Open Source Search Applications

The
Case
for
Lucene/Solr:

A
Manager’s
Guide

to
Real
World

Open
Source

Search
Applications

By
Lucid
Imagination

Abstract

In
today’s
information-‐driven
environment,
search
is
a
critical
solution
to
problems
when
it
slashes

the
time
and
effort
separating
end
users
from
the
data
they
value.
Search
spans
the
range
of

business
models
and
use
cases—from
driving
direct
customer
sales,
to
analytics
and
business

intelligence,
employee
productivity,
and
reduced
administrative
overhead.
Making
the
best
use
of

search
requires
two
perspectives:
both
a
look
at
the
business
requirements
for
a
search
application

and
a
view
to
new
business
opportunities
created
by
using
search
to
leverage
the
organization’s

content
resources.

Thousands
of
organizations
across
different
sectors
and
business
models
have
harnessed
Apache

Lucene/Solr
to
search
their
rapidly
growing
and
diversifying
content
resources.
Underlying
this

broad
adoption
is
the
extraordinary
power,
scalability,
and
versatility
of
open
source
search

technologies.

This
paper
provides
an
overview
of
both
the
requirements
and
the
opportunities
for
search

applications.
It
then
explores
how
real
world
organizations
are
successfully
using
Lucene/Solr

search
applications
to
meet
those
opportunities,
presenting
how
the
technology
is
used
for
specific

business
models
and
use
cases
across
industries.
In
addition,
it
offers
a
baseline
for
setting
search

requirements
that
managers
and
architects
can
use
to
adopt
Lucene/Solr,
and
adapt
this
open

source
search
technology
to
the
unique
needs
of
their
business.

©
2010,
Lucid
Imagination

The Case for Lucene/Solr: Real World Search Applications
A Lucid Imagination White Paper • January 2010
Page ii

Table
of
Contents

Introduction ............................................................................................................................................................... 1

Understanding
Search
Opportunities
and
Requirements ...................................................................... 2

What
Data
and
Documents
Are
You
Searching? ................................................................................ 3

Who
Needs
the
Results
and
Why? ........................................................................................................... 3

Where
Is
Search
Integrated
with
IT
Infrastructure? ....................................................................... 5

How
Is
the
Search
Interface
Presented
to
the
User?........................................................................ 5

The
Real
World:
Applications
and
Case
Studies ......................................................................................... 7

Yellow
Pages,
Local
Search,
and
Searching
Classifieds........................................................................ 8

Media .......................................................................................................................................................................10

E-‐commerce..........................................................................................................................................................12

Job
and
Career
Sites ..........................................................................................................................................14

Libraries,
Archives,
and
Museums
(LAMs)
Search ..............................................................................16

Social
Media
Search...........................................................................................................................................18

Enterprise
(Intranet)
Search.........................................................................................................................21

Business
Use
Case
Matrix ...................................................................................................................................23

Appendix:
Lucene/Solr
Features
and
Benefits..........................................................................................24

Page iii

Introduction
As
fast
as
companies,
communities,
and
consumers
produce
data—about
each
other,
products,

opinions,
research,
and
everything
else
imaginable—they
need
faster,
more
versatile
search

capabilities
to
find
the
information
they
need
to
create
opportunities
for
competitive
advantage.
In

today’s
information-‐driven
environment,
search
addresses
the
critical
problems
created
by
the

explosive
growth
of
content
by
slashing
the
time
and
effort
users
expend
in
finding
data
they
value.

Search
spans
the
range
of
business
models
and
use
cases:
from
driving
direct
customer
sales,
to

analytics
and
business
intelligence,
employee
productivity,
and
reduced
administrative
overhead.

Apache
Lucene/Solr1
open
source
search
technology
has
been
implemented
across
the
broadest

range
of
applications
and
business
models—and
likely
in
ways
that
can
fit
the
needs
of
your

organization.
In
successful
operation
today
at
thousands
of
enterprises,
Lucene/Solr
technology

scales
from
tens
of
thousands
to
hundreds
and
billions
of
documents;
searches
data
that
is

structured,
unstructured,
and
in
combination;
data
inside
and
outside
the
firewall;
and
ranges
in

use
from
a
simple
website
search
box
through
sophisticated
faceted
navigation.
It
addresses
equally

diverse
business
processes
and
mission
critical
applications.
Across
the
spectrum,
Lucene/Solr

helps
users
find,
make
sense
of,
and
act
upon
information
quickly
and
efficiently.

In
this
white
paper,
we’ll
review
real-‐world
case
studies
for
Lucene/Solr
functionality
across

business
sectors
to
demonstrate
its
versatility
and
varied
applicability.
The
diversity
of
examples

provides
strong
evidence
of
Lucene/Solr’s
flexibility
and
power
as
a
search
technology.
The

examples
also
attest
to
the
innovation
and
transparency
inherent
to
the
open
source
development

model.
Our
focus
is
on
familiarizing
the
audience
of
business
managers
and
application
owners
with

existing
Lucene/Solr
applications;
the
substantial
technical
advantages
to
developers
are
covered

elsewhere.

1
Lucene and Solr are complementary technologies that offer very similar underlying capabilities; Solr is the Lucene
Search Server. Since Lucene serves as the core of Solr’s search capabilities, this paper refers to the two as
Lucene/Solr. For more information, see the Appendix.

Page 1

We’ll
first
survey
the
key
requirements
and
business
use
cases
of
search
and
then
look
at
where

they
are
built
into
search
applications.
Our
objective
is
to
provide
business
managers
and

application
owners
with
a
broad
perspective
on
how
Lucene/Solr
search
technology
is
used
to
build

solutions
to
compelling
business
problems.
In
the
Appendix,
we
provide
an
overview
of

Lucene/Solr’s
key
features
and
benefits,
with
a
basic
outline
of
the
capabilities
offered
to
meet
the

broadest
range
of
business
needs.

Understanding Search
Opportunities and Requirements
Search
technology
has
come
a
long
way
from
its
roots
in
matching
keywords
with
appearance
in

documents
and
obtaining
undifferentiated
results.
Search
today
empowers
users
by
delivering

actionable
information
quickly
and
efficiently,
across
multiple,
diverse
sources
of
data.
The

business
use
cases
range
from
executing
mission
critical
commercial
transactions
(e.g.,
e-‐commerce

sites)
to
unlocking
employee
and
end-‐user
productivity
in
the
search
for
a
single
relevant
document

(e.g.,
enterprise
search).

Given
the
breadth
of
capability
of
the
problem
domain,
it’s
useful
to
look
at
search
and
ask
two

fundamental
questions:
“How
it
can
it
solve
my
business
problems?”
and
“What
new
business

opportunities
can
search
solve
for?”

