DBMS > ClickHouse vs. dBASE vs. Google Cloud Bigtable vs. Oracle NoSQL vs. Pinecone

System Properties Comparison ClickHouse vs. dBASE vs. Google Cloud Bigtable vs. Oracle NoSQL vs. Pinecone

Editorial information provided by DB-Engines

Name

Description

A high-performance, column-oriented SQL DBMS for online analytical processing (OLAP) that uses all available system resources to their full potential to process each analytical query as fast as possible. It is available as both an open-source software and a cloud offering.

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 multi-model, scalable, distributed NoSQL database, designed to provide highly reliable, flexible, and available data management across a configurable set of storage nodes

A managed, cloud-native vector database

Primary database model

Relational DBMS

Key-value store
Wide column store

Document store
Key-value store
Relational DBMS

Vector DBMS

Secondary database models

Time Series DBMS

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

Score	16.34
Rank	#38	Overall
	#23	Relational DBMS

Score	10.34
Rank	#44	Overall
	#28	Relational DBMS

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

Score	2.95
Rank	#100	Overall
	#17	Document stores
	#17	Key-value stores
	#50	Relational DBMS

Score	3.16
Rank	#95	Overall
	#2	Vector DBMS

Website

clickhouse.com

www.dbase.com

cloud.google.com/bigtable

www.oracle.com/database/nosql/technologies/nosql

www.pinecone.io

Technical documentation

clickhouse.com/docs

www.dbase.com/support/knowledgebase

cloud.google.com/bigtable/docs

docs.oracle.com/en/database/other-databases/nosql-database/index.html

docs.pinecone.io/docs/overview

Developer

Clickhouse Inc.

Asthon Tate

Google

Oracle

Pinecone Systems, Inc

Initial release

2016

1979

2015

2011

2019

Current release

v24.4.1.2088-stable, May 2024

dBASE 2019, 2019

23.3, December 2023

License

Commercial or Open Source

Open Source

Apache 2.0

commercial

Open Source

Proprietary for Enterprise Edition (Oracle Database EE license has Oracle NoSQL database EE covered: details)

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.

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Implementation language

C++

Java

Server operating systems

FreeBSD
Linux
macOS

DOS

dBase Classic
Windows

dBase Pro

hosted

Linux
Solaris SPARC/x86

hosted

Data scheme

yes

schema-free

Support Fixed schema and Schema-less deployment with the ability to interoperate between them.

Typing

predefined data types such as float or date

yes

optional

String, Number, Boolean

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

Close to ANSI SQL (SQL/JSON + extensions)

SQL-like DML and DDL statements

APIs and other access methods

gRPC
HTTP REST
JDBC
MySQL wire protocol
ODBC
PostgreSQL wire protocol
Proprietary protocol

none

The IDE can access other DBMS or ODBC-sources.

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

RESTful HTTP API

Supported programming languages

3rd party library
C++
Elixir

3rd party library
Go

3rd party library
Java

3rd party library
JavaScript (Node.js)

3rd party library
Kotlin

3rd party library
Nim

3rd party library
Perl

3rd party library
PHP

3rd party library
Python

3rd party library
R

3rd party library
Ruby

3rd party library
Rust
Scala

3rd party library

dBase proprietary IDE

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

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

Python

Server-side scripts

Stored procedures

yes

The IDE can access stored procedures in other database systems.

Triggers

Partitioning methods

Methods for storing different data on different nodes

key based and custom

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Asynchronous and synchronous physical replication; geographically distributed replicas; support for object storages.

none

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

Electable source-replica replication per shard. Support distributed global deployment with Multi-region table feature

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

with Hadoop integration

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)

Eventual Consistency
Immediate Consistency

depending on configuration

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

Atomic single-row operations

configurable

ACID within a storage node (=shard)

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

off heap cache

User concepts

Access control

Access rights for users and roles. Column and row based policies. Quotas and resource limits. Pluggable authentication with LDAP and Kerberos. Password based, X.509 certificate, and SSH key authentication.

Access rights for users and roles

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

Access rights for users and roles

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