DBMS > Ehcache vs. H2 vs. IBM Cloudant vs. Spark SQL

System Properties Comparison Ehcache vs. H2 vs. IBM Cloudant vs. Spark SQL

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Editorial information provided by DB-Engines

Name

Description

A widely adopted Java cache with tiered storage options

Full-featured RDBMS with a small footprint, either embedded into a Java application or used as a database server.

Database as a Service offering based on Apache CouchDB

Spark SQL is a component on top of 'Spark Core' for structured data processing

Primary database model

Secondary database models

Spatial DBMS

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

Score	5.23
Rank	#68	Overall
	#8	Key-value stores

Score	8.22
Rank	#50	Overall
	#32	Relational DBMS

Score	2.73
Rank	#108	Overall
	#20	Document stores

Score	19.15
Rank	#33	Overall
	#20	Relational DBMS

Website

www.ehcache.org

www.h2database.com

www.ibm.com/products/cloudant

spark.apache.org/sql

Technical documentation

www.ehcache.org/documentation

www.h2database.com/html/main.html

cloud.ibm.com/docs/Cloudant

spark.apache.org/docs/latest/sql-programming-guide.html

Developer

Terracotta Inc, owned by Software AG

Thomas Mueller

IBM, Apache Software Foundation

IBM acquired Cloudant in February 2014

Apache Software Foundation

Initial release

2009

2005

2010

2014

Current release

3.10.0, March 2022

2.2.220, July 2023

3.5.0 ( 2.13), September 2023

License

Commercial or Open Source

Open Source

Apache Version 2; commercial licenses available

Open Source

dual-licence (Mozilla public license, Eclipse public license)

commercial

Open Source

Apache 2.0

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

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

Implementation language

Java

Erlang

Scala

Server operating systems

All OS with a Java VM

hosted

Linux
OS X
Windows

Data scheme

schema-free

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 DML and DDL statements

APIs and other access methods

JCache

JDBC
ODBC

RESTful HTTP/JSON API

JDBC
ODBC

Supported programming languages

Java

C#
Java
JavaScript
Objective-C
PHP
Ruby

Java
Python
R
Scala

Server-side scripts

Stored procedures

Java Stored Procedures and User-Defined Functions

View functions (Map-Reduce) in JavaScript

Triggers

yes

Cache Event Listeners

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

by using Terracotta Server

none

Sharding

yes, utilizing Spark Core

Replication methods

Methods for redundantly storing data on multiple nodes

yes

by using Terracotta Server

With clustering: 2 database servers on different computers operate on identical copies of a database

Multi-source replication
Source-replica replication

none

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)

Immediate Consistency

Eventual Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

yes

supports JTA and can work as an XA resource

ACID

atomic operations within a document possible

Concurrency

Support for concurrent manipulation of data

yes

yes, multi-version concurrency control (MVCC)

yes

Optimistic locking

yes

Durability

Support for making data persistent

yes

using a tiered cache-storage approach

yes

In-memory capabilities

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

yes

User concepts

Access control

fine grained access rights according to SQL-standard

Access rights for users can be defined per database

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