DBMS > Cubrid vs. Ehcache vs. Lovefield vs. Machbase Neo

System Properties Comparison Cubrid vs. Ehcache vs. Lovefield vs. Machbase Neo

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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 widely adopted Java cache with tiered storage options

Embeddable relational database for web apps written in pure JavaScript

TimeSeries DBMS for AIoT and BigData

Primary database model

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

Score	0.97
Rank	#189	Overall
	#86	Relational DBMS

Score	4.79
Rank	#66	Overall
	#8	Key-value stores

Score	0.22
Rank	#306	Overall
	#138	Relational DBMS

Score	0.07
Rank	#348	Overall
	#34	Time Series DBMS

Website

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

www.ehcache.org

google.github.io/lovefield

machbase.com

Technical documentation

cubrid.org/manuals

www.ehcache.org/documentation

github.com/google/lovefield/blob/master/docs/spec_index.md

machbase.com/dbms

Developer

CUBRID Corporation, CUBRID Foundation

Terracotta Inc, owned by Software AG

Google

Machbase

Initial release

2008

2009

2014

2013

Current release

11.0, January 2021

3.10.0, March 2022

2.1.12, February 2017

V8.0, August 2023

License

Commercial or Open Source

Open Source

Apache Version 2.0

Open Source

Apache Version 2; commercial licenses available

Open Source

Apache 2.0

commercial

free test version 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.

Implementation language

C, C++, Java

Java

JavaScript

Server operating systems

Linux
Windows

All OS with a Java VM

server-less, requires a JavaScript environment (browser, Node.js)

tested with Chrome, Firefox, IE, Safari

Linux
macOS
Windows

Data scheme

yes

schema-free

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

SQL

Support of SQL

yes

SQL-like query language

via JavaScript builder pattern

SQL-like query language

APIs and other access methods

ADO.NET
JDBC
ODBC
OLE DB

JCache

gRPC
HTTP REST
JDBC
MQTT (Message Queue Telemetry Transport)
ODBC

Supported programming languages

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

Java

JavaScript

C
C#
C++
Go
Java
JavaScript
PHP

via ODBC
Python
R

via ODBC
Scala

Server-side scripts

Stored procedures

Java Stored Procedures

Triggers

yes

Cache Event Listeners

Using read-only observers

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

by using Terracotta Server

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

yes

by using Terracotta Server

none

selectable replication factor

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Tunable Consistency (Strong, Eventual, Weak)

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

yes

supports JTA and can work as an XA resource

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

using a tiered cache-storage approach

yes, by using IndexedDB or the cloud service Firebase Realtime Database

In-memory capabilities

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

yes

using MemoryDB

yes

volatile and lookup table

User concepts

Access control

fine grained access rights according to SQL-standard

simple password-based access control

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