DBMS > Ehcache vs. GeoMesa vs. Graph Engine

System Properties Comparison Ehcache vs. GeoMesa vs. Graph Engine

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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.

A distributed in-memory data processing engine, underpinned by a strongly-typed RAM store and a general distributed computation engine

Primary database model

Key-value store

Spatial DBMS

Graph DBMS
Key-value store

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

Score	4.89
Rank	#67	Overall
	#8	Key-value stores

Score	0.78
Rank	#213	Overall
	#4	Spatial DBMS

Score	0.61
Rank	#240	Overall
	#21	Graph DBMS
	#35	Key-value stores

Website

www.ehcache.org

www.geomesa.org

www.graphengine.io

Technical documentation

www.ehcache.org/documentation

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

www.graphengine.io/docs/manual

Developer

Terracotta Inc, owned by Software AG

CCRi and others

Microsoft

Initial release

2009

2014

2010

Current release

3.10.0, March 2022

4.0.5, February 2024

License

Commercial or Open Source

Open Source

Apache Version 2; commercial licenses available

Open Source

Apache License 2.0

Open Source

MIT License

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

Java

Scala

.NET and C

Server operating systems

All OS with a Java VM

.NET

Data scheme

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

APIs and other access methods

JCache

RESTful HTTP API

Supported programming languages

Java

C#
C++
F#
Visual Basic

Server-side scripts

Stored procedures

yes

Triggers

yes

Cache Event Listeners

Partitioning methods

Methods for storing different data on different nodes

Sharding

by using Terracotta Server

depending on storage layer

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

yes

by using Terracotta Server

depending on storage layer

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

Foreign keys

Referential integrity

Transaction concepts

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

yes

supports JTA and can work as an XA resource

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

using a tiered cache-storage approach

yes

optional: either by committing a write-ahead log (WAL) to the local persistent storage or by dumping the memory to a persistent storage

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

User concepts

Access control

yes

depending on the DBMS used for storage

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More resources

DB-Engines blog posts

Spatial database management systems
6 April 2021, Matthias Gelbmann

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