DBMS > Adabas vs. AlaSQL vs. Google BigQuery vs. IBM Db2 warehouse vs. Sadas Engine

System Properties Comparison Adabas vs. AlaSQL vs. Google BigQuery vs. IBM Db2 warehouse vs. Sadas Engine

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 with append-only tables

Cloud-based data warehousing service

SADAS Engine is a columnar DBMS specifically designed for high performance in data warehouse environments

Primary database model

Multivalue DBMS

Document store
Relational DBMS

Relational DBMS

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	60.38
Rank	#19	Overall
	#13	Relational DBMS

Score	1.30
Rank	#164	Overall
	#75	Relational DBMS

Score	0.00
Rank	#383	Overall
	#158	Relational DBMS

Website

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

alasql.org

cloud.google.com/bigquery

www.ibm.com/products/db2/warehouse

www.sadasengine.com

Technical documentation

github.com/AlaSQL/alasql

cloud.google.com/bigquery/docs

www.sadasengine.com/en/sadas-engine-download-free-trial-and-documentation/#documentation

Developer

Software AG

Andrey Gershun & Mathias R. Wulff

Google

IBM

SADAS s.r.l.

Initial release

1971

2014

2010

2014

2006

Current release

8.0

License

Commercial or Open Source

commercial

Open Source

MIT-License

commercial

free trial version available

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

C++

Server operating systems

BS2000
Linux
Unix
Windows
z/OS
z/VSE

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

hosted

AIX
Linux
Windows

Data scheme

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.

Import/export of XML data possible

Secondary indexes

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

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

RESTful HTTP/JSON API

.NET Client API
JDBC
ODBC
OLE DB

JDBC
ODBC
Proprietary protocol

Supported programming languages

Natural

JavaScript

.Net
Java
JavaScript
Objective-C
PHP
Python
Ruby

Java
JavaScript (Node.js)
Perl
PHP
Python
R
Ruby

.Net
C
C#
C++
Groovy
Java
PHP
Python

Server-side scripts

Stored procedures

in Natural

user defined functions

in JavaScript

PL/SQL, SQL PL

Triggers

yes

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

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

yes, with add-on product Event Replicator

none

yes

none

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

none

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

yes

only for local storage and DOM-storage

Since BigQuery is designed for querying data

ACID

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

managed by 'Learn by Usage'

User concepts

Access control

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

Access privileges (owner, writer, reader) on dataset, table or view level

Google Cloud Identity & Access Management (IAM)

fine grained access rights according to SQL-standard

Access rights for users, groups and roles according to SQL-standard

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