DBMS > Cubrid vs. Datomic vs. Oracle NoSQL vs. Typesense

System Properties Comparison Cubrid vs. Datomic vs. Oracle NoSQL vs. Typesense

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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

Datomic builds on immutable values, supports point-in-time queries and uses 3rd party systems for durability

A multi-model, scalable, distributed NoSQL database, designed to provide highly reliable, flexible, and available data management across a configurable set of storage nodes

A typo-tolerant, in-memory search engine optimized for instant search-as-you-type experiences and developer productivity

Primary database model

Relational DBMS

Document store
Key-value store
Relational DBMS

Search engine

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

Score	1.20
Rank	#169	Overall
	#78	Relational DBMS

Score	1.59
Rank	#150	Overall
	#69	Relational DBMS

Score	2.95
Rank	#100	Overall
	#17	Document stores
	#17	Key-value stores
	#50	Relational DBMS

Score	0.79
Rank	#210	Overall
	#14	Search engines

Website

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

www.datomic.com

www.oracle.com/database/nosql/technologies/nosql

typesense.org

Technical documentation

cubrid.org/manuals

docs.datomic.com

docs.oracle.com/en/database/other-databases/nosql-database/index.html

typesense.org/docs

Developer

CUBRID Corporation, CUBRID Foundation

Cognitect

Oracle

Initial release

2008

2012

2011

2015

Current release

11.0, January 2021

1.0.6735, June 2023

23.3, December 2023

License

Commercial or Open Source

Open Source

Apache Version 2.0

commercial

limited edition free

Open Source

Proprietary for Enterprise Edition (Oracle Database EE license has Oracle NoSQL database EE covered: details)

Open Source

GPL V3

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.

Implementation language

C, C++, Java

Java, Clojure

Java

C++

Server operating systems

Linux
Windows

All OS with a Java VM

Linux
Solaris SPARC/x86

Linux

Data scheme

yes

Support Fixed schema and Schema-less deployment with the ability to interoperate between them.

schema-free

pre-defined schema optional

Typing

predefined data types such as float or date

yes

optional

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

yes

SQL-like DML and DDL statements

APIs and other access methods

ADO.NET
JDBC
ODBC
OLE DB

RESTful HTTP API

Supported programming languages

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

Clojure
Java

C
C#
Go
Java
JavaScript (Node.js)
Python

.Net

community maintained
Clojure

community maintained
Dart

community maintained
Go

community maintained
Java

community maintained
JavaScript
Perl

community maintained
PHP
Python
Ruby
Rust

community maintained
Swift

community maintained

Server-side scripts

Stored procedures

Java Stored Procedures

yes

Transaction Functions

Triggers

yes

By using transaction functions

Partitioning methods

Methods for storing different data on different nodes

none

But extensive use of caching in the application peers

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

none

But extensive use of caching in the application peers

Electable source-replica replication per shard. Support distributed global deployment with Multi-region table feature

Multi-source replication using RAFT

MapReduce

Offers an API for user-defined Map/Reduce methods

with Hadoop integration

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency
Immediate Consistency

depending on configuration

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

configurable

ACID within a storage node (=shard)

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

using external storage systems (e.g. Cassandra, DynamoDB, PostgreSQL, Couchbase and others)

yes

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

yes

recommended only for testing and development

yes

off heap cache

yes

User concepts

Access control

fine grained access rights according to SQL-standard

Access rights for users and roles

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