DBMS > Amazon Neptune vs. EsgynDB vs. ITTIA vs. Trafodion vs. Yanza

System Properties Comparison Amazon Neptune vs. EsgynDB vs. ITTIA vs. Trafodion vs. Yanza

Editorial information provided by DB-Engines

Name

Apache Trafodion has been retired in 2021. Therefore it is excluded from the DB-Engines Ranking.

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

Description

Fast, reliable graph database built for the cloud

Enterprise-class SQL-on-Hadoop solution, powered by Apache Trafodion

Edge Time Series DBMS with Real-Time Stream Processing

Transactional SQL-on-Hadoop DBMS

Time Series DBMS for IoT Applications

Primary database model

Secondary database models

Relational 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	0.25
Rank	#312	Overall
	#138	Relational DBMS

Score	0.44
Rank	#267	Overall
	#23	Time Series DBMS

Website

aws.amazon.com/neptune

www.esgyn.cn

www.ittia.com

trafodion.apache.org

yanza.com

Technical documentation

aws.amazon.com/neptune/developer-resources

trafodion.apache.org/documentation.html

Developer

Amazon

Esgyn

ITTIA L.L.C.

Apache Software Foundation, originally developed by HP

Yanza

Initial release

2017

2015

2007

2014

2015

Current release

8.7

2.3.0, February 2019

License

Commercial or Open Source

commercial

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

C++, Java

C and C++

C++, Java

Server operating systems

hosted

Linux

Linux
Windows

Linux

Windows

Data scheme

schema-free

yes

Fixed schema

yes

schema-free

Typing

predefined data types such as float or date

yes

Float/Blob/Integer/String/Unicode/Date/Time/Timestamp/Interval

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

SQL

Support of SQL

yes

APIs and other access methods

OpenCypher
RDF 1.1 / SPARQL 1.1
TinkerPop Gremlin

ADO.NET
JDBC
ODBC

JDBC
ODBC
RESTful HTTP API
WebSocket

ADO.NET
JDBC
ODBC

HTTP API

Supported programming languages

C#
Go
Java
JavaScript
PHP
Python
Ruby
Scala

All languages supporting JDBC/ODBC/ADO.Net

C
C++
JavaScript (Node.js)
Python

All languages supporting JDBC/ODBC/ADO.Net

any language that supports HTTP calls

Server-side scripts

Stored procedures

Java Stored Procedures

yes

Java Stored Procedures

Triggers

yes

Timer and event based

Partitioning methods

Methods for storing different data on different nodes

none

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.

Multi-source replication between multi datacenters

yes

yes, via HBase

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

via user defined functions and HBase

Consistency concepts

Methods to ensure consistency in a distributed system

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

yes

ACID

Concurrency

Support for concurrent manipulation of data

yes

yes, multi-version concurrency control (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

Database file passwords

fine grained access rights according to SQL-standard

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