DBMS > Amazon Redshift vs. Elasticsearch vs. H2GIS vs. MySQL vs. NCache

System Properties Comparison Amazon Redshift vs. Elasticsearch vs. H2GIS vs. MySQL vs. NCache

Editorial information provided by DB-Engines

Name

Description

Large scale data warehouse service for use with business intelligence tools

A distributed, RESTful modern search and analytics engine based on Apache Lucene

Elasticsearch lets you perform and combine many types of searches such as structured, unstructured, geo, and metric

Spatial extension of H2

Widely used open source RDBMS

Open-Source and Enterprise in-memory Key-Value Store

Primary database model

Key/Value like access via memcached API

Key-value store

Secondary database models

Document store
Spatial DBMS
Vector DBMS

Relational DBMS

Document store
Spatial DBMS

Document store
Search engine

Using distributed Lucene

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

Score	17.94
Rank	#34	Overall
	#21	Relational DBMS

Score	135.35
Rank	#7	Overall
	#1	Search engines

Score	0.00
Rank	#383	Overall
	#7	Spatial DBMS

Score	1083.74
Rank	#2	Overall
	#2	Relational DBMS

Score	0.94
Rank	#195	Overall
	#29	Key-value stores

Website

aws.amazon.com/redshift

www.elastic.co/elasticsearch

www.h2gis.org

www.mysql.com

www.alachisoft.com/ncache

Technical documentation

docs.aws.amazon.com/redshift

www.elastic.co/guide/en/elasticsearch/reference/current/index.html

www.h2gis.org/docs/home

dev.mysql.com/doc

www.alachisoft.com/resources/docs

Developer

Amazon (based on PostgreSQL)

Elastic

CNRS

Oracle

since 2010, originally MySQL AB, then Sun

Alachisoft

Initial release

2012

2010

2013

1995

2005

Current release

8.6, January 2023

8.4.0, April 2024

5.3.3, April 2024

License

Commercial or Open Source

commercial

Open Source

Elastic License

Open Source

LGPL 3.0

Open Source

GPL version 2. Commercial licenses with extended functionallity are available

Open Source

Enterprise Edition available

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

Java

C and C++

C#, .NET, .NET Core, Java

Server operating systems

hosted

All OS with a Java VM

FreeBSD
Linux
OS X
Solaris
Windows

Linux
Windows

Data scheme

yes

schema-free

Flexible type definitions. Once a type is defined, it is persistent

yes

schema-free

Typing

predefined data types such as float or date

yes

partial

Supported data types are Lists, Queues, Hashsets, Dictionary and Counter

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.

yes

Secondary indexes

restricted

yes

All search fields are automatically indexed

yes

SQL

Support of SQL

yes

does not fully support an SQL-standard

SQL-like query language

yes

with proprietary extensions

SQL-like query syntax and LINQ for searching the cache. Cache Synchronization with SQL Server using SQL dependency.

APIs and other access methods

JDBC
ODBC

Java API
RESTful HTTP/JSON API

ADO.NET
JDBC
ODBC
Proprietary native API

IDistributedCache
JCache
LINQ
Proprietary native API

Supported programming languages

All languages supporting JDBC/ODBC

.Net
Groovy
Community Contributed Clients
Java
JavaScript
Perl
PHP
Python
Ruby

Java

Ada
C
C#
C++
D
Delphi
Eiffel
Erlang
Haskell
Java
JavaScript (Node.js)
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl

.Net
.Net Core
C#
Java
JavaScript (Node.js)
Python
Scala

Server-side scripts

Stored procedures

user defined functions

in Python

yes

based on H2

yes

proprietary syntax

support for stored procedures with SQL-Server CLR

Triggers

yes

by using the 'percolation' feature

yes

Notifications

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

horizontal partitioning, sharding with MySQL Cluster or MySQL Fabric

yes

Replication methods

Methods for redundantly storing data on multiple nodes

yes

based on H2

Multi-source replication
Source-replica replication

yes, with selectable consistency level

MapReduce

Offers an API for user-defined Map/Reduce methods

ES-Hadoop Connector

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

Synchronous doc based replication. Get by ID may show delays up to 1 sec. Configurable write consistency: one, quorum, all

Immediate Consistency

Eventual Consistency
Immediate Consistency
Strong Eventual Consistency over WAN with Conflict Resolution using Bridge Topology

Foreign keys

Referential integrity

yes

informational only, not enforced by the system

yes

not for MyISAM storage engine

Transaction concepts

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

ACID

not for MyISAM storage engine

optimistic locking and pessimistic locking

Concurrency

Support for concurrent manipulation of data

yes

yes, multi-version concurrency control (MVCC)

yes

table locks or row locks depending on storage engine

yes

Durability

Support for making data persistent

yes

In-memory capabilities

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

yes

Memcached and Redis integration

yes

User concepts

Access control

fine grained access rights according to SQL-standard

yes

based on H2

Users with fine-grained authorization concept

no user groups or roles

Authentication to access the cache via Active Directory/LDAP (possible roles: user, administrator)

More information provided by the system vendor

Specific characteristics

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Competitive advantages

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Typical application scenarios

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Key customers

Bank of America, Citi, Natures Way, Charter Spectrum, Barclays, Henry Schein, GBM,...
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Market metrics

Market Leader in .NET Distributed Caching since 2005.
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Licensing and pricing models

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