In
considering
how
search
technology
solves
business
problems,
it
is
useful
to
start
with
an

elucidation
of
the
requirements
you’ll
need
to
consider
for
your
search
application.
At
the
same

time,
be
sure
to
look
more
broadly
at
the
capabilities
that
Lucene/Solr
offers,
as
it
can
help
open
up

new
frontiers
for
incorporating
search
and
leveraging
more
value
from
data
repositories.

Starting
with
some
basic
questions—what,
who,
how,
and
where—you
can
clarify
the
high-‐level

business
requirements
specific
to
your
business
needs,
which
in
turn
allow
you
to
make
the
best

decisions
for
your
search
application.
The
process
of
looking
at
the
fundamentals
also
raises
new

questions
about
how
and
where
the
search
technology
offered
by
Lucene
and
Solr
can
create
new

business
opportunities.

Let’s
look
at
four
fundamental
questions
you
should
address
in
understanding
search
opportunities

and
requirements:

• What
data
and
documents
are
you
searching?

• Who
needs
the
results
and
why?

• Where
is
search
integrated
with
IT
Infrastructure?

• How
is
the
search
interface
presented
to
the
user?

Page 2

What Data and Documents Are You Searching?
Business
today
is
driven
more
than
ever
by
the
end-‐users’
creation
and
consumption
of
real-‐time

information.
A
key
differentiating
capability
of
search
technology
is
ingesting
a
broad
range
of

content
types
and
processing
large
collections
of
diverse
data
in
real
time
in
order
to
deliver

actionable
information.
Two
aspects
to
consider:

• Types
of
Content

Content
comes
in
multiple
formats:
HTML
pages,
XML
files,
PDFs,
images,
PowerPoint

presentations,
Excel
spreadsheets,
Word
documents,
log
files,
multimedia
content,
and

more.
Content
resides
in
various
repositories,
including
databases,
file
servers,
content

management
systems,
archiving
systems,
collaboration
applications,
and
employee

desktops
and
laptops.
Search
technology
must
be
able
to
locate,
organize,
and
aggregate

data
whatever
its
form
or
location.

• Frequency
of
Updating
Content

Organizations
update
content
at
varying
intervals,
driven
by
differing
business
processes

and
models—social
media
or
news
applications
have
real-‐time
content
need,
whereas
an
e-‐
commerce
application
might
re-‐index
in
response
to
new
inventory
on
a
batch
basis
and
a

research
institution
might
add
to
its
collection
less
often
still.
Search
applications
need
to
be

adaptable
to
the
differences
in
content
change
frequency.

Who Needs the Results and Why?
Business
search
puts
a
high
priority
on
end
user
experience
and
results
in
which
the
searched

content
is
tuned
to
the
unique
needs
of
each
user.
Because,
after
all,
the
human
dimension—the

usefulness
of
results
and
the
efficacy
of
interaction—is
the
acid
test
of
a
search
application.
Internet

search
applications
like
Google,
Yahoo,
and
Bing
are
now
common
and
mature.
They
have
raised

user
expectations
about
key
qualities
of
the
search
experience...but
they
solve
a
very
different

problem.

While
Internet
searches
can
produce
millions
of
results
in
milliseconds,
they
rely
on
measures
like

website
popularity
or
URLs
and
domain
names—not
relevant
and
not
generally
applicable
to

purpose-‐built
applications
for
businesses.
What’s
more,
they
rely
on
generalizing
relevancy
for
a

global
population
of
all
Internet
users,
without
being
tied
to
business
rules,
or
business
process

logic,
or
the
opportunity
cost
of
improved
precision
for
a
specific
set
of
data
or
search
users.

Business
search
applications
cannot
rely
on
such
brute
force
coarse
approaches
to
tune
their

results.
They
need
far
more
control
and
precision.
They
have
to
be
able
to
deliver
highly
useful

results
while
matching,
if
not
exceeding,
the
levels
of
user
experience
that
people
have
come
to

expect
by
virtue
of
their
daily
interactions
with
commercial
search
engines.
Key
points
of

consideration
from
a
business
perspective
are:

Page 3

• Relevance

Relevance
is
entirely
a
factor
of
the
goals
of
the
search
application’s
users.
The
application

must
have
the
mechanisms
to
recognize
the
subjective
needs
of
users
and
tune
results

accordingly.
It
must
also
provide
easier
ways
to
narrow
search
criteria
without
requiring

users
to
come
up
with
perfect
query
terms.
Flexibility
for
drilling
deeper
will
make
results

richer
and
valuable.
Mechanisms
to
apply
filters,
proximity
values,
and
sorting
parameters

to
narrow
search
scope
can
also
lead
to
a
richer
set
of
more
useful
results,
with
less
time

and
effort.

• Cost
of
Relevance

As
business
goals
are
driven
by
revenue
opportunities
and
cost
savings,
it
is
critical
to
tie

relevance
to
the
economics
of
the
business.
For
example,
a
public-‐facing
retail
site
should

focus
on
matching
merchandise
to
search,
site
stickiness,
and
customer
loyalty.
It
requires

search
technology
that
streamlines
and
simplifies
the
shopping
experience
with
relevant

results
directly
contributing
to
sales
revenue.
For
knowledge
workers,
internal
search

applications
should
help
make
employees
more
productive
by
reducing
the
amount
of
time

and
effort
to
find
documents
they
need
to
do
their
jobs.
Multiple
studies
show
that

information
workers
can
spend
20–30%
of
their
time
searching
for
information.

• Precision
Ranking

Result
accuracy,
sorted
by
attributes
like
relevance,
date,
field,
or
any
document
property

feature,
makes
the
search
process
better.
End
users
generally
abandon
a
search
before

tackling
the
fine
points
of
Boolean
logic
or
scrolling
for
a
result
buried
too
far
down.

• Query
Response
Speed

Today,
5–7
seconds
is
the
typical
threshold
for
end-‐user
patience.
Too
much
wait
time
for

search
results
frustrates
users,
and
causes
them
to
abandon
pages.
Fast,
relevant
results

cannot
be
limited
by
search
technology
hamstrung
by
data
influx
or
query
overload.
Query

response
time
should
also
work
hand-‐in-‐hand
with
the
refinement
of
multiple
search

attributes,
so
that
increasingly
complex
queries
do
not
extract
a
performance
penalty.

Page 4

Where Is Search Integrated with IT Infrastructure?
Useful,
valuable
search
technology
rarely
exists
in
isolation.
Searched
data
is
transformed
into

actionable
information
when
it
is
integrated
with
the
organization’s
information
infrastructure:

business
process
to
business
intelligence
to
content
management
systems.
A
robust
search

technology
must
be
customizable
to
integrate
with
the
existing
systems
seamlessly.

