DBMS > AgensGraph vs. BigchainDB vs. ClickHouse vs. Databricks vs. dBASE

System Properties Comparison AgensGraph vs. BigchainDB vs. ClickHouse vs. Databricks vs. dBASE

Editorial information provided by DB-Engines

Name

Description

Multi-model database supporting relational and graph data models and built upon PostgreSQL

BigchainDB is scalable blockchain database offering decentralization, immutability and native assets

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.

The Databricks Lakehouse Platform combines elements of data lakes and data warehouses to provide a unified view onto structured and unstructured data. It is based on Apache Spark.

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.

Primary database model

Graph DBMS
Relational DBMS

Document store

Relational DBMS

Document store
Relational DBMS

Relational DBMS

Secondary database models

Time Series DBMS

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

Score	0.23
Rank	#315	Overall
	#26	Graph DBMS
	#140	Relational DBMS

Score	0.85
Rank	#208	Overall
	#35	Document stores

Score	15.55
Rank	#38	Overall
	#23	Relational DBMS

Score	81.08
Rank	#15	Overall
	#2	Document stores
	#10	Relational DBMS

Score	9.70
Rank	#44	Overall
	#28	Relational DBMS

Website

bitnine.net/agensgraph

Technical documentation

bitnine.net/documentation

bigchaindb.readthedocs.io/en/latest

clickhouse.com/docs

docs.databricks.com

www.dbase.com/support/knowledgebase

Developer

Bitnine Global Inc.

Clickhouse Inc.

Databricks

Asthon Tate

Initial release

2016

2013

1979

Current release

2.1, December 2018

v24.4.1.2088-stable, May 2024

dBASE 2019, 2019

License

Commercial or Open Source

Open Source

Apache License 2.0

Open Source

AGPL v3

Open Source

Apache 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.

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.
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Aiven for Clickhouse: Managed cloud data warehousing with high-speed analytics.

Implementation language

Python

C++

Server operating systems

Linux
OS X
Windows

Linux

FreeBSD
Linux
macOS

hosted

DOS

dBase Classic
Windows

dBase Pro

Data scheme

depending on used data model

schema-free

yes

Flexible Schema (defined schema, partial schema, schema free)

yes

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

Close to ANSI SQL (SQL/JSON + extensions)

with Databricks SQL

APIs and other access methods

Cypher Query Language
JDBC

CLI Client
RESTful HTTP API

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

JDBC
ODBC
RESTful HTTP API

none

The IDE can access other DBMS or ODBC-sources.

Supported programming languages

C
Java
JavaScript
Python

Go
Haskell
Java
JavaScript
Python
Ruby

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

Python
R
Scala

dBase proprietary IDE

Server-side scripts

Stored procedures

yes

user defined functions and aggregates

The IDE can access stored procedures in other database systems.

Triggers

Partitioning methods

Methods for storing different data on different nodes

no, but can be realized using table inheritance

Sharding

key based and custom

none

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

selectable replication factor

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

yes

none

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

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

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

yes,with MongoDB ord RethinkDB

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

fine grained access rights according to SQL-standard

yes

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

More information provided by the system vendor

Specific characteristics

Supported database models : In addition to the Document store and Relational DBMS...
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