DBMS > Amazon Neptune vs. HugeGraph vs. SAP HANA vs. SWC-DB

System Properties Comparison Amazon Neptune vs. HugeGraph vs. SAP HANA vs. SWC-DB

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Editorial information provided by DB-Engines

Name

Description

Fast, reliable graph database built for the cloud

A fast-speed and highly-scalable Graph DBMS

In-memory, column based data store. Available as appliance or cloud service

A high performance, scalable Wide Column DBMS

Primary database model

Secondary database models

Document store
Graph DBMS

with SAP Hana, Enterprise Edition
Spatial DBMS

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	0.17
Rank	#335	Overall
	#31	Graph DBMS

Score	44.27
Rank	#23	Overall
	#16	Relational DBMS

Score	0.08
Rank	#364	Overall
	#13	Wide column stores

Website

aws.amazon.com/neptune

github.com/hugegraph
hugegraph.apache.org

www.sap.com/products/hana.html

github.com/kashirin-alex/swc-db
www.swcdb.org

Technical documentation

aws.amazon.com/neptune/developer-resources

hugegraph.apache.org/docs

help.sap.com/hana

Developer

Amazon

Baidu

SAP

Alex Kashirin

Initial release

2017

2018

2010

2020

Current release

0.9

2.0 SPS07 (April 4, 2023), April 2023

0.5, April 2021

License

Commercial or Open Source

commercial

Open Source

Apache Version 2.0

commercial

Open Source

GPL V3

Cloud-based only

Only available as a cloud service

yes

also available as a cloud based service

DBaaS offerings (sponsored links)

Database as a Service

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

Implementation language

Java

C++

Server operating systems

hosted

Linux
macOS
Unix

Appliance or cloud-service

Linux

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

also supports composite index and range index

yes

SQL

Support of SQL

yes

SQL-like query language

APIs and other access methods

OpenCypher
RDF 1.1 / SPARQL 1.1
TinkerPop Gremlin

Java API
RESTful HTTP API
TinkerPop Gremlin

JDBC
ODBC

Proprietary protocol
Thrift

Supported programming languages

C#
Go
Java
JavaScript
PHP
Python
Ruby
Scala

Groovy
Java
Python

C++

Server-side scripts

Stored procedures

asynchronous Gremlin script jobs

SQLScript, R

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

none

yes

depending on used storage backend, e.g. Cassandra and HBase

yes

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.

yes

depending on used storage backend, e.g. Cassandra and HBase

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

via hugegraph-spark

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

Relationships in graphs

yes

edges in graph

yes

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

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)

Users, roles and permissions

yes

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