• Application
Integration

A
key
requirement
for
a
search
application
is
its
extensibility
for
integration
with
existing

infrastructure
and
applications
like
content
management
systems,
databases,
and
the
full

range
of
business
processes
and
applications.
It
should
have
interfaces
that
support

ingestion
of
data
as
well
as
delivery
of
results
in
readily
consumable
formats—because
in

many
cases,
results
are
consumed
by
other
applications,
not
a
human.

• Scalability

We
can
assume
that
data
will
change
and
grow.
So
scalability
is
a
key
factor
for
search

application.
Applications
should
grow
to
address
future
needs
without
penalties
for
the

breadth
of
data
or
for
the
count
of
documents
indexed.
The
search
application
should
be

able
to
grow
with
the
requirements
of
the
organization,
without
needing
additional
large

investments
in
hardware
to
match
the
pace
of
growth.
Proprietary
search
vendors
often

charge
for
search
by
the
number
of
documents
indexed.
In
a
world
where
constantly

expanding
content
growth
is
the
norm,
such
costs
can
be
a
real
and
substantial
drag
on

the
cost
of
ownership
for
search
applications,
many
times
resulting
in
negative
return.

• Security

Every
organization
has
its
own
security
requirements
and
access
controls.
Search

technologies
need
to
comply
with
the
security
policies
of
the
enterprise,
controlling

results
that
have
restricted
access.
The
search
technology
should
also
be
able
to
make
use

of
document-‐level
security
from
other
sources.

How Is the Search Interface Presented to the User?
The
user
interface
is
where
search
delivers
on
findability
and
presents
actionable
results.
The

search
application
is
only
as
good
as
the
convenience
of
submitting
queries,
reviewing
and
refining

results,
and
finding
information.
Key
aspects
to
consider:

Page 5

• Navigation

Users
benefit
from
guidance
that
makes
their
queries
more
productive.
Techniques
such
as

faceted
search
with
result
clustering,
advance
hinting
(“did
you
mean”),
“more
like
this,”

and
drop
down
menus
for
setting
search
scope
help
users
achieve
desired
results
faster,

making
a
search
application
both
user-‐
and
information-‐friendly.
It
is
also
important
to

allow
users
to
draw
associative
connections
between
results—using
the
technology
to

uncover
relationships
and
discover
more
about
what
they
were
seeking
than
they
knew
at

the
outset.

The
NetFlix
search

application
is
powered

by
Solr;
it
adds
the
fuzzy

dimension
to
search,

with
auto-completion
of

movie
names,
correction

of
misspelled
names
of

actors,
and
suggests

titles
closest
to
the

query.
As
a
result,
85%

of
users
have
found
the

movie
they
were
looking

for
ranked
at
the
#1
spot

in
the
results.

• Discovery

Search
application
functionality
should
extend
beyond
the
generic
presentation
of
a
result

list
of
documents
that
contain
a
keyword.
Highlighting
keywords
in
searched
results,

expanding
searches
with
synonyms
and
spell
checking,
and
offering
users
ways
to
learn
a

bit
more
about
documents
in
the
results
without
having
to
load
the
document
are
great

ways
to
significantly
improve
usability.

• Intuitive
Intelligence

Search
applications
must
go
beyond
keyword
search
to
help
users
retrieve
accurate

information
even
when
they
are
not
sure
of
the
best
keywords.
Additionally,
they
should

reduce
misinterpretations
where
homonyms,
spelling
errors,
and
ambiguous
keywords
are

involved
(e.g.,
is
“apple”
a
fruit
or
a
computer
company?).

Page 6

The Real World: Applications and Case Studies
With
an
understanding
of
the
fundamentals
of
search
business
applications
in
hand,
it
is

helpful
to
gain
additional
context
on
business
usage
through
a
survey
of
organizations
that

have
successfully
used
Lucene/Solr
for
powerful
search
applications.

All
of
these
cases
were
built
on
the
capability
of
Lucene/Solr
to
provide
innovative,
high-‐
performance,
cross-‐platform,
feature-‐rich
search
technology
suitable
for
nearly
every

application.
By
powering
diverse
search
applications
for
thousands
of
organizations
such

as
AT&T,
Zappos,
McClatchy,
Smithsonian,
MTV
Networks,
LinkedIn,
MySpace,
Comcast,

Monster,
Netflix,
and
many
more,
Lucene/Solr
has
provided
mission
critical
capability
that

turns
search
into
a
robust
competitive
advantage.

For
these
organizations,
Lucene/Solr
solutions
regularly
index
and
search
hundreds
of

millions
of
documents
with
subsecond
response
time,
unencumbered
by
costly
licensing
or

vendor
lock-‐in.
Together
they
represent
a
compelling
argument
for
the
broad
applicability

of
Lucene/Solr
across
the
full
range
of
business
opportunities
and
search
needs.
Business

use
case
studies
we’ll
review
include:

• Yellow
Pages,
Local
Search,
and
Searching
Classifieds

• Media

• E-‐commerce

• Job
and
Career
Sites

• Libraries,
Archives,
and
Museums
(LAMs)
Search

• Social
Media
Search

• Enterprise
(Intranet)
Search

Page 7

Yellow Pages, Local Search, and Searching Requirements

Classifieds
In
the
business
of
online
local
search,
geographic-‐based
(location)
• Intelligent
results
going

beyond
keyword
search

relevance
generates
competitive
advantage.
Online
directories

need
to
provide
a
rich,
interactive
search
experience
to
users
to
• Deeper,
faceted

increase
site
views
and
stickiness,
which
in
turn
translates
into
navigation

increased
advertising
revenue.
Simplified
location-‐based
search,
• Seamless
integration

with
latest
Web
2.0

intuitive
faceted
query
response,
and
data
mashups
are
a
few

features
that
define
search
functionality
for
an
online
directory.
tools

• Lower
IT-‐related
costs

Lucene/Solr
solutions
offer
accurate
search
results,
factoring
in
• Geocentric
user

location,
users’
reviews,
and
ratings,
alongside
paid
advertising.
By
experience

taking
advantage
of
Solr’s
open
source
model—with
search
• Search
numeric
values

algorithms
that
are
completely
transparent—companies
can
invest

in
configuring
their
search
solutions
to
match
their
business
logic,

Solr
Solution

rather
than
trying
to
infer
or
pay
for
exposure
proprietary
back-‐
end
logic.

