DBMS > dBASE vs. Firebase Realtime Database vs. Google Cloud Bigtable vs. JanusGraph vs. SAP HANA

System Properties Comparison dBASE vs. Firebase Realtime Database vs. Google Cloud Bigtable vs. JanusGraph vs. SAP HANA

Editorial information provided by DB-Engines

Name

Description

dBase was one of the first databases with a development environment on PC's. Its latest version dBase V is still sold as dBase classic, which needs a DOS Emulation. The up-to-date product is dBase plus.

Cloud-hosted realtime document store. iOS, Android, and JavaScript clients share one Realtime Database instance and automatically receive updates with the newest data.

Google's NoSQL Big Data database service. It's the same database that powers many core Google services, including Search, Analytics, Maps, and Gmail.

A Graph DBMS optimized for distributed clusters

It was forked from the latest code base of Titan in January 2017

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

Primary database model

Relational DBMS

Document store

Key-value store
Wide column store

Graph DBMS

Relational DBMS

Secondary database models

Document store
Graph DBMS

with SAP Hana, Enterprise Edition
Spatial DBMS

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

Score	10.34
Rank	#44	Overall
	#28	Relational DBMS

Score	14.29
Rank	#39	Overall
	#6	Document stores

Score	3.26
Rank	#92	Overall
	#13	Key-value stores
	#8	Wide column stores

Score	1.94
Rank	#129	Overall
	#12	Graph DBMS

Score	44.69
Rank	#22	Overall
	#16	Relational DBMS

Website

www.dbase.com

firebase.google.com/products/realtime-database

cloud.google.com/bigtable

janusgraph.org

www.sap.com/products/hana.html

Technical documentation

www.dbase.com/support/knowledgebase

firebase.google.com/docs/database

cloud.google.com/bigtable/docs

docs.janusgraph.org

help.sap.com/hana

Developer

Asthon Tate

Google

acquired by Google 2014

Google

Linux Foundation; originally developed as Titan by Aurelius

SAP

Initial release

1979

2012

2015

2017

2010

Current release

dBASE 2019, 2019

0.6.3, February 2023

2.0 SPS07 (April 4, 2023), April 2023

License

Commercial or Open Source

commercial

Open Source

Apache 2.0

commercial

Cloud-based only

Only available as a cloud service

yes

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

Java

Server operating systems

DOS

dBase Classic
Windows

dBase Pro

hosted

Linux
OS X
Unix
Windows

Appliance or cloud-service

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

APIs and other access methods

none

The IDE can access other DBMS or ODBC-sources.

Android
iOS
JavaScript API
RESTful HTTP API

gRPC (using protocol buffers) API
HappyBase (Python library)
HBase compatible API (Java)

Java API
TinkerPop Blueprints
TinkerPop Frames
TinkerPop Gremlin
TinkerPop Rexster

JDBC
ODBC

Supported programming languages

dBase proprietary IDE

Java
JavaScript
Objective-C

C#
C++
Go
Java
JavaScript (Node.js)
Python

Clojure
Java
Python

Server-side scripts

Stored procedures

The IDE can access stored procedures in other database systems.

limited functionality with using 'rules'

yes

SQLScript, R

Triggers

Callbacks are triggered when data changes

yes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

yes

depending on the used storage backend (e.g. Cassandra, HBase, BerkeleyDB)

yes

Replication methods

Methods for redundantly storing data on multiple nodes

none

Internal replication in Colossus, and regional replication between two clusters in different zones

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

via Faunus, a graph analytics engine

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

if the client is offline
Immediate Consistency

if the client is online

Immediate consistency (for a single cluster), Eventual consistency (for two or more replicated clusters)

Eventual Consistency
Immediate Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

Relationships in graphs

yes

Transaction concepts

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

not for dBase internal data, but IDE does support transactions when accessing external DBMS

yes

Atomic single-row operations

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

Supports various storage backends: Cassandra, HBase, Berkeley DB, Akiban, Hazelcast

yes

In-memory capabilities

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

yes

User concepts

Access control

Access rights for users and roles

yes, based on authentication and database rules

Access rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)

User authentification and security via Rexster Graph Server

yes

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