DBMS > Cubrid vs. Databricks vs. Graph Engine vs. jBASE

System Properties Comparison Cubrid vs. Databricks vs. Graph Engine vs. jBASE

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Editorial information provided by DB-Engines

Name

Description

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

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.

A distributed in-memory data processing engine, underpinned by a strongly-typed RAM store and a general distributed computation engine

A robust multi-value DBMS comprising development tools and middleware

Primary database model

Relational DBMS

Document store
Relational DBMS

Graph DBMS
Key-value store

Multivalue DBMS

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

Score	1.20
Rank	#169	Overall
	#78	Relational DBMS

Score	78.61
Rank	#15	Overall
	#2	Document stores
	#10	Relational DBMS

Score	0.61
Rank	#240	Overall
	#21	Graph DBMS
	#35	Key-value stores

Score	1.41
Rank	#159	Overall
	#3	Multivalue DBMS

Website

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

www.databricks.com

www.graphengine.io

www.rocketsoftware.com/products/rocket-multivalue-application-development-platform/rocket-jbase

Technical documentation

cubrid.org/manuals

docs.databricks.com

www.graphengine.io/docs/manual

docs.rocketsoftware.com/bundle?labelkey=jbase_5.9

Developer

CUBRID Corporation, CUBRID Foundation

Databricks

Microsoft

Rocket Software (formerly Zumasys)

Initial release

2008

2013

2010

1991

Current release

11.0, January 2021

5.7

License

Commercial or Open Source

Open Source

Apache Version 2.0

commercial

Open Source

MIT License

commercial

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

C, C++, Java

.NET and C

Server operating systems

Linux
Windows

hosted

.NET

AIX
Linux
Windows

Data scheme

yes

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

yes

schema-free

Typing

predefined data types such as float or date

yes

optional

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

with Databricks SQL

Embedded SQL for jBASE in BASIC

APIs and other access methods

ADO.NET
JDBC
ODBC
OLE DB

JDBC
ODBC
RESTful HTTP API

RESTful HTTP API

JDBC
ODBC
Proprietary protocol
RESTful HTTP API
SOAP-based API

Supported programming languages

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

Python
R
Scala

C#
C++
F#
Visual Basic

.Net
Basic
Jabbascript
Java

Server-side scripts

Stored procedures

Java Stored Procedures

user defined functions and aggregates

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

none

horizontal partitioning

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

yes

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

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

optional: either by committing a write-ahead log (WAL) to the local persistent storage or by dumping the memory to a persistent storage

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

Access rights can be defined down to the item level

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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