DBMS > Adabas vs. AlaSQL vs. Amazon Redshift vs. Google Cloud Datastore vs. Microsoft Azure Table Storage

System Properties Comparison Adabas vs. AlaSQL vs. Amazon Redshift vs. Google Cloud Datastore vs. Microsoft Azure Table Storage

Editorial information provided by DB-Engines

Name

Description

OLTP - DBMS for mainframes and Linux/Unix/Windows environments

used typically together with the Natural programming platform

JavaScript DBMS library

Large scale data warehouse service for use with business intelligence tools

Automatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud Platform

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

Primary database model

Multivalue DBMS

Document store
Relational DBMS

Relational DBMS

Document store

Wide column store

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

Score	3.17
Rank	#94	Overall
	#1	Multivalue DBMS

Score	0.46
Rank	#260	Overall
	#40	Document stores
	#121	Relational DBMS

Score	17.94
Rank	#34	Overall
	#21	Relational DBMS

Score	4.47
Rank	#76	Overall
	#12	Document stores

Score	4.48
Rank	#75	Overall
	#6	Wide column stores

Website

www.softwareag.com/en_corporate/platform/adabas-natural.html

alasql.org

aws.amazon.com/redshift

cloud.google.com/datastore

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

Technical documentation

github.com/AlaSQL/alasql

docs.aws.amazon.com/redshift

cloud.google.com/datastore/docs

Developer

Software AG

Andrey Gershun & Mathias R. Wulff

Amazon (based on PostgreSQL)

Google

Microsoft

Initial release

1971

2014

2012

2008

2012

License

Commercial or Open Source

commercial

Open Source

MIT-License

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

JavaScript

Server operating systems

BS2000
Linux
Unix
Windows
z/OS
z/VSE

server-less, requires a JavaScript environment (browser, Node.js)

hosted

Data scheme

yes

schema-free

yes

schema-free

Typing

predefined data types such as float or date

yes

yes, details here

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.

Secondary indexes

yes

restricted

yes

SQL

Support of SQL

yes

with add-on product Adabas SQL Gateway

Close to SQL99, but no user access control, stored procedures and host language bindings.

yes

does not fully support an SQL-standard

SQL-like query language (GQL)

APIs and other access methods

HTTP API

with add-on software Adabas SOA Gateway
SOAP-based API

with add-on software Adabas SOA Gateway

JavaScript API

JDBC
ODBC

gRPC (using protocol buffers) API
RESTful HTTP/JSON API

RESTful HTTP API

Supported programming languages

Natural

JavaScript

All languages supporting JDBC/ODBC

.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby

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

Server-side scripts

Stored procedures

in Natural

user defined functions

in Python

using Google App Engine

Triggers

yes

Callbacks using the Google Apps Engine

Partitioning methods

Methods for storing different data on different nodes

yes, with additonal products like Adabas Cluster Services, Adabas Parallel Services, Adabas Vista

none

Sharding

Implicit feature of the cloud service

Replication methods

Methods for redundantly storing data on multiple nodes

yes, with add-on product Event Replicator

none

yes

Multi-source replication using Paxos

yes

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

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

using Google Cloud Dataflow

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

none

Immediate Consistency

Immediate Consistency or Eventual Consistency depending on type of query and configuration

Strong Consistency is default for entity lookups and queries within an Entity Group (but can instead be made eventually consistent). Other queries are always eventual consistent.

Immediate Consistency

Foreign keys

Referential integrity

yes

informational only, not enforced by the system

yes

via ReferenceProperties or Ancestor paths

Transaction concepts

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

ACID

yes

only for local storage and DOM-storage

ACID

Serializable Isolation within Transactions, Read Committed outside of Transactions

optimistic locking

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

by using IndexedDB, SQL.JS or proprietary FileStorage

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

only with OS-specific tools (e.g. IBM RACF, CA Top Secret)

fine grained access rights according to SQL-standard

Access rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)

Access rights based on private key authentication or shared access signatures

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