DBMS > Adabas vs. Bangdb vs. Google Cloud Firestore vs. HyperSQL vs. Lovefield

System Properties Comparison Adabas vs. Bangdb vs. Google Cloud Firestore vs. HyperSQL vs. Lovefield

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

Converged and high performance database for device data, events, time series, document and graph

Cloud Firestore is an auto-scaling document database for storing, syncing, and querying data for mobile and web apps. It offers seamless integration with other Firebase and Google Cloud Platform products.

Multithreaded, transactional RDBMS written in Java

also known as HSQLDB

Embeddable relational database for web apps written in pure JavaScript

Primary database model

Multivalue DBMS

Document store
Graph DBMS
Time Series DBMS

Document store

Relational DBMS

Secondary database models

Spatial DBMS

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

Score	3.17
Rank	#94	Overall
	#1	Multivalue DBMS

Score	0.08
Rank	#347	Overall
	#47	Document stores
	#34	Graph DBMS
	#31	Time Series DBMS

Score	7.85
Rank	#51	Overall
	#8	Document stores

Score	3.49
Rank	#87	Overall
	#47	Relational DBMS

Score	0.29
Rank	#293	Overall
	#133	Relational DBMS

Website

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

bangdb.com

firebase.google.com/products/firestore

hsqldb.org

google.github.io/lovefield

Technical documentation

docs.bangdb.com

firebase.google.com/docs/firestore

hsqldb.org/web/hsqlDocsFrame.html

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

Developer

Software AG

Sachin Sinha, BangDB

Google

Initial release

1971

2012

2017

2001

2014

Current release

BangDB 2.0, October 2021

2.7.2, June 2023

2.1.12, February 2017

License

Commercial or Open Source

commercial

Open Source

BSD 3

commercial

Open Source

based on BSD license

Open Source

Apache 2.0

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

C, C++

Java

JavaScript

Server operating systems

BS2000
Linux
Unix
Windows
z/OS
z/VSE

Linux

hosted

All OS with a Java VM

Embedded (into Java applications) and Client-Server operating modes

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

tested with Chrome, Firefox, IE, Safari

Data scheme

yes

schema-free

yes

Typing

predefined data types such as float or date

yes

yes: string, long, double, int, geospatial, stream, events

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

secondary, composite, nested, reverse, geospatial

yes

SQL

Support of SQL

yes

with add-on product Adabas SQL Gateway

SQL like support with command line tool

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

Proprietary protocol
RESTful HTTP API

Android
gRPC (using protocol buffers) API
iOS
JavaScript API
RESTful HTTP API

HTTP API

JDBC via HTTP
JDBC
ODBC

Supported programming languages

Natural

C
C#
C++
Java
Python

Go
Java
JavaScript
JavaScript (Node.js)
Objective-C
Python

All languages supporting JDBC/ODBC
Java

JavaScript

Server-side scripts

Stored procedures

in Natural

yes, Firebase Rules & Cloud Functions

Java, SQL

Triggers

yes, Notifications (with Streaming only)

yes, with Cloud Functions

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 (enterprise version only). P2P based virtual network overlay with consistent hashing and chord algorithm

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes, with add-on product Event Replicator

selectable replication factor, Knob for CAP (enterprise version only)

Multi-source replication

none

MapReduce

Offers an API for user-defined Map/Reduce methods

Using Cloud Dataflow

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Tunable consistency, set CAP knob accordingly

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

yes

ACID

Concurrency

Support for concurrent manipulation of data

yes

yes, optimistic concurrency control

yes

Durability

Support for making data persistent

yes

yes, implements WAL (Write ahead log) as well

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, run db with in-memory only mode

yes

using MemoryDB

User concepts

Access control

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

yes (enterprise version only)

Access rights for users, groups and roles based on Google Cloud Identity and Access Management. Security Rules for 3rd party authentication using Firebase Auth.

fine grained access rights according to SQL-standard

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More resources

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