2017

2014

1974

originally developed at University Berkely in early 1970s

2015

Current release

12.0, July 2024

License

Commercial or Open Source

commercial

Open Source

Apache 2.0

commercial

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
OS X
Windows

AIX
HP Open VMS
HP-UX
Linux
Solaris
Windows

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.

but tools for importing/exporting data from/to XML-files available

Secondary indexes

yes

SQL

Support of SQL

yes

through Apache Derby

APIs and other access methods

OpenCypher
RDF 1.1 / SPARQL 1.1
TinkerPop Gremlin

HTTP REST

.NET Client API
JDBC
ODBC
proprietary protocol (OpenAPI)

JDBC
Kafka Connector
ODBC
proprietary key/value interface
Spark Connector

Supported programming languages

C#
Go
Java
JavaScript
PHP
Python
Ruby
Scala

Go
Java
Python
Ruby

C
Java
Scala

Server-side scripts

Stored procedures

yes

Triggers

yes

via Hawkular Alerting

yes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

based on Cassandra

horizontal partitioning

Ingres Star to access multiple databases simultaneously

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.

selectable replication factor

based on Cassandra

Ingres Replicator

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

based on Cassandra
Immediate Consistency

based on Cassandra

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

Concurrency

Support for concurrent manipulation of data

yes

MVCC

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

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

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

Amazon Neptune Analytics now supports openCypher queries over RDF Graphs
13 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

Waiting for Red Hat OpenShift 4.0? Too late, 4.1 has already arrived…
5 June 2019, DevClass

provided by Google News

Actian Launches Ingres 12.0 Database
4 June 2024, PR Newswire

New startup from Postgres creator puts the database at heart of software stack
12 March 2024, TechCrunch

Postgres pioneer Michael Stonebraker promises to upend the database once more
26 December 2023, The Register

Actian Launches Ingres as a Fully-Managed Cloud Service
24 September 2021, Integration Developers

Actian Avalanche Real-Time Connected Data Warehouse adds integration
28 April 2020, TechTarget

provided by Google News

Share this page