DBMS > ClickHouse vs. dBASE vs. Google Cloud Datastore vs. TerminusDB

System Properties Comparison ClickHouse vs. dBASE vs. Google Cloud Datastore vs. TerminusDB

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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.

Automatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud Platform

Scalable Graph Database platform making enterprise data available by exploiting inferred entities and relationships

Primary database model

Relational DBMS

Document store

Graph DBMS

Secondary database models

Time Series DBMS

Document store
RDF store

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

Score	15.88
Rank	#37	Overall
	#22	Relational DBMS

Score	9.16
Rank	#43	Overall
	#27	Relational DBMS

Score	4.13
Rank	#71	Overall
	#12	Document stores

Score	0.19
Rank	#311	Overall
	#27	Graph DBMS

Website

clickhouse.com

www.dbase.com

cloud.google.com/datastore

terminusdb.com

Technical documentation

clickhouse.com/docs

www.dbase.com/support/knowledgebase

cloud.google.com/datastore/docs

terminusdb.github.io/terminusdb/#

Developer

Clickhouse Inc.

Asthon Tate

Google

DataChemist Ltd.

Initial release

2016

1979

2008

2018

Current release

v24.6.2.17-stable, July 2024

dBASE 2019, 2019

11.0.0, January 2023

License

Commercial or Open Source

Open Source

Apache 2.0

commercial

Open Source

GPL V3

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.

DoubleCloud: Fully managed ClickHouse alongside best-in-class managed open-source services to build analytics at scale.
ClickHouse Cloud: Get the performance you love from open source ClickHouse in a serverless offering that takes care of the details so you can spend more time getting insight out of the fastest database on earth.

Implementation language

C++

Prolog, Rust

Server operating systems

FreeBSD
Linux
macOS

DOS

dBase Classic
Windows

dBase Pro

hosted

Linux

Data scheme

yes

schema-free

yes

Typing

predefined data types such as float or date

yes

yes, details here

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

Close to ANSI SQL (SQL/JSON + extensions)

SQL-like query language (GQL)

SQL-like query language (WOQL)

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
RESTful HTTP/JSON API

OWL
RESTful HTTP API
WOQL (Web Object Query Language)

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

.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby

JavaScript
Python

Server-side scripts

Stored procedures

yes

The IDE can access stored procedures in other database systems.

using Google App Engine

yes

Triggers

Callbacks using the Google Apps Engine

yes

Partitioning methods

Methods for storing different data on different nodes

key based and custom

none

Sharding

Graph Partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

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

none

Multi-source replication using Paxos

Journaling Streams

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

using Google Cloud Dataflow

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Immediate Consistency or Eventual Consistency depending on type of query and configuration

Strong Consistency is default for entity lookups and queries within an Entity Group (but can instead be made eventually consistent). Other queries are always eventual consistent.

Foreign keys

Referential integrity

yes

via ReferenceProperties or Ancestor paths

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

ACID

Serializable Isolation within Transactions, Read Committed outside of Transactions

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

in-memory journaling

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. 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)

Role-based access control

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