DBMS > Ehcache vs. GeoMesa vs. MongoDB

System Properties Comparison Ehcache vs. GeoMesa vs. MongoDB

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Editorial information provided by DB-Engines

Name

Description

A widely adopted Java cache with tiered storage options

GeoMesa is a distributed spatio-temporal DBMS based on various systems as storage layer.

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

Primary database model

Key-value store

Spatial DBMS

Document store

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	0.72
Rank	#220	Overall
	#4	Spatial DBMS

Score	402.51
Rank	#5	Overall
	#1	Document stores

Website

www.ehcache.org

www.geomesa.org

www.mongodb.com

Technical documentation

www.ehcache.org/documentation

www.geomesa.org/documentation/stable/user/index.html

www.mongodb.com/docs/manual

Developer

Terracotta Inc, owned by Software AG

CCRi and others

MongoDB, Inc

Initial release

2009

2014

2009

Current release

3.10.0, March 2022

5.0.1, July 2024

7.0.5, January 2024

License

Commercial or Open Source

Open Source

Apache Version 2; commercial licenses available

Open Source

Apache License 2.0

Open Source

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

Cloud-based only

Only available as a cloud service

MongoDB available as DBaaS (MongoDB Atlas)

DBaaS offerings (sponsored links)

Database as a Service

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

Implementation language

Java

Scala

C++

Server operating systems

All OS with a Java VM

Linux
OS X
Solaris
Windows

Data scheme

schema-free

yes

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.

Typing

predefined data types such as float or date

yes

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

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

Read-only SQL queries via the MongoDB Atlas SQL Interface

APIs and other access methods

JCache

GraphQL
HTTP REST
Prisma
proprietary protocol using JSON

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

Server-side scripts

Stored procedures

JavaScript

Triggers

yes

Cache Event Listeners

yes

in MongoDB Atlas only

Partitioning methods

Methods for storing different data on different nodes

Sharding

by using Terracotta Server

depending on storage layer

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.

Replication methods

Methods for redundantly storing data on multiple nodes

yes

by using Terracotta Server

depending on storage layer

Multi-Source deployments with MongoDB Atlas Global Clusters
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)

depending on storage layer

Eventual Consistency

can be individually decided for each read operation
Immediate Consistency

default behaviour

Foreign keys

Referential integrity

typically not used, however similar functionality with DBRef possible

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

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

In-memory capabilities

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

yes

depending on storage layer

yes

In-memory storage engine introduced with MongoDB version 3.2

User concepts

Access control

yes

depending on the DBMS used for storage

Access rights for users and roles

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