• Customizable
Search

Index
which
can
be

tuned
transparently
to

Internet
Yellow
pages
and
local
account
for
key

online
search
is
forecast
to
findability
drivers

• Drop
down
filters
for

grow
to
$27.8
billion
in
2011.

narrowing
or
widening

The
Kelsey
Report1
the
scope
of
search

• Seamless
integration

Success
Stories
with
existing

technologies

• YP.com,
a
division
of
AT&T
Interactive

• Native
numeric

• Zvents.com,
local
event
search
service

encoding
and
search

• Yelp.com,
the
community
local
search
site

capabilities

M • Reduced
server

footprint
for
lower
TCO

than
most
commercial

vendors

1The
Kelsey
Group’s
Global
Print
Yellow
Pages,
Internet
Yellow
Pages
and
Local
Search
Five

Year
Outlook

Page 8

Case
Study
1

yp.com
by
AT&T
Interactive

AT&T
Interactive
is
an
online
and
mobile
search
and
advertising
company.
Their
leading-‐edge
portal,
yp.com—an

online
business
listing
and
advertising
site—was
originally
implemented
with
a
commercial
proprietary
search

application.
It
faced
issues
of
scalability,
vendor
lock-‐in,
and
performance.
With
help
from
Lucid
Imagination,
AT&T

successfully
migrated
to
a
Solr-‐based
search
solution
that
leveraged
the
flexibility
of
open
source
without

compromising
features
and
functionality.

And
they
did
so
with
a
much
smaller
budget.

Business
Needs

• Addressing
the
need
to
factor
in
location
to
support
geographic
search,
and
include
relevant
comments

• Striking
a
balance
between
organic
search
and
advertised
content

• Indexing
highly
unstructured
content
such
as
user
comments

• Increasing
relevancy
of
results
and
boosting
paid
search
results
for
preferential
placement
of
advertisers

• Linguistic
support
to
enable
search
experience,
such
as
spellchecking,
synonyms,
find-‐similar,
etc.

• Integrating
with
latest
Web
2.0
tools

• Reducing
server
footprint

The
Solr
Solution

• Context-‐specific
relevancy,
geographic
proximity,
ad
placement,
and
user
comments

• Faceting,
drop
down
filters
to
narrow/widen
the
scope
of
search

• Functional
support
for
creating
new
features

• Spell-‐correction,
and
location-‐optimized
search
results
to
show
users
businesses
nearest
to
them
first

• Seamless
integration
with
many
Web
2.0
tools
to
create
innovative
features
and
mashups

• Lowers
TCO
by
reducing
the
number
of
search
servers
from
120
to
two
dozen
servers

Page 9

Media
Brand
reinforcement,
premium
content,
and
easy
accessibility

are
the
main
business
motivators
for
online
media
and
Requirements

publishing
companies.
Relevant
information
improves
time
on
• Real-‐time
indexing
of

the
site
and
encourages
users
to
explore
related
content,
petabytes
of
structured

boosting
subscription
rates
and
site
views.
These
translate
into
a
and
unstructured
data

virtuous
cycle
of
additional
revenue
generation.
• Deeper
search
capability

• Improved
query

Given
that
content
is
the
business,
the
need
for
a
robust
search

response
time

application
ties
directly
to
competitive
advantage.

• Reduced

infrastructure

Lucene/Solr
provides
a
customized,
function
rich
solution
for
the
and
customization
costs

media
and
publishing
industry.
It
addresses
dynamic
challenges

of
content
diversity,
content
freshness,
and
content
acquisition
,
Solr
Solution

and
gives
companies
a
platform
on
which

to
build
a
world-‐class
• Reverse
indexing

innovative
search
experience
to
differentiate
themselves
in
a
• Intelligent,
faceted
search

highly
competitive
marketplace.

to
enable
contextual
and

linguistic
relevance

• Easy
configuration
for

“Solr
has
done
wonders
for
us.
parsing
structured
and

It
is
easy
to
understand
and
unstructured
data

deploy,
and
has
reduced
our
• Easy
and
seamless

installation
for
lower

costs
drastically.”
TCO

Doug
Steigerwald,
• Customization
with
open

source
code

McClatchy
Interactive

Success
Stories

• McClatchy
Newspapers

• Netflix

• Comcast
Interactive

• MTV
Networks,
a
division
of
Viacom

M
• The
Motley
Fool,
fool.com

• Fanfeedr.com,
personalized
sports
aggregator

Page 10

Case
Study
2

McClatchy—Leading
Newspaper
Publisher

The
third
largest
newspaper
publisher
in
the
United
States,
McClatchy
Company
owns
30
daily

newspapers
in
29
markets
across
the
country.
To
win
online,
McClatchy
knew
it
had
to
have
a
robust

search
solution,
to
empower
the
McClatchy
audience
with
the
information
they
wanted
and
secure

loyalty
from
readers
and
sponsorships
from
advertisers.
Working
with
Lucid
Imagination,
McClatchy

migrated
from
proprietary
search
software
to
open
source
and
chose
Solr
for
its
high
performance,

comprehensive
capabilities,
and
superior
value

Requirements

• Proliferating
content
and
data
sources
(text,
videos,
audios,
images),
with
real-‐time

streaming

• Empowering
end
users
with
ease
of
use

• Supporting
peak
traffic
and
popular
search
spikes
with
consistent
performance

• Providing
scalability
for
a
database
growing
by
orders
of
magnitude
annually

• Providing
flexibility
to
support
customization

• Controlling
IT
costs
while
exceeding
performance
benchmarks
of
competition

The
Lucene/Solr
Solution

• Deeper
content
by
indexing
both
structured
and
unstructured
data
in
real
time,
effortlessly

• Indexes
millions
of
documents,
with
search
results
delivered
in
milliseconds

• User-‐friendly
navigation
with
drop
down
filters,
faceted
navigation,
linguistic
corrections,

etc.

• Excellent
performance,
even
in
peak
hours,
by
load-‐balancing
search
requests
across
servers

• Scalability
without
impact
on
performance

• High
degree
of
customization,
since
it’s
open
source

• Integration
with
existing
IT
infrastructure
and
eliminates
associated
license
fees
to
cut
costs

• 8-‐fold
reduction
in
server
footprint

Page 11

E-commerce

E-‐commerce
businesses
must
provide
a
compelling
shopping
experience
Requirements

in
order
to
maintain
brand
equity
and
thrive
in
a
very
highly
competitive
• Multidimensional,

market
landscape.
By
reducing
the
time
and
effort
required
to
navigate
dynamic
search

available
merchandise
and
find
what
they
want,
superior
search
• Faster
results

contributes
directly
to
a
satisfying
buying
experience
for
customers.
• Real-‐time
indexing

