DBMS > dBASE vs. GeoMesa vs. Google BigQuery vs. Google Cloud Bigtable vs. Hazelcast

System Properties Comparison dBASE vs. GeoMesa vs. Google BigQuery vs. Google Cloud Bigtable vs. Hazelcast

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.

GeoMesa is a distributed spatio-temporal DBMS based on various systems as storage layer.

Large scale data warehouse service with append-only tables

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 widely adopted in-memory data grid

Primary database model

Relational DBMS

Spatial DBMS

Relational DBMS

Key-value store
Wide column store

Key-value store

Secondary database models

Document store

JSON support with IMDG 3.12

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

Score	10.34
Rank	#44	Overall
	#28	Relational DBMS

Score	0.78
Rank	#213	Overall
	#4	Spatial DBMS

Score	60.38
Rank	#19	Overall
	#13	Relational DBMS

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

Score	5.97
Rank	#57	Overall
	#6	Key-value stores

Website

www.dbase.com

www.geomesa.org

cloud.google.com/bigquery

cloud.google.com/bigtable

hazelcast.com

Technical documentation

www.dbase.com/support/knowledgebase

www.geomesa.org/documentation/stable/user/index.html

cloud.google.com/bigquery/docs

cloud.google.com/bigtable/docs

hazelcast.org/imdg/docs

Developer

Asthon Tate

CCRi and others

Google

Hazelcast

Initial release

1979

2014

2010

2015

2008

Current release

dBASE 2019, 2019

4.0.5, February 2024

5.3.6, November 2023

License

Commercial or Open Source

commercial

Open Source

Apache License 2.0

commercial

Open Source

Apache Version 2; commercial licenses available

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

Scala

Java

Server operating systems

DOS

dBase Classic
Windows

dBase Pro

hosted

All OS with a Java VM

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.

yes

the object must implement a serialization strategy

Secondary indexes

yes

SQL

Support of SQL

yes

SQL-like query language

APIs and other access methods

none

The IDE can access other DBMS or ODBC-sources.

RESTful HTTP/JSON API

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

JCache
JPA
Memcached protocol
RESTful HTTP API

Supported programming languages

dBase proprietary IDE

.Net
Java
JavaScript
Objective-C
PHP
Python
Ruby

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

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

Server-side scripts

Stored procedures

The IDE can access stored procedures in other database systems.

user defined functions

in JavaScript

yes

Event Listeners, Executor Services

Triggers

yes

Events

Partitioning methods

Methods for storing different data on different nodes

none

depending on storage layer

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

none

depending on storage layer

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

yes

Replicated Map

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

depending on storage layer

Immediate Consistency

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

Immediate Consistency or Eventual Consistency selectable by user

Raft Consensus Algorithm

Foreign keys

Referential integrity

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

Since BigQuery is designed for querying data

Atomic single-row operations

one or two-phase-commit; repeatable reads; read commited

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

In-memory capabilities

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

depending on storage layer

yes

User concepts

Access control

Access rights for users and roles

yes

depending on the DBMS used for storage

Access privileges (owner, writer, reader) on dataset, table or view level

Google Cloud Identity & Access Management (IAM)

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

Role-based access control

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