DBMS > Cubrid vs. OpenSearch vs. Oracle vs. Splice Machine

System Properties Comparison Cubrid vs. OpenSearch vs. Oracle vs. Splice Machine

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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

A distributed, RESTful search and analytics engine forked from Elasticsearch and based on Apache Lucene

Widely used RDBMS

Open-Source SQL RDBMS for Operational and Analytical use cases with native Machine Learning, powered by Hadoop and Spark

Primary database model

Relational DBMS

Search engine

Relational DBMS

Secondary database models

Vector DBMS

Document store
Graph DBMS

with Oracle Spatial and Graph
RDF store

with Oracle Spatial and Graph
Spatial DBMS

with Oracle Spatial and Graph
Vector DBMS

since Oracle 23

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

Score	0.97
Rank	#189	Overall
	#86	Relational DBMS

Score	16.31
Rank	#36	Overall
	#4	Search engines

Score	1286.59
Rank	#1	Overall
	#1	Relational DBMS

Score	0.54
Rank	#244	Overall
	#114	Relational DBMS

Website

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

github.com/opensearch-project
opensearch.org

www.oracle.com/database

splicemachine.com

Technical documentation

cubrid.org/manuals

opensearch.org/docs/latest

docs.oracle.com/en/database

splicemachine.com/how-it-works

Developer

CUBRID Corporation, CUBRID Foundation

Amazon Web Services

Oracle

Splice Machine

Initial release

2008

2021

1980

2014

Current release

11.0, January 2021

2.5.0, January 2023

23c, September 2023

3.1, March 2021

License

Commercial or Open Source

Open Source

Apache Version 2.0

Open Source

Apache Version 2.0

commercial

restricted free version is available

Open Source

AGPL 3.0, commercial license available

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

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

STACKIT OpenSearch offers OpenSearch in a managed version in enterprise grade, 100% GDPR-compliant, for a wide range of applications like analytics, website search, offering scalability and fast data access.

Implementation language

C, C++, Java

Java

C and C++

Java

Server operating systems

Linux
Windows

All OS with a Java VM

AIX
HP-UX
Linux
OS X
Solaris
Windows
z/OS

Linux
OS X
Solaris
Windows

Data scheme

yes

schema-free

Flexible type definitions. Once a type is defined, it is persistent

yes

Schemaless in JSON and XML columns

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

All search fields are automatically indexed

yes

SQL

Support of SQL

yes

SQL-like query language

yes

with proprietary extensions

yes

APIs and other access methods

ADO.NET
JDBC
ODBC
OLE DB

Java API
RESTful HTTP/JSON API

JDBC
ODBC
ODP.NET
Oracle Call Interface (OCI)

JDBC
Native Spark Datasource
ODBC

Supported programming languages

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

Go
Java
JavaScript (Node.js)
PHP
Python
Ruby

Elasticsearch client

C
C#
C++
Clojure
Cobol
Delphi
Eiffel
Erlang
Fortran
Groovy
Haskell
Java
JavaScript
Lisp
Objective C
OCaml
Perl
PHP
Python
R
Ruby
Scala
Tcl
Visual Basic

C#
C++
Java
JavaScript (Node.js)
Python
R
Scala

Server-side scripts

Stored procedures

Java Stored Procedures

yes

PL/SQL

also stored procedures in Java possible

yes

Java

Triggers

yes

by using the 'percolation' feature

yes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

Sharding, horizontal partitioning

Shared Nothhing Auto-Sharding, Columnar Partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

yes

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

can be realized in PL/SQL

Yes, via Full Spark Integration

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

Synchronous doc based replication. Get by ID may show delays up to 1 sec. Configurable write consistency: one, quorum, all

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

Support to ensure data integrity after non-atomic manipulations of data

ACID

isolation level can be parameterized

ACID

Concurrency

Support for concurrent manipulation of data

yes

yes, multi-version concurrency control (MVCC)

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

Version 12c introduced the new option 'Oracle Database In-Memory'

yes

User concepts

Access control

fine grained access rights according to SQL-standard

Access rights for users, groups and roles according to SQL-standard

More information provided by the system vendor

Specific characteristics

OpenSearch is a highly scalable and extensible open-source software suite for search,...
» more

Competitive advantages

Distributed as fully open source under Apache License, Version 2.0 (ALv2), OpenSearch...
» more

Typical application scenarios

The OpenSearch platform is used across a broad range of search , analytics, and observability...
» more

Licensing and pricing models

The OpenSearch Project offers open source software licensed under Apache License...
» more

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