DBMS > Amazon Neptune vs. Microsoft Azure Table Storage vs. OpenEdge vs. Postgres-XL vs. SiteWhere

System Properties Comparison Amazon Neptune vs. Microsoft Azure Table Storage vs. OpenEdge vs. Postgres-XL vs. SiteWhere

Editorial information provided by DB-Engines

Name

Description

Fast, reliable graph database built for the cloud

A Wide Column Store for rapid development using massive semi-structured datasets

Application development environment with integrated database management system

Based on PostgreSQL enhanced with MPP and write-scale-out cluster features

M2M integration platform for persisting/querying time series data

Primary database model

Secondary database models

Document store
Spatial DBMS

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

Score	2.58
Rank	#112	Overall
	#9	Graph DBMS
	#5	RDF stores

Score	4.92
Rank	#73	Overall
	#6	Wide column stores

Score	3.75
Rank	#88	Overall
	#47	Relational DBMS

Score	0.52
Rank	#256	Overall
	#117	Relational DBMS

Score	0.06
Rank	#367	Overall
	#36	Time Series DBMS

Website

aws.amazon.com/neptune

azure.microsoft.com/en-us/services/storage/tables

www.progress.com/openedge

www.postgres-xl.org

github.com/sitewhere/sitewhere

Technical documentation

aws.amazon.com/neptune/developer-resources

documentation.progress.com/output/ua/OpenEdge_latest

www.postgres-xl.org/documentation

sitewhere1.sitewhere.io/index.html

Developer

Amazon

Microsoft

Progress Software Corporation

SiteWhere

Initial release

2017

2012

1984

2014

since 2012, originally named StormDB

2010

Current release

OpenEdge 12.2, March 2020

10 R1, October 2018

License

Commercial or Open Source

commercial

Open Source

Mozilla public license

Open Source

Common Public Attribution License Version 1.0

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

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

Implementation language

Java

Server operating systems

hosted

AIX
HP-UX
Linux
Solaris
Windows

Linux
macOS

Linux
OS X
Windows

Data scheme

schema-free

yes

predefined scheme

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

XML type, but no XML query functionality

Secondary indexes

yes

SQL

Support of SQL

yes

close to SQL 92

yes

distributed, parallel query execution

APIs and other access methods

OpenCypher
RDF 1.1 / SPARQL 1.1
TinkerPop Gremlin

RESTful HTTP API

JDBC
ODBC

ADO.NET
JDBC
native C library
ODBC
streaming API for large objects

HTTP REST

Supported programming languages

C#
Go
Java
JavaScript
PHP
Python
Ruby
Scala

.Net
C#
C++
Java
JavaScript (Node.js)
PHP
Python
Ruby

Progress proprietary ABL (Advanced Business Language)

.Net
C
C++
Delphi
Erlang
Java
JavaScript (Node.js)
Perl
PHP
Python
Tcl

Server-side scripts

Stored procedures

yes

user defined functions

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

Implicit feature of the cloud service

horizontal partitioning

since Version 11.4

horizontal partitioning

Sharding

based on HBase

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

implicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.

Source-replica replication

selectable replication factor

based on HBase

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

optimistic locking

ACID

MVCC

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)

Access rights based on private key authentication or shared access signatures

Users and groups

fine grained access rights according to SQL-standard

Users with fine-grained authorization concept

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