DBMS > Amazon Neptune vs. Databricks vs. OpenEdge vs. Yanza

System Properties Comparison Amazon Neptune vs. Databricks vs. OpenEdge 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

The Databricks Lakehouse Platform combines elements of data lakes and data warehouses to provide a unified view onto structured and unstructured data. It is based on Apache Spark.

Application development environment with integrated database management system

Time Series DBMS for IoT Applications

Primary database model

Graph DBMS
RDF store

Document store
Relational DBMS

Relational DBMS

Time Series 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	78.61
Rank	#15	Overall
	#2	Document stores
	#10	Relational DBMS

Score	3.51
Rank	#86	Overall
	#46	Relational DBMS

Website

aws.amazon.com/neptune

www.databricks.com

www.progress.com/openedge

yanza.com

Technical documentation

aws.amazon.com/neptune/developer-resources

docs.databricks.com

documentation.progress.com/output/ua/OpenEdge_latest

Developer

Amazon

Databricks

Progress Software Corporation

Yanza

Initial release

2017

2013

1984

2015

Current release

OpenEdge 12.2, March 2020

License

Commercial or Open Source

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.

Server operating systems

hosted

AIX
HP-UX
Linux
Solaris
Windows

Windows

Data scheme

schema-free

Flexible Schema (defined schema, partial schema, 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.

yes

Secondary indexes

yes

SQL

Support of SQL

with Databricks SQL

yes

close to SQL 92

APIs and other access methods

OpenCypher
RDF 1.1 / SPARQL 1.1
TinkerPop Gremlin

JDBC
ODBC
RESTful HTTP API

JDBC
ODBC

HTTP API

Supported programming languages

C#
Go
Java
JavaScript
PHP
Python
Ruby
Scala

Python
R
Scala

Progress proprietary ABL (Advanced Business Language)

any language that supports HTTP calls

Server-side scripts

Stored procedures

user defined functions and aggregates

yes

Triggers

yes

Timer and event based

Partitioning methods

Methods for storing different data on different nodes

none

horizontal partitioning

since Version 11.4

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

Source-replica replication

none

MapReduce

Offers an API for user-defined Map/Reduce methods

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

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.

User concepts

Access control

Access rights for users and roles can be defined via the AWS Identity and Access Management (IAM)

Users and groups

More information provided by the system vendor

Specific characteristics

Supported database models : In addition to the Document store and Relational DBMS...
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