DBMS > Amazon Neptune vs. Graph Engine vs. Heroic vs. Yanza

System Properties Comparison Amazon Neptune vs. Graph Engine vs. Heroic vs. Yanza

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Editorial information provided by DB-Engines

Name

Yanza seems to be discontinued. Therefore it is excluded from the DB-Engines Ranking.

Description

Fast, reliable graph database built for the cloud

A distributed in-memory data processing engine, underpinned by a strongly-typed RAM store and a general distributed computation engine

Time Series DBMS built at Spotify based on Cassandra or Google Cloud Bigtable, and ElasticSearch

Time Series DBMS for IoT Applications

Primary database model

Graph DBMS
RDF store

Graph DBMS
Key-value store

Time Series DBMS

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

Score	2.29
Rank	#113	Overall
	#9	Graph DBMS
	#5	RDF stores

Score	0.67
Rank	#232	Overall
	#21	Graph DBMS
	#34	Key-value stores

Score	0.46
Rank	#265	Overall
	#22	Time Series DBMS

Website

aws.amazon.com/neptune

www.graphengine.io

github.com/spotify/heroic

yanza.com

Technical documentation

aws.amazon.com/neptune/developer-resources

www.graphengine.io/docs/manual

spotify.github.io/heroic

Developer

Amazon

Microsoft

Spotify

Yanza

Initial release

2017

2010

2014

2015

License

Commercial or Open Source

commercial

Open Source

MIT License

Open Source

Apache 2.0

commercial

free version available

Cloud-based only

Only available as a cloud service

yes

but mainly used as a service provided by Yanza

DBaaS offerings (sponsored links)

Database as a Service

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

Implementation language

.NET and C

Java

Server operating systems

hosted

.NET

Windows

Data scheme

schema-free

yes

schema-free

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

via Elasticsearch

SQL

Support of SQL

APIs and other access methods

OpenCypher
RDF 1.1 / SPARQL 1.1
TinkerPop Gremlin

RESTful HTTP API

HQL (Heroic Query Language, a JSON-based language)
HTTP API

HTTP API

Supported programming languages

C#
Go
Java
JavaScript
PHP
Python
Ruby
Scala

C#
C++
F#
Visual Basic

any language that supports HTTP calls

Server-side scripts

Stored procedures

yes

Triggers

yes

Timer and event based

Partitioning methods

Methods for storing different data on different nodes

none

horizontal partitioning

Sharding

none

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

none

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency
Immediate Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

Relationships in graphs

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

optional: either by committing a write-ahead log (WAL) to the local persistent storage or by dumping the memory to a persistent storage

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)

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