Search
then
translates
directly
into
higher
revenues
and
customer
of
products

loyalty.
Instant
results,
intuitively
organized,
advanced
faceting
for
easy
• Faceting
and

browsing,
synchronizing
results
with
images,
and
integration
with
user
browsing

ratings
are
among
the
must
have
features
of
an
e-‐commerce
search
capabilities

application.
• Seamless

Lucene/Solr
gives
companies
the
ability
to
build
their
sites
around
the
integration
with

concept
of
“searchendizing”—putting
the
desired
merchandise
at
the
top
existing
IT

of
the
results
list—which
can
make
the
difference
between
sales
made
infrastructure

and
sales
lost.
Faceting,
database
integration,
real-‐time
indexing,
and

query
monitoring
all
enable
users
to
find
products
they
want,
driving
Solr
Solution

conversion
rates
and
enabling
a
winning
online
experience.
2

• Faceted
search
for

deeper
drill
down

Online
retail
sales
in
the
and
browsing

B2C
market
are
expected
• Intuitive
search

capabilities
for

Success
Stories

to
reach
$340
billion
by
cross-‐channel

201321
shopping

• Buy.com

• Sears.com

experience

Forrester
Research
• System

• Macys.com

administration
tools

• Zappos.com

for
data
loading,

• Advanceautoparts.com

index
replication,

• Dollardays.com

monitoring,
logging,

and
cache

management

• Query
monitoring

2
“Consumers
will
spend
more
than
$340
billion
online
by
2013,
says
Forrester,”
for
better

Internet
Retailer,
27
November
2009,
http://www.internetretailer.com/dailyNews.asp?id=32630.
highlighting
of

popular
products

Page 12

Case
Study
3

Zappos

Zappos
is
the
premier
destination
for
online
shoe
shopping.
At
Zappos,
the
mission
is
excellent
online
customer

service—customers
should
be
able
to
browse
shoe
styles,
sizes,
shapes,
and
colors
more
easily
than
any
other
shoe

store,
on
or
offline.
To
achieve
this,
Zappos
wanted
a
robust,
flexible,
multifunctional
search
solution/application.

After
evaluating
many
commercial
search
technologies,
Zappos
zeroed
in
on
Solr,
working
with
Lucid
Imagination
to

ensure
continued,
successful
deployment.

Requirements

• Simplified,
attractive
user
experience
that
makes
it
easy
to
find
and
buy

• Relevant
results,
fast

• Navigation
across
attributes,
such
as
size,
color,
and
style
for
broader
and
deeper
results

• Indexing
products
as
they
were
entered
in
the
catalogs

• Cross-‐functional
navigation
to
give
customers
a
realistic
shopping
experience

• Intuitive
intelligence
to
provide
alternate
suggestions

• Analytical
capabilities
to
drive
business
strategy

• Facilitating
control
on
results

• Integration
with
existing
IT
infrastructure

The
Solr
Solution

• Search
results
in
subseconds,
across
categories

• Faceting,
for
easy
browsing
and
discovery
and
a
compelling
user
experience

• Real-‐time
indexing
of
products

• Synchronization
of
visuals,
specs,
filters,
and
promotions
to
make
shopping
experience
true
to
life

• Information
on
user
activity
to
help
build
strategy
on
product
promotions

• Controls
to
rank

popular
or
high-‐stock
products
in
results

where
users
are
more
likely
to
buy
them

• Facilitates
integration
with
heterogeneous
open
source
environment

Page 13

Job and Career Sites Requirements

• Linguistic

Job
portals
are
countercyclical
to
the
economy.
When
the
economy
intelligence
for

flourishes,
posted
jobs
grow
in
number;
when
it
sags,
candidates
flock
in
more
relevant

to
post
their
resumes.
Success
for
an
online
job
portal
is
tied
to
the
results

efficiency
of
its
search
capability—matching
résumés
to
job
listings
and
• Control
search

vice
versa—so
both
employers
and
prospective
employees
can
zero
in
results
to
maintain

on
just
the
right
opportunity.
privacy

For
example,
an
employer
may
want
to
navigate
through
filters
to
• Deeper
search

narrow
the
scope
of
a
candidate
search,
such
as
education,
previous
capability

employer,
salary
history,
skillsets,
etc.;
a
job
seeker
may
want
to
expose
• Numeric
search

these
attributes,
but
keep
a
current
employer’s
name
confidential.
A
job-‐ • Faster
query

seeker
may
want
to
apply
to
jobs
within
a
particular
geographic
area.
response

• Reduced

Lucene/Solr
not
only
provides
such
flexibility
but
also
addresses
other

infrastructure
and

complexities
of
this
industry
by
enabling
linguistic
intelligence
(such
as

customization
costs

identical
acronyms
that
correspond
to
different
entities;
variations
in

spelling,
imperfectly
constructed
search
queries);
indexing
unstructured
Solr
Solution

data
(résumés);
and
managing
ever-‐growing
data.
• Intelligent,
faceted

search
to
enable

contextual
and

“I
think
the
breakthrough
was
linguistic
relevance

when
we
tried
it,
and
we
• Easy
configuration

realized,
wow,
this
thing
could
for
parsing

structured
and

really
scale.”
unstructured
data

• Easy
and
seamless

Peter
Keegan,
Monster.com
installation
for

Success
Stories
lower
TCO

• Business
process

• Monster
integration
and

• The
Big
Jobs
Customization
with

• eBharatJobs
open
source
code

• Careerjet

M
Page 14

Monster.com

Monster
is
the
largest
job
search
engine
in
the
world,
with
over
a
million
jobs
posted
at
any
one
time.
By
2008
it
had

150
million
résumés
in
its
database,
serving
over
63
million
job
seekers
per
month,
now
running
on
average
300
to

400
queries
per
second
with
an
average
response
time
of
40
milliseconds.
To
provide
the
highest
level
of
service

and
support
to
their
customers—both
employers
and
job
seekers—Monster
has
an
unmatched
marketplace
for

employment
opportunities,
with
Lucene-‐based
search
at
the
heart
of
its
business
model.

