DBMS > Amazon CloudSearch vs. BigObject vs. Google Cloud Bigtable vs. OrigoDB

System Properties Comparison Amazon CloudSearch vs. BigObject vs. Google Cloud Bigtable vs. OrigoDB

Please select another system to include it in the comparison.

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

Google's NoSQL Big Data database service. It's the same database that powers many core Google services, including Search, Analytics, Maps, and Gmail.

A fully ACID in-memory object graph database

Primary database model

Search engine

Relational DBMS

a hierachical model (tree) can be imposed

Key-value store
Wide column store

Document store
Object oriented DBMS

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

Score	1.85
Rank	#137	Overall
	#12	Search engines

Score	0.13
Rank	#333	Overall
	#147	Relational DBMS

Score	3.26
Rank	#92	Overall
	#13	Key-value stores
	#8	Wide column stores

Score	0.00
Rank	#383	Overall
	#53	Document stores
	#20	Object oriented DBMS

Website

aws.amazon.com/cloudsearch

bigobject.io

cloud.google.com/bigtable

origodb.com

Technical documentation

docs.aws.amazon.com/cloudsearch

docs.bigobject.io

cloud.google.com/bigtable/docs

origodb.com/docs

Developer

Amazon

BigObject, Inc.

Google

Robert Friberg et al

Initial release

2012

2015

2009

under the name LiveDB

License

Commercial or Open Source

commercial

free community edition available

commercial

Open Source

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

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)

hosted

Linux
Windows

Data scheme

yes

schema-free

yes

Typing

predefined data types such as float or date

yes

User defined using .NET types and collections

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.

can be achieved using .NET

Secondary indexes

yes

all search fields are automatically indexed

yes

SQL

Support of SQL

SQL-like DML and DDL statements

APIs and other access methods

HTTP API

fluentd
ODBC
RESTful HTTP API

gRPC (using protocol buffers) API
HappyBase (Python library)
HBase compatible API (Java)

.NET Client API
HTTP API
LINQ

Supported programming languages

C#
C++
Go
Java
JavaScript (Node.js)
Python

.Net

Server-side scripts

Stored procedures

Lua

yes

Triggers

yes

Domain Events

Partitioning methods

Methods for storing different data on different nodes

yes

automatic partitioning across Amazon Search Instance as required

none

Sharding

horizontal partitioning

client side managed; servers are not synchronized

Replication methods

Methods for redundantly storing data on multiple nodes

yes

managed transparently by AWS

none

Internal replication in Colossus, and regional replication between two clusters in different zones

Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

none

Immediate consistency (for a single cluster), Eventual consistency (for two or more replicated clusters)

Foreign keys

Referential integrity

yes

automatically between fact table and dimension tables

depending on model

Transaction concepts

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

Atomic single-row operations

ACID

Concurrency

Support for concurrent manipulation of data

yes

Read/write lock on objects (tables, trees)

yes

Durability

Support for making data persistent

yes

Write ahead log

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

Access rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)

Role based authorization

More information provided by the system vendor

We invite representatives of system vendors to contact us for updating and extending the system information,
and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

Related products and services

We invite representatives of vendors of related products to contact us for presenting information about their offerings here.

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

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

Google's AI-First Strategy Brings Vector Support To Cloud Databases
1 March 2024, Forbes

Google Introduces Autoscaling for Cloud Bigtable for Optimizing Costs
31 January 2022, InfoQ.com

Google scales up Cloud Bigtable NoSQL database
27 January 2022, TechTarget

Google introduces Cloud Bigtable managed NoSQL database to process data at scale
6 May 2015, VentureBeat

Google Launches Cloud Bigtable, A Highly Scalable And Performant NoSQL Database
6 May 2015, TechCrunch

provided by Google News

Share this page