DBMS > Adabas vs. HEAVY.AI vs. Lovefield vs. SAP HANA vs. Tkrzw

System Properties Comparison Adabas vs. HEAVY.AI vs. Lovefield vs. SAP HANA vs. Tkrzw

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

Embeddable relational database for web apps written in pure JavaScript

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

A concept of libraries, allowing an application program to store and query key-value pairs in a file. Successor of Tokyo Cabinet and Kyoto Cabinet

Primary database model

Multivalue DBMS

Relational DBMS

Key-value store

Secondary database models

Spatial DBMS

Document store
Graph DBMS

with SAP Hana, Enterprise Edition
Spatial DBMS

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

Score	2.64
Rank	#104	Overall
	#1	Multivalue DBMS

Score	1.41
Rank	#153	Overall
	#71	Relational DBMS

Score	0.22
Rank	#306	Overall
	#138	Relational DBMS

Score	41.32
Rank	#23	Overall
	#16	Relational DBMS

Score	0.00
Rank	#385	Overall
	#61	Key-value stores

Website

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

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

google.github.io/lovefield

www.sap.com/products/hana.html

dbmx.net/tkrzw

Technical documentation

docs.heavy.ai

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

help.sap.com/hana

Developer

Software AG

HEAVY.AI, Inc.

Google

SAP

Mikio Hirabayashi

Initial release

1971

2016

2014

2010

2020

Current release

5.10, January 2022

2.1.12, February 2017

2.0 SPS07 (April 4, 2023), April 2023

0.9.3, August 2020

License

Commercial or Open Source

commercial

Open Source

Apache Version 2; enterprise edition available

Open Source

Apache 2.0

commercial

Open Source

Apache Version 2.0

Cloud-based only

Only available as a cloud service

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

C++ and CUDA

JavaScript

C++

Server operating systems

BS2000
Linux
Unix
Windows
z/OS
z/VSE

Linux

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

tested with Chrome, Firefox, IE, Safari

Appliance or cloud-service

Linux
macOS

Data scheme

yes

schema-free

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

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

JDBC
ODBC
Thrift
Vega

JDBC
ODBC

Supported programming languages

Natural

All languages supporting JDBC/ODBC/Thrift
Python

JavaScript

C++
Java
Python
Ruby

Server-side scripts

Stored procedures

in Natural

SQLScript, R

Triggers

Using read-only observers

yes

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

yes

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes, with add-on product Event Replicator

Multi-source replication

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

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

yes

In-memory capabilities

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

yes

using MemoryDB

yes

using specific database classes

User concepts

Access control

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

fine grained access rights according to SQL-standard

yes

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