The
Requirements

• Managing
high
volumes
of
data,
continually
increasing
by
double
digit
percentages
annually

• Maintaining
constant
inventory
updates
and
providing
faster
results

• Removing
technological
barriers
that
limit
the
scope
of
information

• Enabling
end
users
to
refine
search
and
drill
deeper
without
any
performance
impact

• Providing
security
controls
to
ensure
end
user
privacy

• Facilitating
scalability
and
flexibility
in
tandem
with
company’s
vision
and
growth
plans

The
Lucene
Solution

• High
volumes
of
data
by
clustering
data
to
reduce
the
index
size

• Real-‐time
indexing
for
fresher,
faster
query
results

• Intuitive
search
to
enable
in-‐depth
cross-‐functional
job
and
résumé
browsing

• Faceted
search
and
‘single
click’
filters
for
search
refinement

• Security
controls
to
manage
user
information

• Unlimited
scalability
and
customization
leveraging
open
source
licensing

Page 15

Case
Study
4

Libraries, Archives, and Museums (LAMs) Search
The
core
asset
of
educational
and
research
institutions
is
knowledge
Requirements

archived
and
accumulated
over
decades.
In
the
world
of
academic
search,

the
diversity
of
information
for
any
query—text,
illustration,
audio/video
• Management
of

media,
or
data
in
any
other
format—makes
unstructured
formats
a
key
multiple
formats
of

aspect
of
the
searchable
archive.

data
and
documents

• Customization
and

Lucene/Solr
gives
academic
and
research
institutions
the
power
to
turn
scalability

information
into
knowledge
by
going
beyond
keyword-‐driven
search
to
• Linguistic
support
in

expose
a
rich
variety
of
results
and
exploration.
Based
on
the
open
source
queries

model,
it
not
only
integrates
with
the
existing
IT
infrastructure
but
also
• Faster
results

leverages
the
existing
classification
hierarchies
to
give
structure
to

terabytes
of
information
spread
across
disparate
collections,
significantly

reducing
overhead
and
enabling
flexible
and
scalable
deployment.
Solr
Solution

• Optimized
index

infrastructure
limits

“With
Solr,
you
can
do
so
many
things
size
without

without
writing
a
lick
of
code.
I
hadn't
compromising
speed

realized
how
easy
it
is
to
extend
our
or
flexibility

custom
request
handler,
response
• Easy
customization

for
implementing

writer,
and
update
handler.
Just
move
taxonomy
rules

it
all
to
Solr
and
let
it
do
the
heavy
• Faceted
search
to

lifting.”
narrow
results
to
a

specific
source
across

Sjored
Siebinga,
Europeana
diverse
sets
of
data

• Instant
results

Success
Stories

• Seamless
integration

• Smithsonian
Institute

with
IT

• Europeana,
the
European
Union
online
cultural
archive
infrastructure
for

• The
US
Library
of
Congress
and
World
Digital
Library
lower
TCO

• Stanford
University
Library

• University
of
Michigan
Graduate
Library

Page 16

Case
Study
5

Smithsonian

The
Smithsonian
Institution
is
the
flagship
museum
collection
of
the
United
States,
supporting
a
research
institute

that
provides
“one-‐stop”
searching
for
2
million
records,
including
nearly
a
quarter
of
a
million
media
files
(images,

media
files,
online
journals,
and
other
resources)
distributed
across
dozens
of
archives,
databases,
museums,
and

libraries.
To
make
this
treasure
of
information
easily
accessible
to
people,
the
Smithsonian
needed
an
efficient

search
solution
that
could
overcome
the
following
challenges:

The
Challenges

Managing
a
complicated
taxonomy
that
could
no
longer
accommodate
a
growing
data
index

•
Indexing
disparate
types
of
content,
including
documents,
videos,
and
images

•
Making
information
available
from
a
large
database

•
Providing
access
controls
to
restrict
information

•
Integrating
with
existing
legacy
tools

•

Smithsonian
chose
Lucene/Solr,
and
worked
with
Lucid
Imagination
to
create
an
optimized,
well-‐designed
solution.

The
Solr
Solution

• Efficient
index
strategy
to
manage
a
mix
of
structured
and
unstructured
data

• Holistic
search,
by
optimizing
configuration
to
reduce

the
number
of
servers
and
better
handling
query

requests

• Filtering
information
through
faceted
search

• Access
controls
to
restrict
information
based
on
membership
profiles

• Integration
with
the
existing
IT
infrastructure

• Provides
guidance
and
assistance
on
setting
replicated
search
environment

Page 17

Requirements

Social Media Search • Deliver
search
results

Search
solutions
must
support
differentiated
business
models

matching
Web
2.0
innovations,
including
user-‐generated
content
as
soon
as
content
is

and
mashups,
without
compromising
scalability—a
challenge,
available

given
the
virtually
limitless
content
on
the
Internet.
Success
and
• Deeper
drill
down

differentiation
is
measured
by
how
well
the
site
provides
relevant
capabilities

results
to
grow
its
user
base
and
keeps
them
engaged.
• Intuitive
interface

Increasingly,
the
technological
factors
driving
Web
2.0
application

paradigms
are
finding
their
way
into
the
enterprise,
unlocking

collaboration
and
productivity
in
new
ways
that
challenge
Lucene/Solr
Solution

conventional
organizational
bounds—and
that
rely
in
equal

measure
on
search
to
create
the
connections
between
employees
• Near-‐instant
results

to
enable
discovery,
cross-‐pollination,
and
more
efficient
collective
with
segmentable

effort.
indexing

Lucene/Solr
not
only
provides
fast
results
but
also
facilitates
• Intuitive
search

flexible,
intuitive
navigation
to
help
end
users
connect
with
others.
• Data-‐driven

It
boosts
the
reach
and
performance
of
search,
while
cutting
spellchecking
based

implementation
costs
and
lowering
barriers
to
innovation.

on
user
search

histories

 Linguistic
support

Success
Stories
“With
Solr,
we
really
treat
it

through
‘Did
you

• Digg
as
kind
of
a
platform
where

Myspace
mean"
functionality

• we
can
build
other
kind
of
 Highlighting
keywords

• LinkedIn

• Reddit
things
on
top
of
it…
We
have
• Deeper
drill
down

• Technorati
a
very
valuable
set
of
data,
with
faceting

• Scout
Labs
and
we
really
want
to

• Xmarks.com
• Real-‐time
content

explore
new
ways
of
updating

building
new
features
from

that
data
set.”

—Sammy
Yu,
Digg.com

Page 18

Case
Study
6

Digg.com

Digg
displays
the
wisdom
of
the
crowds.
By
leveraging
the
mass
collaboration
of
readers
distributed
across
the

Internet—everything
on
Digg
is
submitted
by
the
public
community
for
the
public
community—it
builds
on
the
easy

findability
of
information
valued
by
the
marketplace
of
readers
and
consumers.

Digg
realized
early
on
that
to
succeed
in
the
business
of
information,
they
needed
to
make
information
available
to

their
audience
as
effortlessly
as
possible.
They
saw
the
following
challenges
as
roadblocks
for
implementing
a
base

search
application:

Requirements

• Managing
unstructured
data
(13
million
documents
and
growing)
in
real
time

• Providing
results
faster

• Facilitating
smart
navigation
to
provide
information
in
digestible
portions

• Recognizing
and
eliminating
duplicate
content

• Providing
semantic
and
linguistic
smart
application

• Facilitating
scalability
while
retaining
costs

Digg
selected
Solr
for
its
unmatched
flexibility
and
functionality.

