DBMS > Ehcache vs. IBM Db2 warehouse vs. Lovefield vs. Stardog vs. Yanza

System Properties Comparison Ehcache vs. IBM Db2 warehouse vs. Lovefield vs. Stardog vs. Yanza

Editorial information provided by DB-Engines

Name

Yanza seems to be discontinued. Therefore it is excluded from the DB-Engines Ranking.

Description

A widely adopted Java cache with tiered storage options

Cloud-based data warehousing service

Embeddable relational database for web apps written in pure JavaScript

Enterprise Knowledge Graph platform and graph DBMS with high availability, high performance reasoning, and virtualization

Time Series DBMS for IoT Applications

Primary database model

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

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

Score	1.37
Rank	#160	Overall
	#74	Relational DBMS

Score	0.33
Rank	#286	Overall
	#131	Relational DBMS

Score	2.07
Rank	#122	Overall
	#11	Graph DBMS
	#6	RDF stores

Website

www.ehcache.org

www.ibm.com/products/db2/warehouse

google.github.io/lovefield

www.stardog.com

yanza.com

Technical documentation

www.ehcache.org/documentation

github.com/google/lovefield/blob/master/docs/spec_index.md

docs.stardog.com

Developer

Terracotta Inc, owned by Software AG

IBM

Google

Stardog-Union

Yanza

Initial release

2009

2014

2010

2015

Current release

3.10.0, March 2022

2.1.12, February 2017

7.3.0, May 2020

License

Commercial or Open Source

Open Source

Apache Version 2; commercial licenses available

commercial

Open Source

Apache 2.0

commercial

60-day fully-featured trial license; 1-year fully-featured non-commercial use license for academics/students

commercial

free version available

Cloud-based only

Only available as a cloud service

yes

but mainly used as a service provided by Yanza

DBaaS offerings (sponsored links)

Database as a Service

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

Implementation language

Java

JavaScript

Java

Server operating systems

All OS with a Java VM

hosted

server-less, requires a JavaScript environment (browser, Node.js)

tested with Chrome, Firefox, IE, Safari

Linux
macOS
Windows

Windows

Data scheme

schema-free

yes

schema-free and OWL/RDFS-schema support

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.

Import/export of XML data possible

Secondary indexes

yes

supports real-time indexing in full-text and geospatial

SQL

Support of SQL

yes

SQL-like query language

via JavaScript builder pattern

Yes, compatible with all major SQL variants through dedicated BI/SQL Server

APIs and other access methods

JCache

.NET Client API
JDBC
ODBC
OLE DB

GraphQL query language
HTTP API
Jena RDF API
OWL
RDF4J API
Sesame REST HTTP Protocol
SNARL
SPARQL
Spring Data
Stardog Studio
TinkerPop 3

HTTP API

Supported programming languages

Java

Java
JavaScript (Node.js)
Perl
PHP
Python
R
Ruby

JavaScript

.Net
Clojure
Groovy
Java
JavaScript
Python
Ruby

any language that supports HTTP calls

Server-side scripts

Stored procedures

PL/SQL, SQL PL

user defined functions and aggregates, HTTP Server extensions in Java

Triggers

yes

Cache Event Listeners

yes

Using read-only observers

yes

via event handlers

yes

Timer and event based

Partitioning methods

Methods for storing different data on different nodes

Sharding

by using Terracotta Server

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes

by using Terracotta Server

yes

none

Multi-source replication in HA-Cluster

none

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Tunable Consistency (Strong, Eventual, Weak)

Immediate Consistency

Immediate Consistency in HA-Cluster

Immediate Consistency

Foreign keys

Referential integrity

yes

relationships in graphs

Transaction concepts

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

yes

supports JTA and can work as an XA resource

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

using a tiered cache-storage approach

yes

yes, by using IndexedDB or the cloud service Firebase Realtime Database

yes

In-memory capabilities

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

yes

using MemoryDB

yes

User concepts

Access control

fine grained access rights according to SQL-standard

Access rights for users and roles

More information provided by the system vendor

We invite representatives of system vendors to contact us for updating and extending the system information,
and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

Related products and services

We invite representatives of vendors of related products to contact us for presenting information about their offerings here.

More resources

Recent citations in the news

Scaling Australia's Most Popular Online News Sites with Ehcache
6 December 2010, InfoQ.com

Atlassian asks customers to patch critical Jira vulnerability
22 July 2021, BleepingComputer

Critical Jira Flaw in Atlassian Could Lead to RCE
22 July 2021, Threatpost

DZone Coding Java JBoss 5 to 7 in 11 steps
9 January 2014, dzone.com

provided by Google News

Announcing the deprecation of prior generation Db2 Warehouse plans on AWS
16 October 2023, ibm.com

Introducing the next generation of Db2 Warehouse: Our cost-effective, cloud-native data warehouse built for always-on ...
11 July 2023, ibm.com

Data Mining in Db2 Warehouse: the basics
23 June 2020, Towards Data Science

Db2 Warehouse delivers 4x faster query performance than previously, while cutting storage costs by 34x
11 July 2023, ibm.com

Top 7 Cloud Data Warehouse Companies
31 May 2023, Datamation

provided by Google News

Share this page