DBMS > Cachelot.io vs. Cubrid vs. XTDB

System Properties Comparison Cachelot.io vs. Cubrid vs. XTDB

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Editorial information provided by DB-Engines

Name

Description

In-memory caching system

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

A general purpose database with bitemporal SQL and Datalog and graph queries

Primary database model

Key-value store

Relational DBMS

Document store

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Trend Chart

Score	0.00
Rank	#396	Overall
	#64	Key-value stores

Score	1.31
Rank	#169	Overall
	#78	Relational DBMS

Score	0.09
Rank	#351	Overall
	#47	Document stores

Website

cachelot.io

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

github.com/xtdb/xtdb
www.xtdb.com

Technical documentation

cubrid.org/manuals

www.xtdb.com/docs

Developer

CUBRID Corporation, CUBRID Foundation

Juxt Ltd.

Initial release

2015

2008

2019

Current release

11.0, January 2021

1.19, September 2021

License

Commercial or Open Source

Open Source

Simplified BSD License

Open Source

Apache Version 2.0

Open Source

MIT License

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

C++

C, C++, Java

Clojure

Server operating systems

FreeBSD
Linux
OS X

Linux
Windows

All OS with a Java 8 (and higher) VM
Linux

Data scheme

schema-free

yes

schema-free

Typing

predefined data types such as float or date

yes

yes, extensible-data-notation format

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

limited SQL, making use of Apache Calcite

APIs and other access methods

Memcached protocol

ADO.NET
JDBC
ODBC
OLE DB

HTTP REST
JDBC

Supported programming languages

.Net
C
C++
ColdFusion
Erlang
Java
Lisp
Lua
OCaml
OCaml
Perl
PHP
Python
Ruby

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

Clojure
Java

Server-side scripts

Stored procedures

Java Stored Procedures

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

none

Replication methods

Methods for redundantly storing data on multiple nodes

none

Source-replica replication

yes, each node contains all data

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

none

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

yes, flexibel persistency by using storage technologies like Apache Kafka, RocksDB or LMDB

In-memory capabilities

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

User concepts

Access control

fine grained access rights according to SQL-standard

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