The
Solr
Solution

• Highly
customizable
and
flexible

• Results
in
subseconds,
with
simple-‐to-‐use
pull
downs
to
refine
results

• Fuzzy
duplicate
detection
(by
coding)

• Unlimited
scalability
and
seamless
integration
with
the
heterogeneous
environment

Page 19

Case
Study
7

LinkedIn

Connecting
50
million
registered
users
from
200
countries
across
170
industries
and
matching
them
to

the
right
professional
contacts
is
what
LinkedIn
is
all
about.
LinkedIn’s
business
is
premised
on

intelligent
search
application
that
could
overcome
the
following:

The
Challenges

• Managing
an
ever-‐growing
database,
with
one
new
member
joining
and
creating
a
profile
every

second

• Indexing
unstructured
data
in
real
time

• Giving
instant
query
responses,
even
in
peak
traffic
hours

• Providing
intuitive
navigation
and
intelligent
linguistic
support

• Integrating
with
other
Web
2.0
tools
to
build
user
profiles
that
integrate
data
from
multiple

sources

They
chose
Lucene
to
implement
the
search
function
at
the
core
of
their
business
model.

The
Lucene
Solution

• Used
index
segmentation
for
faster
results
and
to
limit
index
base

• Provided
faceted
search
and
intelligence
support
features
like
changing
the
view
of
search

results
and
auto-‐completion
of
contacts

• Calculated
relative
relevance,
ranking
results
on
the
fly
based
on
relationship
between
the
user’s

profile
and
the
other
profiles
being
searched

• Integrated
with
the
latest
web
tools;
for
example,
incorporating
videos
in
search
results

• Provided
"scale
as
you
grow”
facility
through
the
flexibility
of
the
open
source
model

Page 20

Enterprise (Intranet) Search
Enterprises
today
have
a
global
footprint,
which
leads
to
the
creation
of
Requirements

multiple
content
types
and
the
use
of
disparate
applications
and
content

management
systems
across
business
centers.
The
result
is
often
silos
of
• Single
interface
to

unmanaged
data
spread
across
the
intranet
of
an
enterprise—a
situation
access
enterprise

where
information
is
omnipresent
but
cannot
be
used.
data

• Faster
results

To
achieve
a
competitive
advantage,
enable
intelligent
decisionmaking,
• Control
over
search

eliminate
duplication
of
work,
and
lower
the
cost
of
ownership,
results

enterprises
need
a
search
application
that
gives
structure
to
• Ready
integration

unstructured
data;
provides
a
single
gateway
to
search
across
multiple
with
existing

enterprise
repositories,
with
speed,
flexibility,
and
intuitive
intelligence.

content

Lucene/Solr
is
a
solid
match
for
enterprise
search.
As
a
customizable
and
management

multifunctional
search
application,
Lucene/Solr
provides
robust
search
software

features
at
minimal
cost.
The
open
source
development
model
behind

Lucene/Solr
integrates
seamlessly
with
legacy
tools,
and
brings
down
Solr
Solution

the
total
cost
of
ownership
significantly.

• Single
gateway
for

Given
the
sensitive
nature
of
enterprise
content,
Lucene/Solr
facilitates
all
types
of
data

document-‐level,
role-‐based
security.
And
with
the
transparent
search
• Dynamic
boosting

algorithms
and
configurability
for
relevancy,
Lucene/Solr
enables
of
content

intranet
search
with
the
precise
control
enterprise
content
owners
• Transparent
search

require,
ensuring
that
results
consistently
deliver
the
right
documents
to
algorithms
and

the
right
people.
relevancy
tuning

• Customization
and

easy
integration

“The
search
and
discovery
with
open
source

software
market
grew
19
code

percent
in
2008
to
$2.1
billion”

Sue
Feldman,
IDC

M

Page 21

Case
Study
8

Food
and
Drug
Administration

The
Food
and
Drug
Administration
(FDA)
is
a
U.S.
government
agency
responsible
for
regulating

and
supervising
the
safety
of
foods
medications,
veterinary
products,
tobacco,
and
cosmetics.
The

FDA
has
a
large
repository
of
information
that
dates
back
multiple
decades,
and
exists
in
formats

ranging
from
early
optical
character
recognition
to
recent
electronic
formats.
To
mine
this

knowledge
base,
the
FDA
is
developing
a
semantic
mining
framework
using
open
source
tools
such

as
Apache
Lucene
and
Solr.

Requirements

• Integrating
petabytes
of
data
highly
distributed
across
the
intranet
of
an
enterprise

• Managing
multiple
indices
for
documents
stored
in
distributed
repositories

• Managing
and
maintaining
archival
data
and
evolving
vocabularies

• Indexing
unstructured
data
in
real
time

• Recognizing
and
eliminating
duplicate
content

• Handling
concurrent
queries
and
delivering
fast
and
relevant
results

• Restricting
search
results
according
to
agency
access
control
policies

• Integrating
with
existing
infrastructure
without
additional
overhead

The
Lucene
Solution

• A
single
gateway
to
search
across
multiple
enterprise
repositories

• Duplicate
detection

• Fast
and
relevant
results
with
content
analysis
and
query
interpretation
algorithms

• Filters
results
based
on
access
controls
and
security
policies
of
an
enterprise

• Facilitates
integration
with
existing
enterprise
infrastructure
to
reduce
TCO

Page 22

Business Use Case Matrix
To
simplify
mapping
your
search
needs
to
existing
search
applications
in
the
real
world,
the
matrix

below
compares
business
use
cases
against
key
search
requirements.
While
not
an
exhaustive
list,

the
matrix
highlights
the
different
business
use
cases
across
sectors
and
business
models,
reflecting

the
adaptability
of
Lucene/Solr
across
the
various
domains
of
search
applications
and
use
cases.

Users Content Content Update Frequency
Access
Verticals Customer Control
Internal Original Aggregated High Medium Low
Facing

Enterprise (Intranet) √ √ √ √

Schools/
√ √ √ √ √ √
Universities
Education
Libraries √ √ √ √ √

Job Portals √ √ √ √

Social Networks √ √ √ √ √

News √ √ √ √
Media
Media √ √ √ √

E-Commerce Sites √ √ √ √ √ √

Financial Services √ √ √ √ √

Yellow Pages √ √ √

Horizontal Portals √ √ √ √

Page 23

Appendix: Lucene/Solr Features and Benefits
Lucene
and
Solr
are
complementary
technologies
that
offer
very
similar
underlying
capabilities.
In

choosing
a
search
solution
that
is
best
suited
for
your
requirements,
key
factors
to
consider
are

application
scope,
development
environment,
and
software
development
preferences.

