DBMS > Adabas vs. HEAVY.AI vs. Linter vs. Lovefield

System Properties Comparison Adabas vs. HEAVY.AI vs. Linter vs. Lovefield

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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

A high performance, column-oriented RDBMS, specifically developed to harness the massive parallelism of modern CPU and GPU hardware

RDBMS for high security requirements

Embeddable relational database for web apps written in pure JavaScript

Primary database model

Multivalue DBMS

Relational DBMS

Secondary database models

Spatial DBMS

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

Score	3.58
Rank	#91	Overall
	#1	Multivalue DBMS

Score	2.10
Rank	#126	Overall
	#61	Relational DBMS

Score	0.10
Rank	#350	Overall
	#153	Relational DBMS

Score	0.32
Rank	#290	Overall
	#132	Relational DBMS

Website

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

github.com/heavyai/heavydb
www.heavy.ai

linter.ru

google.github.io/lovefield

Technical documentation

docs.heavy.ai

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

Developer

Software AG

HEAVY.AI, Inc.

relex.ru

Google

Initial release

1971

2016

1990

2014

Current release

5.10, January 2022

2.1.12, February 2017

License

Commercial or Open Source

commercial

Open Source

Apache Version 2; enterprise edition available

commercial

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

C++ and CUDA

C and C++

JavaScript

Server operating systems

BS2000
Linux
Unix
Windows
z/OS
z/VSE

Linux

AIX
Android
BSD
HP Open VMS
iOS
Linux
OS X
VxWorks
Windows

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

tested with Chrome, Firefox, IE, Safari

Data scheme

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

yes

SQL-like query language

via JavaScript builder pattern

APIs and other access methods

HTTP API

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

with add-on software Adabas SOA Gateway

JDBC
ODBC
Thrift
Vega

ADO.NET
JDBC
LINQ
ODBC
OLE DB
Oracle Call Interface (OCI)

Supported programming languages

Natural

All languages supporting JDBC/ODBC/Thrift
Python

C
C#
C++
Java
Perl
PHP
Python
Qt
Ruby
Tcl

JavaScript

Server-side scripts

Stored procedures

in Natural

yes

proprietary syntax with the possibility to convert from PL/SQL

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

Sharding

Round robin

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes, with add-on product Event Replicator

Multi-source replication

Source-replica replication

none

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

Transaction concepts

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

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

yes, by using IndexedDB or the cloud service Firebase Realtime Database

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)

fine grained access rights according to SQL-standard

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