DBMS > Ehcache vs. Graph Engine vs. SAP HANA

System Properties Comparison Ehcache vs. Graph Engine vs. SAP HANA

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Editorial information provided by DB-Engines

Name

Description

A widely adopted Java cache with tiered storage options

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

In-memory, column based data store. Available as appliance or cloud service

Primary database model

Key-value store

Graph DBMS
Key-value store

Relational DBMS

Secondary database models

Document store
Graph DBMS

with SAP Hana, Enterprise Edition
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	0.61
Rank	#240	Overall
	#21	Graph DBMS
	#35	Key-value stores

Score	44.69
Rank	#22	Overall
	#16	Relational DBMS

Website

www.ehcache.org

www.graphengine.io

www.sap.com/products/hana.html

Technical documentation

www.ehcache.org/documentation

www.graphengine.io/docs/manual

help.sap.com/hana

Developer

Terracotta Inc, owned by Software AG

Microsoft

SAP

Initial release

2009

2010

Current release

3.10.0, March 2022

2.0 SPS07 (April 4, 2023), April 2023

License

Commercial or Open Source

Open Source

Apache Version 2; commercial licenses available

Open Source

MIT License

commercial

Cloud-based only

Only available as a cloud service

also available as a cloud based service

DBaaS offerings (sponsored links)

Database as a Service

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

Implementation language

Java

.NET and C

Server operating systems

All OS with a Java VM

.NET

Appliance or cloud-service

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

yes

APIs and other access methods

JCache

RESTful HTTP API

JDBC
ODBC

Supported programming languages

Java

C#
C++
F#
Visual Basic

Server-side scripts

Stored procedures

yes

SQLScript, R

Triggers

yes

Cache Event Listeners

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

by using Terracotta Server

horizontal partitioning

yes

Replication methods

Methods for redundantly storing data on multiple nodes

yes

by using Terracotta Server

yes

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

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

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

using a tiered cache-storage approach

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

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

yes

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