DBMS > Ehcache vs. MongoDB vs. Tibero

System Properties Comparison Ehcache vs. MongoDB vs. Tibero

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Editorial information provided by DB-Engines

Name

Description

A widely adopted Java cache with tiered storage options

One of the most popular document stores available both as a fully managed cloud service and for deployment on self-managed infrastructure

A secure RDBMS, designed for easy portability from Oracle

Primary database model

Key-value store

Document store

Relational DBMS

Secondary database models

Spatial DBMS
Search engine

integrated Lucene index, currently in MongoDB Atlas only.
Time Series DBMS

Time Series Collections introduced in Release 5.0
Vector DBMS

currently available in the MongoDB Atlas cloud service only

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

Score	3.98
Rank	#67	Overall
	#8	Key-value stores

Score	402.51
Rank	#5	Overall
	#1	Document stores

Score	1.42
Rank	#150	Overall
	#67	Relational DBMS

Website

www.ehcache.org

www.mongodb.com

us.tmaxsoft.com/products/tibero

Technical documentation

www.ehcache.org/documentation

www.mongodb.com/docs/manual

technet.tmaxsoft.com/upload/download/online/tibero/pver-20150504-000002/index.html

Developer

Terracotta Inc, owned by Software AG

MongoDB, Inc

TmaxSoft

Initial release

2009

2003

Current release

3.10.0, March 2022

7.0.5, January 2024

7, September 2022

License

Commercial or Open Source

Open Source

Apache Version 2; commercial licenses available

Open Source

MongoDB Inc.'s Server Side Public License v1. Prior versions were published under GNU AGPL v3.0. Commercial licenses are also available.

commercial

Cloud-based only

Only available as a cloud service

MongoDB available as DBaaS (MongoDB Atlas)

DBaaS offerings (sponsored links)

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Implementation language

Java

C++

C and Assembler

Server operating systems

All OS with a Java VM

Linux
OS X
Solaris
Windows

AIX
HP-UX
Linux
Solaris
Windows

Data scheme

schema-free

Although schema-free, documents of the same collection often follow the same structure. Optionally impose all or part of a schema by defining a JSON schema.

yes

Typing

predefined data types such as float or date

yes

string, integer, double, decimal, boolean, date, object_id, geospatial

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

SQL

Support of SQL

Read-only SQL queries via the MongoDB Atlas SQL Interface

yes

APIs and other access methods

JCache

GraphQL
HTTP REST
Prisma
proprietary protocol using JSON

JDBC
ODBC
ODP.NET
Oracle Call Interface (OCI)
Tibero CLI

Supported programming languages

Java

Actionscript

unofficial driver
C
C#
C++
Clojure

unofficial driver
ColdFusion

unofficial driver
D

unofficial driver
Dart

unofficial driver
Delphi

unofficial driver
Erlang
Go
Groovy

unofficial driver
Haskell
Java
JavaScript
Kotlin
Lisp

unofficial driver
Lua

unofficial driver
MatLab

unofficial driver
Perl
PHP
PowerShell

unofficial driver
Prolog

unofficial driver
Python
R

unofficial driver
Ruby
Rust
Scala
Smalltalk

unofficial driver
Swift

C
C#
C++
Cobol
Java
Objective-C
Perl
PHP
Python
Ruby
Visual Basic

Server-side scripts

Stored procedures

JavaScript

Persistent Stored Procedure (PSM)

Triggers

yes

Cache Event Listeners

yes

in MongoDB Atlas only

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

by using Terracotta Server

Sharding

Partitioned by hashed, ranged, or zoned sharding keys. Live resharding allows users to change their shard keys as an online operation with zero downtime.

horizontal partitioning

by range, hash, list or composite

Replication methods

Methods for redundantly storing data on multiple nodes

yes

by using Terracotta Server

Multi-Source deployments with MongoDB Atlas Global Clusters
Source-replica replication

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Tunable Consistency (Strong, Eventual, Weak)

Eventual Consistency

can be individually decided for each read operation
Immediate Consistency

default behaviour

Immediate Consistency

Foreign keys

Referential integrity

typically not used, however similar functionality with DBRef possible

yes

Transaction concepts

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

yes

supports JTA and can work as an XA resource

Multi-document ACID Transactions with snapshot isolation

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

using a tiered cache-storage approach

yes

optional, enabled by default

yes

In-memory capabilities

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

yes

In-memory storage engine introduced with MongoDB version 3.2

planned for next version

User concepts

Access control

Access rights for users and roles

fine grained access rights according to SQL-standard (SQL 92, SQL 99)

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