DBMS > CockroachDB vs. dBASE vs. Google Cloud Bigtable vs. Hazelcast vs. Oracle

System Properties Comparison CockroachDB vs. dBASE vs. Google Cloud Bigtable vs. Hazelcast vs. Oracle

Editorial information provided by DB-Engines

Name

Description

CockroachDB is a distributed database architected for modern cloud applications. It is wire compatible with PostgreSQL and backed by a Key-Value Store, which is either RocksDB or a purpose-built derivative, called Pebble.

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.

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

Widely used RDBMS

Primary database model

Relational DBMS

Key-value store
Wide column store

Key-value store

Relational DBMS

Secondary database models

Document store

JSON support with IMDG 3.12

Document store
Graph DBMS

with Oracle Spatial and Graph
RDF store

with Oracle Spatial and Graph
Spatial DBMS

with Oracle Spatial and Graph
Vector DBMS

since Oracle 23

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

Score	6.10
Rank	#58	Overall
	#33	Relational DBMS

Score	11.18
Rank	#44	Overall
	#28	Relational DBMS

Score	3.58
Rank	#92	Overall
	#14	Key-value stores
	#8	Wide column stores

Score	6.87
Rank	#55	Overall
	#6	Key-value stores

Score	1234.27
Rank	#1	Overall
	#1	Relational DBMS

Website

www.cockroachlabs.com

www.dbase.com

cloud.google.com/bigtable

hazelcast.com

www.oracle.com/database

Technical documentation

www.cockroachlabs.com/docs

www.dbase.com/support/knowledgebase

cloud.google.com/bigtable/docs

hazelcast.org/imdg/docs

docs.oracle.com/en/database

Developer

Cockroach Labs

Asthon Tate

Google

Hazelcast

Oracle

Initial release

2015

1979

2015

2008

1980

Current release

23.1.1, May 2023

dBASE 2019, 2019

5.3.6, November 2023

23c, September 2023

License

Commercial or Open Source

Open Source

Apache 2.0, commercial license available

commercial

Open Source

Apache Version 2; commercial licenses available

commercial

restricted free version is 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

Java

C and C++

Server operating systems

Linux
macOS
Windows

DOS

dBase Classic
Windows

dBase Pro

hosted

All OS with a Java VM

AIX
HP-UX
Linux
OS X
Solaris
Windows
z/OS

Data scheme

dynamic schema

yes

schema-free

yes

Schemaless in JSON and XML columns

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

yes

Secondary indexes

yes

SQL

Support of SQL

yes, wire compatible with PostgreSQL

SQL-like query language

yes

with proprietary extensions

APIs and other access methods

JDBC

none

The IDE can access other DBMS or ODBC-sources.

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

JCache
JPA
Memcached protocol
RESTful HTTP API

JDBC
ODBC
ODP.NET
Oracle Call Interface (OCI)

Supported programming languages

C#
C++
Clojure
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
Rust

dBase proprietary IDE

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

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

C
C#
C++
Clojure
Cobol
Delphi
Eiffel
Erlang
Fortran
Groovy
Haskell
Java
JavaScript
Lisp
Objective C
OCaml
Perl
PHP
Python
R
Ruby
Scala
Tcl
Visual Basic

Server-side scripts

Stored procedures

The IDE can access stored procedures in other database systems.

yes

Event Listeners, Executor Services

PL/SQL

also stored procedures in Java possible

Triggers

yes

Events

yes

Partitioning methods

Methods for storing different data on different nodes

horizontal partitioning (by key range)

all tables are translated to an ordered KV store and then broken down into 64MB ranges, which are then used as replicas in RAFT

none

Sharding

Sharding, horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication using RAFT

none

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

yes

Replicated Map

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

can be realized in PL/SQL

Consistency concepts

Methods to ensure consistency in a distributed system

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

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

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

Atomic single-row operations

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

ACID

isolation level can be parameterized

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.

yes

Version 12c introduced the new option 'Oracle Database In-Memory'

User concepts

Access control

Role-based access control

Access rights for users and roles

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

Role-based access control

fine grained access rights according to SQL-standard

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