DBMS > Amazon Neptune vs. Amazon Redshift vs. InfinityDB vs. Microsoft Azure Table Storage vs. OpenEdge

System Properties Comparison Amazon Neptune vs. Amazon Redshift vs. InfinityDB vs. Microsoft Azure Table Storage vs. OpenEdge

Editorial information provided by DB-Engines

Name

Description

Fast, reliable graph database built for the cloud

Large scale data warehouse service for use with business intelligence tools

A Java embedded Key-Value Store which extends the Java Map interface

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

Application development environment with integrated database management system

Primary database model

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	19.03
Rank	#34	Overall
	#21	Relational DBMS

Score	0.07
Rank	#359	Overall
	#54	Key-value stores

Score	4.92
Rank	#73	Overall
	#6	Wide column stores

Score	3.75
Rank	#88	Overall
	#47	Relational DBMS

Website

aws.amazon.com/neptune

aws.amazon.com/redshift

boilerbay.com

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

www.progress.com/openedge

Technical documentation

aws.amazon.com/neptune/developer-resources

docs.aws.amazon.com/redshift

boilerbay.com/infinitydb/manual

documentation.progress.com/output/ua/OpenEdge_latest

Developer

Amazon

Amazon (based on PostgreSQL)

Boiler Bay Inc.

Microsoft

Progress Software Corporation

Initial release

2017

2012

2002

2012

1984

Current release

4.0

OpenEdge 12.2, March 2020

License

Commercial or Open Source

commercial

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

All OS with a Java VM

hosted

AIX
HP-UX
Linux
Solaris
Windows

Data scheme

schema-free

yes

nested virtual Java Maps, multi-value, logical â€˜tuple spaceâ€™ runtime Schema upgrade

schema-free

yes

Typing

predefined data types such as float or date

yes

all Java primitives, Date, CLOB, BLOB, huge sparse arrays

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

restricted

manual creation possible, using inversions based on multi-value capability

yes

SQL

Support of SQL

yes

does not fully support an SQL-standard

yes

close to SQL 92

APIs and other access methods

OpenCypher
RDF 1.1 / SPARQL 1.1
TinkerPop Gremlin

JDBC
ODBC

Access via java.util.concurrent.ConcurrentNavigableMap Interface
Proprietary API to InfinityDB ItemSpace (boilerbay.com/docs/ItemSpaceDataStructures.htm)

RESTful HTTP API

JDBC
ODBC

Supported programming languages

C#
Go
Java
JavaScript
PHP
Python
Ruby
Scala

All languages supporting JDBC/ODBC

Java

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

Progress proprietary ABL (Advanced Business Language)

Server-side scripts

Stored procedures

user defined functions

in Python

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

none

Sharding

Implicit feature of the cloud service

horizontal partitioning

since Version 11.4

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

none

yes

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

Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

READ-COMMITTED or SERIALIZED

Immediate Consistency

Foreign keys

Referential integrity

yes

Relationships in graphs

yes

informational only, not enforced by the system

manual creation possible, using inversions based on multi-value capability

yes

Transaction concepts

Support to ensure data integrity after non-atomic manipulations of data

ACID

Optimistic locking for transactions; no isolation for bulk loads

optimistic locking

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)

fine grained access rights according to SQL-standard

Access rights based on private key authentication or shared access signatures

Users and groups

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