DBMS > Microsoft Azure Table Storage vs. OpenEdge vs. Realm vs. Riak KV vs. SAP HANA

System Properties Comparison Microsoft Azure Table Storage vs. OpenEdge vs. Realm vs. Riak KV vs. SAP HANA

Editorial information provided by DB-Engines

Name

Description

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

Application development environment with integrated database management system

A DBMS built for use on mobile devices that’s a fast, easy to use alternative to SQLite and Core Data

Distributed, fault tolerant key-value store

In-memory, column based data store. Available as appliance or cloud service

Primary database model

with links between data sets and object tags for the creation of secondary indexes

Relational DBMS

Secondary database models

Document store
Graph DBMS

with SAP Hana, Enterprise Edition
Spatial DBMS

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

Score	4.92
Rank	#73	Overall
	#6	Wide column stores

Score	3.75
Rank	#88	Overall
	#47	Relational DBMS

Score	7.71
Rank	#52	Overall
	#9	Document stores

Score	4.44
Rank	#80	Overall
	#9	Key-value stores

Score	45.84
Rank	#22	Overall
	#16	Relational DBMS

Website

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

www.progress.com/openedge

realm.io

www.sap.com/products/hana.html

Technical documentation

documentation.progress.com/output/ua/OpenEdge_latest

realm.io/docs

www.tiot.jp/riak-docs/riak/kv/latest

help.sap.com/hana

Developer

Microsoft

Progress Software Corporation

Realm, acquired by MongoDB in May 2019

OpenSource, formerly Basho Technologies

SAP

Initial release

2012

1984

2014

2009

2010

Current release

OpenEdge 12.2, March 2020

3.2.0, December 2022

2.0 SPS07 (April 4, 2023), April 2023

License

Commercial or Open Source

commercial

Open Source

Apache version 2, commercial enterprise edition

commercial

Cloud-based only

Only available as a cloud service

yes

also available as a cloud based service

DBaaS offerings (sponsored links)

Database as a Service

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

Implementation language

Erlang

Server operating systems

hosted

AIX
HP-UX
Linux
Solaris
Windows

Android
Backend: server-less
iOS
Windows

Linux
OS X

Appliance or cloud-service

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

restricted

yes

SQL

Support of SQL

yes

close to SQL 92

yes

APIs and other access methods

RESTful HTTP API

JDBC
ODBC

HTTP API
Native Erlang Interface

JDBC
ODBC

Supported programming languages

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

Progress proprietary ABL (Advanced Business Language)

.Net
Java

with Android only
Objective-C
React Native
Swift

unofficial client library
C#
C++

unofficial client library
Clojure

unofficial client library
Dart

unofficial client library
Erlang
Go

unofficial client library
Groovy

unofficial client library
Haskell

unofficial client library
Java
JavaScript

unofficial client library
Lisp

unofficial client library
Perl

unofficial client library
PHP
Python
Ruby
Scala

unofficial client library
Smalltalk

unofficial client library

Server-side scripts

Stored procedures

yes

runs within the applications so server-side scripts are unnecessary

Erlang

SQLScript, R

Triggers

yes

Change Listeners

yes

pre-commit hooks and post-commit hooks

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

Implicit feature of the cloud service

horizontal partitioning

since Version 11.4

none

Sharding

no "single point of failure"

yes

Replication methods

Methods for redundantly storing data on multiple nodes

yes

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

Source-replica replication

none

selectable replication factor

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

links between data sets can be stored

yes

Transaction concepts

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

optimistic locking

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

In-memory capabilities

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

yes

In-Memory realm

yes

User concepts

Access control

Access rights based on private key authentication or shared access signatures

Users and groups

yes

yes, using Riak Security

yes

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