DBMS > Ehcache vs. Google Cloud Bigtable vs. Hawkular Metrics vs. RDF4J

System Properties Comparison Ehcache vs. Google Cloud Bigtable vs. Hawkular Metrics vs. RDF4J

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Editorial information provided by DB-Engines

Name

Description

A widely adopted Java cache with tiered storage options

Google's NoSQL Big Data database service. It's the same database that powers many core Google services, including Search, Analytics, Maps, and Gmail.

Hawkular metrics is the metric storage of the Red Hat sponsored Hawkular monitoring system. It is based on Cassandra.

RDF4J is a Java framework for processing RDF data, supporting both memory-based and a disk-based storage.

Primary database model

Key-value store

Key-value store
Wide column store

Time Series DBMS

RDF store

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

Score	4.64
Rank	#68	Overall
	#8	Key-value stores

Score	3.15
Rank	#95	Overall
	#14	Key-value stores
	#8	Wide column stores

Score	0.08
Rank	#366	Overall
	#39	Time Series DBMS

Score	0.74
Rank	#222	Overall
	#9	RDF stores

Website

www.ehcache.org

cloud.google.com/bigtable

www.hawkular.org

rdf4j.org

Technical documentation

www.ehcache.org/documentation

cloud.google.com/bigtable/docs

www.hawkular.org/hawkular-metrics/docs/user-guide

rdf4j.org/documentation

Developer

Terracotta Inc, owned by Software AG

Google

Community supported by Red Hat

Since 2016 officially forked into an Eclipse project, former developer was Aduna Software.

Initial release

2009

2015

2014

2004

Current release

3.10.0, March 2022

License

Commercial or Open Source

Open Source

Apache Version 2; commercial licenses available

commercial

Open Source

Apache 2.0

Open Source

Eclipse Distribution License (EDL), v1.0.

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

Server operating systems

All OS with a Java VM

hosted

Linux
OS X
Windows

Linux
OS X
Unix
Windows

Data scheme

schema-free

yes

RDF Schemas

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

gRPC (using protocol buffers) API
HappyBase (Python library)
HBase compatible API (Java)

HTTP REST

Java API
RIO

RDF Input/Output
Sail API
SeRQL

Sesame RDF Query Language
Sesame REST HTTP Protocol
SPARQL

Supported programming languages

Java

C#
C++
Go
Java
JavaScript (Node.js)
Python

Go
Java
Python
Ruby

Java
PHP
Python

Server-side scripts

Stored procedures

yes

Triggers

yes

Cache Event Listeners

yes

via Hawkular Alerting

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

by using Terracotta Server

Sharding

based on Cassandra

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes

by using Terracotta Server

Internal replication in Colossus, and regional replication between two clusters in different zones

selectable replication factor

based on Cassandra

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 (for a single cluster), Eventual consistency (for two or more replicated clusters)

Eventual Consistency

based on Cassandra
Immediate Consistency

based on Cassandra

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

Atomic single-row operations

ACID

Isolation support depends on the API used

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

using a tiered cache-storage approach

yes

in-memory storage is supported as well

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)

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