DBMS > Cubrid vs. SAP HANA vs. SpatiaLite vs. Sphinx

System Properties Comparison Cubrid vs. SAP HANA vs. SpatiaLite vs. Sphinx

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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

In-memory, column based data store. Available as appliance or cloud service

Spatial extension of SQLite

Open source search engine for searching in data from different sources, e.g. relational databases

Primary database model

Relational DBMS

Spatial DBMS

Search engine

Secondary database models

Document store
Graph DBMS

with SAP Hana, Enterprise Edition
Spatial DBMS

Relational DBMS

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

Score	1.20
Rank	#169	Overall
	#78	Relational DBMS

Score	44.69
Rank	#22	Overall
	#16	Relational DBMS

Score	1.60
Rank	#149	Overall
	#3	Spatial DBMS

Score	5.98
Rank	#56	Overall
	#5	Search engines

Website

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

www.sap.com/products/hana.html

www.gaia-gis.it/fossil/libspatialite/index

sphinxsearch.com

Technical documentation

cubrid.org/manuals

help.sap.com/hana

www.gaia-gis.it/gaia-sins/spatialite_topics.html

sphinxsearch.com/docs

Developer

CUBRID Corporation, CUBRID Foundation

SAP

Alessandro Furieri

Sphinx Technologies Inc.

Initial release

2008

2010

2008

2001

Current release

11.0, January 2021

2.0 SPS07 (April 4, 2023), April 2023

5.0.0, August 2020

3.5.1, February 2023

License

Commercial or Open Source

Open Source

Apache Version 2.0

commercial

Open Source

MPL 1.1, GPL v2.0 or LGPL v2.1

Open Source

GPL version 2, commercial licence available

Cloud-based only

Only available as a cloud service

also available as a cloud based service

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

C, C++, Java

C++

Server operating systems

Linux
Windows

Appliance or cloud-service

server-less

FreeBSD
Linux
NetBSD
OS X
Solaris
Windows

Data scheme

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.

Secondary indexes

yes

full-text index on all search fields

SQL

Support of SQL

yes

SQL-like query language (SphinxQL)

APIs and other access methods

ADO.NET
JDBC
ODBC
OLE DB

JDBC
ODBC

Proprietary protocol

Supported programming languages

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

C++

unofficial client library
Java
Perl

unofficial client library
PHP
Python
Ruby

unofficial client library

Server-side scripts

Stored procedures

Java Stored Procedures

SQLScript, R

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

none

yes

none

Sharding

Partitioning is done manually, search queries against distributed index is supported

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

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

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

The original contents of fields are not stored in the Sphinx index.

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

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