DBMS > Amazon CloudSearch vs. BigObject vs. Sequoiadb

System Properties Comparison Amazon CloudSearch vs. BigObject vs. Sequoiadb

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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

Analytic DBMS for real-time computations and queries

NewSQL database with distributed OLTP and SQL

Primary database model

Search engine

Relational DBMS

a hierachical model (tree) can be imposed

Document store
Relational DBMS

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

Score	1.87
Rank	#140	Overall
	#12	Search engines

Score	0.13
Rank	#342	Overall
	#150	Relational DBMS

Score	0.48
Rank	#260	Overall
	#41	Document stores
	#121	Relational DBMS

Website

aws.amazon.com/cloudsearch

bigobject.io

www.sequoiadb.com

Technical documentation

docs.aws.amazon.com/cloudsearch

docs.bigobject.io

www.sequoiadb.com/en/index.php?m=Files&a=index

Developer

Amazon

BigObject, Inc.

Sequoiadb Ltd.

Initial release

2012

2015

2013

License

Commercial or Open Source

commercial

free community edition available

Open Source

Server: AGPL; Client: Apache V2

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

C++

Server operating systems

hosted

Linux

distributed as a docker-image
OS X

distributed as a docker-image (boot2docker)
Windows

distributed as a docker-image (boot2docker)

Linux

Data scheme

yes

schema-free

Typing

predefined data types such as float or date

yes

oid, date, timestamp, binary, regex

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

yes

SQL

Support of SQL

SQL-like DML and DDL statements

SQL-like query language

APIs and other access methods

HTTP API

fluentd
ODBC
RESTful HTTP API

proprietary protocol using JSON

Supported programming languages

.Net
C++
Java
PHP
Python

Server-side scripts

Stored procedures

Lua

JavaScript

Triggers

Partitioning methods

Methods for storing different data on different nodes

yes

automatic partitioning across Amazon Search Instance as required

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes

managed transparently by AWS

none

Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

none

Eventual Consistency

Foreign keys

Referential integrity

yes

automatically between fact table and dimension tables

Transaction concepts

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

Document is locked during a transaction

Concurrency

Support for concurrent manipulation of data

yes

Read/write lock on objects (tables, trees)

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

simple password-based access control

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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

show all

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

Is Amazon CloudSearch superior to do-it-yourself search tools?
24 January 2014, TechTarget

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

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

provided by Google News

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