DBMS > Amazon CloudSearch vs. Amazon Redshift vs. H2 vs. RocksDB

System Properties Comparison Amazon CloudSearch vs. Amazon Redshift vs. H2 vs. RocksDB

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Editorial information provided by DB-Engines

Name

Description

A hosted search engine service by Amazon with the data stored in Amazons cloud

Large scale data warehouse service for use with business intelligence tools

Full-featured RDBMS with a small footprint, either embedded into a Java application or used as a database server.

Embeddable persistent key-value store optimized for fast storage (flash and RAM)

Primary database model

Search engine

Relational DBMS

Key-value store

Secondary database models

Spatial DBMS

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

Score	1.86
Rank	#133	Overall
	#12	Search engines

Score	15.25
Rank	#38	Overall
	#23	Relational DBMS

Score	7.57
Rank	#47	Overall
	#30	Relational DBMS

Score	2.84
Rank	#97	Overall
	#16	Key-value stores

Website

aws.amazon.com/cloudsearch

aws.amazon.com/redshift

www.h2database.com

rocksdb.org

Technical documentation

docs.aws.amazon.com/cloudsearch

docs.aws.amazon.com/redshift

www.h2database.com/html/main.html

github.com/facebook/rocksdb/wiki

Developer

Amazon

Amazon (based on PostgreSQL)

Thomas Mueller

Facebook, Inc.

Initial release

2012

2005

2013

Current release

2.2.220, July 2023

9.4.0, June 2024

License

Commercial or Open Source

commercial

Open Source

dual-licence (Mozilla public license, Eclipse public license)

Open Source

BSD

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

hosted

All OS with a Java VM

Linux

Data scheme

yes

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.

Secondary indexes

yes

all search fields are automatically indexed

restricted

yes

SQL

Support of SQL

yes

does not fully support an SQL-standard

yes

APIs and other access methods

HTTP API

JDBC
ODBC

C++ API
Java API

Supported programming languages

All languages supporting JDBC/ODBC

Java

C
C++
Go
Java
Perl
Python
Ruby

Server-side scripts

Stored procedures

user defined functions

in Python

Java Stored Procedures and User-Defined Functions

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

yes

automatic partitioning across Amazon Search Instance as required

Sharding

none

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

yes

managed transparently by AWS

yes

With clustering: 2 database servers on different computers operate on identical copies of a database

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Foreign keys

Referential integrity

yes

informational only, not enforced by the system

yes

Transaction concepts

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

ACID

yes

Concurrency

Support for concurrent manipulation of data

yes

yes, multi-version concurrency control (MVCC)

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

User concepts

Access control

authentication via encrypted signatures

fine grained access rights according to SQL-standard

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