DBMS > Amazon CloudSearch vs. Blueflood vs. EsgynDB vs. Oracle Berkeley DB

System Properties Comparison Amazon CloudSearch vs. Blueflood vs. EsgynDB vs. Oracle Berkeley DB

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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

Scalable TimeSeries DBMS based on Cassandra

Enterprise-class SQL-on-Hadoop solution, powered by Apache Trafodion

Widely used in-process key-value store

Primary database model

supports sorted and unsorted key sets
Native XML DBMS

in the Oracle Berkeley DB XML version

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

Score	1.85
Rank	#137	Overall
	#12	Search engines

Score	0.06
Rank	#353	Overall
	#34	Time Series DBMS

Score	0.16
Rank	#329	Overall
	#146	Relational DBMS

Score	2.21
Rank	#117	Overall
	#20	Key-value stores
	#3	Native XML DBMS

Website

aws.amazon.com/cloudsearch

blueflood.io

www.esgyn.cn

www.oracle.com/database/technologies/related/berkeleydb.html

Technical documentation

docs.aws.amazon.com/cloudsearch

github.com/rax-maas/blueflood/wiki

docs.oracle.com/cd/E17076_05/html/index.html

Developer

Amazon

Rackspace

Esgyn

Oracle

originally developed by Sleepycat, which was acquired by Oracle

Initial release

2012

2013

2015

1994

Current release

18.1.40, May 2020

License

Commercial or Open Source

commercial

Open Source

Apache 2.0

commercial

Open Source

commercial license available

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++, Java

C, Java, C++ (depending on the Berkeley DB edition)

Server operating systems

hosted

Linux
OS X

Linux

AIX
Android
FreeBSD
iOS
Linux
OS X
Solaris
VxWorks
Windows

Data scheme

yes

predefined 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.

yes

only with the Berkeley DB XML edition

Secondary indexes

yes

all search fields are automatically indexed

yes

SQL

Support of SQL

yes

SQL interfaced based on SQLite is available

APIs and other access methods

HTTP API

HTTP REST

ADO.NET
JDBC
ODBC

Supported programming languages

All languages supporting JDBC/ODBC/ADO.Net

.Net

Figaro is a .Net framework assembly that extends Berkeley DB XML into an embeddable database engine for .NET
others

Third-party libraries to manipulate Berkeley DB files are available for many languages
C
C#
C++
Java
JavaScript (Node.js)

3rd party binding
Perl
Python
Tcl

Server-side scripts

Stored procedures

Java Stored Procedures

Triggers

yes

only for the SQL API

Partitioning methods

Methods for storing different data on different nodes

yes

automatic partitioning across Amazon Search Instance as required

Sharding

based on Cassandra

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes

managed transparently by AWS

selectable replication factor

based on Cassandra

Multi-source replication between multi datacenters

Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

based on Cassandra
Immediate Consistency

based on Cassandra

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

Concurrency

Support for concurrent manipulation of data

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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More resources

DB-Engines blog posts

Amazon - the rising star in the DBMS market
3 August 2015, Matthias Gelbmann

The DB-Engines ranking includes now search engines
4 February 2013, Paul Andlinger

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Recent citations in the news

Amazon CloudSearch – Start Searching in One Hour for Less Than $100 / Month | Amazon Web Services
12 April 2012, AWS Blog

Amazon CloudSearch – Even Better Searching for Less Than $100/Month | Amazon Web Services
24 March 2014, AWS Blog

Amazon Takes On Google And Microsoft With CloudSearch
16 April 2012, Forbes

AWS, Microsoft and Google should retire these cloud services
2 June 2020, TechTarget

Searching CloudTrail Logs Easily with Amazon CloudSearch | AWS Startups Blog
21 October 2014, AWS Blog

provided by Google News

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2 September 2019, CNX Software

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26 May 2021, EurekAlert

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18 August 2020, Berkman Klein Center

Database Trends Report: SQL Beats NoSQL, MySQL Most Popular -- ADTmag
5 March 2019, ADT Magazine

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26 January 2019, Towards Data Science

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9 May 2014, The Merkle News

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