DBMS > Ehcache vs. Google Cloud Spanner vs. H2 vs. IBM Cloudant

System Properties Comparison Ehcache vs. Google Cloud Spanner vs. H2 vs. IBM Cloudant

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Editorial information provided by DB-Engines

Name

Description

A widely adopted Java cache with tiered storage options

A horizontally scalable, globally consistent, relational database service. It is the externalization of the core Google database that runs the biggest aspects of Google, like Ads and Google Play.

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

Primary database model

Key-value store

Relational DBMS

Document store

Secondary database models

Spatial DBMS

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

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

Score	2.89
Rank	#103	Overall
	#52	Relational DBMS

Score	8.13
Rank	#49	Overall
	#31	Relational DBMS

Score	2.68
Rank	#106	Overall
	#20	Document stores

Website

www.ehcache.org

cloud.google.com/spanner

www.h2database.com

www.ibm.com/products/cloudant

Technical documentation

www.ehcache.org/documentation

cloud.google.com/spanner/docs

www.h2database.com/html/main.html

cloud.ibm.com/docs/Cloudant

Developer

Terracotta Inc, owned by Software AG

Google

Thomas Mueller

IBM, Apache Software Foundation

IBM acquired Cloudant in February 2014

Initial release

2009

2017

2005

2010

Current release

3.10.0, March 2022

2.2.220, July 2023

License

Commercial or Open Source

Open Source

Apache Version 2; commercial licenses available

commercial

Open Source

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

commercial

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

Server operating systems

All OS with a Java VM

hosted

All OS with a Java VM

hosted

Data scheme

schema-free

yes

schema-free

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

Query statements complying to ANSI 2011

yes

APIs and other access methods

JCache

gRPC (using protocol buffers) API
JDBC

At present, JDBC supports read-only queries. No support for DDL or DML statements.
RESTful HTTP API

JDBC
ODBC

RESTful HTTP/JSON API

Supported programming languages

Java

Go
Java
JavaScript (Node.js)
Python

Java

C#
Java
JavaScript
Objective-C
PHP
Ruby

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

Sharding

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes

by using Terracotta Server

Multi-source replication with 3 replicas for regional instances.

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

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

using Google Cloud Dataflow

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

by using interleaved tables, this features focuses more on performance improvements than on 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

Strict serializable isolation

ACID

atomic operations within a document possible

Concurrency

Support for concurrent manipulation of data

yes

yes, multi-version concurrency control (MVCC)

yes

Optimistic locking

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

Access rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)

fine grained access rights according to SQL-standard

Access rights for users can be defined per database

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