DBMS > Ehcache vs. Graph Engine vs. Heroic vs. OrigoDB vs. SAP IQ

System Properties Comparison Ehcache vs. Graph Engine vs. Heroic vs. OrigoDB vs. SAP IQ

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

Time Series DBMS built at Spotify based on Cassandra or Google Cloud Bigtable, and ElasticSearch

A fully ACID in-memory object graph database

Columnar RDBMS optimized for Big Data analytics

Primary database model

Key-value store

Graph DBMS
Key-value store

Time Series DBMS

Document store
Object oriented DBMS

Relational DBMS

column-oriented

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	0.51
Rank	#255	Overall
	#21	Time Series DBMS

Score	0.00
Rank	#383	Overall
	#53	Document stores
	#20	Object oriented DBMS

Score	2.75
Rank	#104	Overall
	#53	Relational DBMS

Website

www.ehcache.org

www.graphengine.io

github.com/spotify/heroic

origodb.com

www.sap.com/products/technology-platform/sybase-iq-big-data-management.html

Technical documentation

www.ehcache.org/documentation

www.graphengine.io/docs/manual

spotify.github.io/heroic

origodb.com/docs

help.sap.com/docs/SAP_IQ

Developer

Terracotta Inc, owned by Software AG

Microsoft

Spotify

Robert Friberg et al

SAP, formerly Sybase

Initial release

2009

2010

2014

2009

under the name LiveDB

1994

Current release

3.10.0, March 2022

16.1 SPS04, April 2019

License

Commercial or Open Source

Open Source

Apache Version 2; commercial licenses available

Open Source

MIT License

Open Source

Apache 2.0

Open Source

commercial

Cloud-based only

Only available as a cloud 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

Java

Server operating systems

All OS with a Java VM

.NET

Linux
Windows

AIX
HP-UX
Linux
Solaris
Windows

Data scheme

schema-free

yes

schema-free

yes

Typing

predefined data types such as float or date

yes

User defined using .NET types and collections

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.

can be achieved using .NET

Secondary indexes

yes

via Elasticsearch

yes

SQL

Support of SQL

yes

APIs and other access methods

JCache

RESTful HTTP API

HQL (Heroic Query Language, a JSON-based language)
HTTP API

.NET Client API
HTTP API
LINQ

ADO.NET
JDBC
ODBC
RESTful HTTP API

Supported programming languages

Java

C#
C++
F#
Visual Basic

.Net

C
C#
C++
Java
Perl
PHP
Python
Ruby

Server-side scripts

Stored procedures

yes

Triggers

yes

Cache Event Listeners

yes

Domain Events

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

by using Terracotta Server

horizontal partitioning

Sharding

horizontal partitioning

client side managed; servers are not synchronized

shared disk or shared nothing architectures with SAP IQ Multiplexer

Replication methods

Methods for redundantly storing data on multiple nodes

yes

by using Terracotta Server

yes

Source-replica replication

SAP/Sybase Replication Server

MapReduce

Offers an API for user-defined Map/Reduce methods

Hadoop integration

Consistency concepts

Methods to ensure consistency in a distributed system

Tunable Consistency (Strong, Eventual, Weak)

Eventual Consistency
Immediate Consistency

Immediate Consistency

Foreign keys

Referential integrity

depending on model

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

Write ahead log

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

Role based authorization

fine grained access rights according to SQL-standard

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