DBMS > Amazon Neptune vs. Datomic vs. Microsoft Azure Cosmos DB vs. OpenEdge vs. Yanza

System Properties Comparison Amazon Neptune vs. Datomic vs. Microsoft Azure Cosmos DB vs. OpenEdge vs. Yanza

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

Datomic builds on immutable values, supports point-in-time queries and uses 3rd party systems for durability

Globally distributed, horizontally scalable, multi-model database service

Application development environment with integrated database management system

Time Series DBMS for IoT Applications

Primary database model

Graph DBMS
RDF store

Relational DBMS

Document store
Graph DBMS
Key-value store
Wide column store

Relational DBMS

Time Series DBMS

Secondary database models

Spatial 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	1.66
Rank	#144	Overall
	#66	Relational DBMS

Score	27.71
Rank	#27	Overall
	#4	Document stores
	#2	Graph DBMS
	#3	Key-value stores
	#3	Wide column stores

Score	3.45
Rank	#85	Overall
	#46	Relational DBMS

Website

aws.amazon.com/neptune

www.datomic.com

azure.microsoft.com/services/cosmos-db

www.progress.com/openedge

yanza.com

Technical documentation

aws.amazon.com/neptune/developer-resources

docs.datomic.com

learn.microsoft.com/azure/cosmos-db

documentation.progress.com/output/ua/OpenEdge_latest

Developer

Amazon

Cognitect

Microsoft

Progress Software Corporation

Yanza

Initial release

2017

2012

2014

1984

2015

Current release

1.0.7075, December 2023

OpenEdge 12.2, March 2020

License

Commercial or Open Source

commercial

limited edition free

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

Java, Clojure

Server operating systems

hosted

All OS with a Java VM

hosted

AIX
HP-UX
Linux
Solaris
Windows

Windows

Data scheme

schema-free

yes

schema-free

yes

schema-free

Typing

predefined data types such as float or date

yes

JSON types

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

All properties auto-indexed by default

yes

SQL

Support of SQL

SQL-like query language

yes

close to SQL 92

APIs and other access methods

OpenCypher
RDF 1.1 / SPARQL 1.1
TinkerPop Gremlin

RESTful HTTP API

DocumentDB API
Graph API (Gremlin)
MongoDB API
RESTful HTTP API
Table API

JDBC
ODBC

HTTP API

Supported programming languages

C#
Go
Java
JavaScript
PHP
Python
Ruby
Scala

Clojure
Java

.Net
C#
Java
JavaScript
JavaScript (Node.js)
MongoDB client drivers written for various programming languages
Python

Progress proprietary ABL (Advanced Business Language)

any language that supports HTTP calls

Server-side scripts

Stored procedures

yes

Transaction Functions

JavaScript

yes

Triggers

By using transaction functions

JavaScript

yes

Timer and event based

Partitioning methods

Methods for storing different data on different nodes

none

But extensive use of caching in the application peers

Sharding

Implicit feature of the cloud service

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.

none

But extensive use of caching in the application peers

yes

Implicit feature of the cloud service

Source-replica replication

none

MapReduce

Offers an API for user-defined Map/Reduce methods

with Hadoop integration

Integration with Hadoop/HDInsight on Azure*

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Bounded Staleness
Consistent Prefix
Eventual Consistency
Immediate Consistency

Consistency level configurable on request level
Session Consistency

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

Multi-item ACID transactions with snapshot isolation within a partition

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

with encyption-at-rest

yes

using external storage systems (e.g. Cassandra, DynamoDB, PostgreSQL, Couchbase and others)

yes

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

yes

recommended only for testing and development

User concepts

Access control

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

Access rights can be defined down to the item level

Users and groups

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.