DBMS > Ehcache vs. Microsoft Azure Synapse Analytics vs. SAP IQ

System Properties Comparison Ehcache vs. Microsoft Azure Synapse Analytics vs. SAP IQ

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Editorial information provided by DB-Engines

Name

Description

A widely adopted Java cache with tiered storage options

Elastic, large scale data warehouse service leveraging the broad eco-system of SQL Server

Columnar RDBMS optimized for Big Data analytics

Primary database model

Key-value store

Relational DBMS

column-oriented

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

Score	5.23
Rank	#68	Overall
	#8	Key-value stores

Score	22.71
Rank	#30	Overall
	#18	Relational DBMS

Score	3.27
Rank	#96	Overall
	#50	Relational DBMS

Website

www.ehcache.org

azure.microsoft.com/services/synapse-analytics

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

Technical documentation

www.ehcache.org/documentation

docs.microsoft.com/azure/synapse-analytics

help.sap.com/docs/SAP_IQ

Developer

Terracotta Inc, owned by Software AG

Microsoft

SAP, formerly Sybase

Initial release

2009

2016

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

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

C++

Server operating systems

All OS with a Java VM

hosted

AIX
HP-UX
Linux
Solaris
Windows

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

ADO.NET
JDBC
ODBC

ADO.NET
JDBC
ODBC
RESTful HTTP API

Supported programming languages

Java

C#
Java
PHP

C
C#
C++
Java
Perl
PHP
Python
Ruby

Server-side scripts

Stored procedures

Transact SQL

yes

Triggers

yes

Cache Event Listeners

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

by using Terracotta Server

Sharding, horizontal partitioning

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

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)

Immediate Consistency

Foreign keys

Referential integrity

docs.microsoft.com/en-us/azure/synapse-analytics/sql-data-warehouse/sql-data-warehouse-table-constraints

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

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

fine grained access rights according to SQL-standard

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