Lucene
is
a
Java
technology-‐based
search
library
that
offers
speed,
relevancy
ranking,
complete

query
capabilities,
portability,
scalability,
and
low
overhead
indexes
and
rapid
incremental

indexing.

Solr
is
the
Lucene
Search
Server.
It
presents
a
web
service
layer
built
atop
Lucene
using
the
Lucene

search
library
and
extending
it
to
provide
application
users
with
a
ready-‐to-‐use
search
platform.

Solr
brings
with
it
operational
and
administrative
capabilities
like
web
services,
faceting,

configurable
schema,
caching,
replication,
and
administrative
tools
for
configuration,
data
loading,

statistics,
logging,
cache
management,
and
more.

Lucene
presents
a
collection
of
directly
callable
Java
libraries
and
requires
coding
and
solid

information
retrieval
experience.
Solr
extends
the
capabilities
of
Lucene
to
provide
an
enterprise-‐
ready
search
platform,
eliminating
the
need
for
extensive
programming.

Solr
provides
the
starting
point
for
most
developers
who
are
building
a
Lucene-‐based
search

application.
It
comes
ready
to
run
in
a
servlet
container
such
as
Tomcat
or
Jetty,
making
it
ready
to

scale
in
a
production
Java
environment.

With
convenient
ReST-‐like/web-‐service
interfaces
callable
over
HTTP,
and
transparent
XML-‐based

configuration
files,
Solr
can
greatly
accelerate
application
development
and
maintenance.
In
fact,

Lucene
programmers
have
often
reported
that
they
find
Solr
contains
“the
same
features
I
was

going
to
build
myself
as
a
framework
for
Lucene,
but
already
very
well
implemented.”
Using
Solr,

enterprises
can
customize
the
search
application
according
to
their
requirements,
without

involving
the
cost
and
risk
of
writing
the
code
from
the
scratch.

Lucene
provides
greater
control
of
your
source
code
and
works
best
in
development
environments

where
resources
need
to
be
controlled
exclusively
by
Java
API
calls.
It
works
best
when

constructing
and
embedding
a
state-‐of-‐the-‐art
search
engine,
allowing
programmers
to
assemble

and
compile
inside
a
native
Java
application.
While
working
with
Lucene,
programmers
can
directly

control
the
large
set
of
sophisticated
features
with
low-‐level
access,
data,
or
state
manipulation.

Enterprises
that
do
not
require
strict
control
of
low-‐level
Java
libraries
generally
prefer
Solr,
as
it

provides
ease
of
use
and
scalable
search
power
out
of
the
box.

Page 24

As
functional
siblings,
Lucene
and
Solr
have
become
popular
alternatives
for
search
applications;

the
two
differ
mainly
in
the
style
of
application
development
used.
Key
benefits
of
search
with

Lucene/Solr
include:

• Search
Quality:
Speed,
Relevance,
and
Precision
Lucene/Solr
provides
near-‐real-‐time

search
and
strong
relevance
ranking
to
deliver
contextually
relevant
and
accurate
results

very
quickly.
Tailor-‐made
coding
for
relevancy
ranking
and
sophisticated
search

capabilities
like
faceted
search
help
users
in
sorting,
organizing,
classifying,
and
structuring

retrieved
information
to
ensure
that
search
delivers
desired
results.
Search
with

Lucene/Solr
also
provides
proximity
operators,
wildcards,
fielded
searching,

term/field/document
weights,
find-‐similar
functions,
spell
checking,
multilingual
search,

and
much
more.

• Lower
Cost
and
Greater
Flexibility,
Plug
and
Play
Architecture
Lucene/Solr
reduces

recurring
and
nonrecurring
costs,
lowering
your
TCO.
As
open
source
software,
it
does
not

require
purchase
of
a
license
and
is
freely
available
for
use.
The
open
source
code
can
be

used
as
is,
modified,
customized,
and
updated
as
appropriate
to
your
needs.
Solr
is
easily

embedded
in
your
enterprise’s
existing
infrastructure,
reducing
costs
of
installation,

configuration,
and
management.

• Open
Source
Platform
for
Portability
and
Easy
Deployment
Because
Lucene/Solr
is
an

open-‐source
software
solution,
it
is
based
on
open
standards
and
community-‐driven

development
processes.
It
is
highly
portable
and
can
run
on
any
platform
that
supports
Java.

For
instance,
you
can
build
an
index
on
Linux
and
copy
it
to
a
Microsoft
Windows
machine

and
search
there.
This
unsurpassed
portability
enables
you
to
keep
your
search
application

and
your
company’s
evolving
infrastructure
in
tandem.
Lucene,
in
turn,
has
been

implemented
in
other
environments,
including
C#,
C,
Python,
and
PHP.
At
deployment
time,

Solr
offers
very
flexible
options;
it
can
be
easily
deployed
on
a
single
server
as
well
as
on

distributed,
multiserver
systems.

• Largest
Installed
Base
of
Applications,
Increasing
Customer
Base
Lucene/Solr
is
the

most
widely
used
open
source
search
system
and
is
installed
in
around
4,000
organizations

worldwide.
Publicly
visible
search
sites
that
use
Lucene/Solr
include
CNET,
LinkedIn,

Monster,
Digg,
Zappos,
MySpace,
Netflix,
and
Wikipedia.
Lucene/Solr
is
also
in
use
at
Apple,

HP,
IBM,
Iron
Mountain,
and
Los
Alamos
National
Laboratories.

Page 25

• Large
Developer
Base
and
Adaptability
As
community
developed
software,
Lucene/Solr

provides
transparent
development
and
easy
access
to
updates
and
releases.
Developers
can

work
with
open
source
code
and
customize
the
software
according
to
business-‐specific

needs
and
objectives.
Its
open
source
paradigm
lets
Lucene/Solr
provide
developers
with

the
freedom
and
flexibility
to
evolve
the
software
with
changing
requirements,
liberating

them
from
the
constraints
of
commercial
vendors.

• Commercial-Grade
Support
for
Mission
Critical
Search
Applications
from
Lucid

Imagination
Lucid
Imagination
provides
the
expertise,
resources,
and
services
that
are

needed
to
help
enterprises
deploy
and
develop
Lucene-‐based
search
solutions
efficiently

and
cost-‐effectively.
Lucid
helps
enterprises
achieve
optimal
search
performance
and

accuracy
with
its
broad
range
of
expertise,
which
includes
indexing
and
metadata

management,
content
analysis,
business
rule
application,
and
natural
language
processing.

Lucid
Imagination
also
offers
certified
distributions
of
Lucene
and
Solr,
commercial-‐grade

SLA-‐based
support,
training,
high-‐level
consulting
and
value-‐added
software
extensions
to

enable
customers
to
create
powerful
and
successful
search
applications.

Page 26

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