DBMS > Amazon Neptune vs. LeanXcale vs. Microsoft Azure Table Storage vs. MySQL vs. OpenEdge

System Properties Comparison Amazon Neptune vs. LeanXcale vs. Microsoft Azure Table Storage vs. MySQL vs. OpenEdge

Editorial information provided by DB-Engines

Name

Description

Fast, reliable graph database built for the cloud

A highly scalable full ACID SQL database with fast NoSQL data ingestion and GIS capabilities

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

Widely used open source RDBMS

Application development environment with integrated database management system

Primary database model

Graph DBMS
RDF store

Key-value store
Relational DBMS

Wide column store

Relational DBMS

Key/Value like access via memcached API

Relational DBMS

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	0.35
Rank	#283	Overall
	#41	Key-value stores
	#128	Relational DBMS

Score	4.92
Rank	#73	Overall
	#6	Wide column stores

Score	1087.72
Rank	#2	Overall
	#2	Relational DBMS

Score	3.75
Rank	#88	Overall
	#47	Relational DBMS

Website

aws.amazon.com/neptune

www.leanxcale.com

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

www.mysql.com

www.progress.com/openedge

Technical documentation

aws.amazon.com/neptune/developer-resources

dev.mysql.com/doc

documentation.progress.com/output/ua/OpenEdge_latest

Developer

Amazon

LeanXcale

Microsoft

Oracle

since 2010, originally MySQL AB, then Sun

Progress Software Corporation

Initial release

2017

2015

2012

1995

1984

Current release

8.3.0, January 2024

OpenEdge 12.2, March 2020

License

Commercial or Open Source

commercial

Open Source

GPL version 2. Commercial licenses with extended functionallity are available

commercial

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

C and C++

Server operating systems

hosted

FreeBSD
Linux
OS X
Solaris
Windows

AIX
HP-UX
Linux
Solaris
Windows

Data scheme

schema-free

yes

schema-free

yes

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

yes

through Apache Derby

yes

with proprietary extensions

yes

close to SQL 92

APIs and other access methods

OpenCypher
RDF 1.1 / SPARQL 1.1
TinkerPop Gremlin

JDBC
Kafka Connector
ODBC
proprietary key/value interface
Spark Connector

RESTful HTTP API

ADO.NET
JDBC
ODBC
Proprietary native API

JDBC
ODBC

Supported programming languages

C#
Go
Java
JavaScript
PHP
Python
Ruby
Scala

C
Java
Scala

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

Ada
C
C#
C++
D
Delphi
Eiffel
Erlang
Haskell
Java
JavaScript (Node.js)
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl

Progress proprietary ABL (Advanced Business Language)

Server-side scripts

Stored procedures

yes

proprietary syntax

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

Implicit feature of the cloud service

horizontal partitioning, sharding with MySQL Cluster or MySQL Fabric

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

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

Multi-source replication
Source-replica replication

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

Foreign keys

Referential integrity

yes

Relationships in graphs

yes

not for MyISAM storage engine

yes

Transaction concepts

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

ACID

optimistic locking

ACID

not for MyISAM storage engine

ACID

Concurrency

Support for concurrent manipulation of data

yes

table locks or row locks depending on storage engine

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)

Access rights based on private key authentication or shared access signatures

Users with fine-grained authorization concept

no user groups or roles

Users and groups

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