DBMS > Adabas vs. AlaSQL vs. Lovefield vs. Spark SQL

System Properties Comparison Adabas vs. AlaSQL vs. Lovefield vs. Spark SQL

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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

Embeddable relational database for web apps written in pure JavaScript

Spark SQL is a component on top of 'Spark Core' for structured data processing

Primary database model

Multivalue DBMS

Document store
Relational DBMS

Relational DBMS

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

Score	2.79
Rank	#102	Overall
	#2	Multivalue DBMS

Score	0.51
Rank	#256	Overall
	#40	Document stores
	#118	Relational DBMS

Score	0.33
Rank	#286	Overall
	#131	Relational DBMS

Score	18.04
Rank	#33	Overall
	#20	Relational DBMS

Website

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

alasql.org

google.github.io/lovefield

spark.apache.org/sql

Technical documentation

github.com/AlaSQL/alasql

github.com/google/lovefield/blob/master/docs/spec_index.md

spark.apache.org/docs/latest/sql-programming-guide.html

Developer

Software AG

Andrey Gershun & Mathias R. Wulff

Google

Apache Software Foundation

Initial release

1971

2014

Current release

2.1.12, February 2017

3.5.0 ( 2.13), September 2023

License

Commercial or Open Source

commercial

Open Source

MIT-License

Open Source

Apache 2.0

Open Source

Apache 2.0

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

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

Implementation language

JavaScript

Scala

Server operating systems

BS2000
Linux
Unix
Windows
z/OS
z/VSE

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

tested with Chrome, Firefox, IE, Safari

Linux
OS X
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.

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.

SQL-like query language

via JavaScript builder pattern

SQL-like DML and DDL statements

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

Supported programming languages

Natural

JavaScript

Java
Python
R
Scala

Server-side scripts

Stored procedures

in Natural

Triggers

yes

Using read-only observers

Partitioning methods

Methods for storing different data on different nodes

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

none

yes, utilizing Spark Core

Replication methods

Methods for redundantly storing data on multiple nodes

yes, with add-on product Event Replicator

none

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

none

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

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, by using IndexedDB or the cloud service Firebase Realtime Database

yes

In-memory capabilities

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

yes

using MemoryDB

User concepts

Access control

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

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