DBMS > Apache Phoenix vs. Cubrid vs. dBASE vs. Google Cloud Spanner vs. Snowflake

System Properties Comparison Apache Phoenix vs. Cubrid vs. dBASE vs. Google Cloud Spanner vs. Snowflake

Editorial information provided by DB-Engines

Name

Description

A scale-out RDBMS with evolutionary schema built on Apache HBase

CUBRID is an open-source SQL-based relational database management system with object extensions for OLTP

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.

A horizontally scalable, globally consistent, relational database service. It is the externalization of the core Google database that runs the biggest aspects of Google, like Ads and Google Play.

Cloud-based data warehousing service for structured and semi-structured data

Primary database model

Relational DBMS

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

Score	1.90
Rank	#125	Overall
	#59	Relational DBMS

Score	0.97
Rank	#189	Overall
	#86	Relational DBMS

Score	9.16
Rank	#43	Overall
	#27	Relational DBMS

Score	2.69
Rank	#101	Overall
	#51	Relational DBMS

Score	133.72
Rank	#7	Overall
	#5	Relational DBMS

Website

phoenix.apache.org

cubrid.com (korean)
cubrid.org (english)

www.dbase.com

cloud.google.com/spanner

www.snowflake.com

Technical documentation

phoenix.apache.org

cubrid.org/manuals

www.dbase.com/support/knowledgebase

cloud.google.com/spanner/docs

docs.snowflake.net/manuals/index.html

Developer

Apache Software Foundation

CUBRID Corporation, CUBRID Foundation

Asthon Tate

Google

Snowflake Computing Inc.

Initial release

2014

2008

1979

2017

2014

Current release

5.0-HBase2, July 2018 and 4.15-HBase1, December 2019

11.0, January 2021

dBASE 2019, 2019

License

Commercial or Open Source

Open Source

Apache Version 2.0

Open Source

Apache Version 2.0

commercial

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, C++, Java

Server operating systems

Linux
Unix
Windows

Linux
Windows

DOS

dBase Classic
Windows

dBase Pro

hosted

Data scheme

yes

late-bound, schema-on-read capabilities

yes

support of semi-structured data formats (JSON, XML, Avro)

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

Secondary indexes

yes

SQL

Support of SQL

yes

Query statements complying to ANSI 2011

yes

APIs and other access methods

JDBC

ADO.NET
JDBC
ODBC
OLE DB

none

The IDE can access other DBMS or ODBC-sources.

gRPC (using protocol buffers) API
JDBC

At present, JDBC supports read-only queries. No support for DDL or DML statements.
RESTful HTTP API

CLI Client
JDBC
ODBC

Supported programming languages

C
C#
C++
Go
Groovy
Java
PHP
Python
Scala

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

dBase proprietary IDE

Go
Java
JavaScript (Node.js)
Python

JavaScript (Node.js)
Python

Server-side scripts

Stored procedures

user defined functions

Java Stored Procedures

The IDE can access stored procedures in other database systems.

user defined functions

Triggers

yes

similar concept for controling cloud resources

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

Sharding

yes

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication
Source-replica replication

Source-replica replication

none

Multi-source replication with 3 replicas for regional instances.

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

Hadoop integration

yes

using Google Cloud Dataflow

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency or Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

by using interleaved tables, this features focuses more on performance improvements than on 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

ACID

Strict serializable isolation

ACID

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

User concepts

Access control

Access Control Lists (using HBase ACL) for RBAC, integration with Apache Ranger for RBAC & ABAC, multi-tenancy

fine grained access rights according to SQL-standard

Access rights for users and roles

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

Users with fine-grained authorization concept, user roles and pluggable authentication

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