Infrastructure people pushing google search on us:-( any help defending ES would be appreciated!

We have a really good pilot with ES and now infrastructure people pushing
google search on us because they have in on their approved stack (and I bet
to charge for licenses too)

What are the weaknesses of google search compared to ES?

Our application works with heavily structured data (large number of small
fields) and has lots of faceting and analytics. Is google search any good
with it structured documents with many fields? Does it have it advanced
faceting? Does it allow fine grained control over indexing?

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I haven't used Google search. Briefly played around w/ Amazon CloudSearch.
One thing is latency that is probably applicable to any cloud based
solution. Within a data center you can update ES and have near realtime
updates. With AWS CloudSearch I remember it does things in batches and
there's also the latency of a network request to Virginia.

On Thursday, May 23, 2013 12:06:02 PM UTC-7, AlexR wrote:

We have a really good pilot with ES and now infrastructure people pushing
google search on us because they have in on their approved stack (and I bet
to charge for licenses too)

What are the weaknesses of google search compared to ES?

Our application works with heavily structured data (large number of small
fields) and has lots of faceting and analytics. Is google search any good
with it structured documents with many fields? Does it have it advanced
faceting? Does it allow fine grained control over indexing?

--
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To unsubscribe from this group and stop receiving emails from it, send an email to elasticsearch+unsubscribe@googlegroups.com.
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Thanks Tinou,

They have (or would have) google search (I guess appliance) in the data
center. so i do not think latency will be an issue. it is the services it
can provide, and integration I need to understand.
From very briefly going over google documentation my feeling is:

  1.   It is not free like ElasticSearch. The licenses may be quite costly
    
  2.   It is optimized for document and site indexing and searching and
    

not so much for structured data indexing searching, analytics and faceting
while elastic allows very easy mixing of both

  1.   It is a shrink wrap product which comes with GUI, administration
    

and is centered around searching for documents or web pages or emails plus
some metadata about them not structured data with 100th of fields with need
to

  1.   It is not an open source or open platform - it is a shrink wrapped
    

solution with various connectors to pull data from various data sources.

a. It may be impossible to do something unless google baked it. For
example showing which fields got hits might not even be possible

b. It will be harder to integrate

  1.   Our product will be constrained to what google platform offers and
    

we will be bound to versions, licenses and upgrade schedule the IT Shop has
for the product

  1.   All documentation I found is about configuring and managing
    

nothing much about developing for it, executing complex custom queries etc.

  1.   I checked its user groups – they seems to be dormant unlike
    

elastic search. Not sure where one can get any support unless it is paid
8. Last not the least it will be starting development all over even
if it is possible to achieve the same with google

On Thu, May 23, 2013 at 7:03 PM, Tinou Bao tinou.bao@gmail.com wrote:

I haven't used Google search. Briefly played around w/ Amazon CloudSearch.
One thing is latency that is probably applicable to any cloud based
solution. Within a data center you can update ES and have near realtime
updates. With AWS CloudSearch I remember it does things in batches and
there's also the latency of a network request to Virginia.

On Thursday, May 23, 2013 12:06:02 PM UTC-7, AlexR wrote:

We have a really good pilot with ES and now infrastructure people pushing
google search on us because they have in on their approved stack (and I bet
to charge for licenses too)

What are the weaknesses of google search compared to ES?

Our application works with heavily structured data (large number of small
fields) and has lots of faceting and analytics. Is google search any good
with it structured documents with many fields? Does it have it advanced
faceting? Does it allow fine grained control over indexing?

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Our infra guy also provide Google search service. One issue, if not miss
configuration,is that the search result is not stable. You could find the
result one day, but failed the other day.

My 2 cents here.
在 2013-5-24 上午7:10,"Alex Roytman" roytmana@gmail.com写道:

Thanks Tinou,

They have (or would have) google search (I guess appliance) in the data
center. so i do not think latency will be an issue. it is the services it
can provide, and integration I need to understand.
From very briefly going over google documentation my feeling is:

  1.   It is not free like ElasticSearch. The licenses may be quite
    

costly

  1.   It is optimized for document and site indexing and searching and
    

not so much for structured data indexing searching, analytics and faceting
while elastic allows very easy mixing of both

  1.   It is a shrink wrap product which comes with GUI, administration
    

and is centered around searching for documents or web pages or emails plus
some metadata about them not structured data with 100th of fields with
need to

  1.   It is not an open source or open platform - it is a shrink
    

wrapped solution with various connectors to pull data from various data
sources.

a. It may be impossible to do something unless google baked it. For
example showing which fields got hits might not even be possible

b. It will be harder to integrate

  1.   Our product will be constrained to what google platform offers
    

and we will be bound to versions, licenses and upgrade schedule the IT Shop
has for the product

  1.   All documentation I found is about configuring and managing
    

nothing much about developing for it, executing complex custom queries etc.

  1.   I checked its user groups – they seems to be dormant unlike
    

elastic search. Not sure where one can get any support unless it is paid
8. Last not the least it will be starting development all over even
if it is possible to achieve the same with google

On Thu, May 23, 2013 at 7:03 PM, Tinou Bao tinou.bao@gmail.com wrote:

I haven't used Google search. Briefly played around w/ Amazon
CloudSearch. One thing is latency that is probably applicable to any cloud
based solution. Within a data center you can update ES and have near
realtime updates. With AWS CloudSearch I remember it does things in batches
and there's also the latency of a network request to Virginia.

On Thursday, May 23, 2013 12:06:02 PM UTC-7, AlexR wrote:

We have a really good pilot with ES and now infrastructure people
pushing google search on us because they have in on their approved stack
(and I bet to charge for licenses too)

What are the weaknesses of google search compared to ES?

Our application works with heavily structured data (large number of
small fields) and has lots of faceting and analytics. Is google search any
good with it structured documents with many fields? Does it have it
advanced faceting? Does it allow fine grained control over indexing?

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To my knowledge, GSA doesn't have any faceting/analytics/counts
capabilities:
http://www.google.com/support/enterprise/static/gsa/docs/admin/70/gsa_doc_set/xml_reference/

On Thu, May 23, 2013 at 6:03 PM, xiong.jaguar xiong.jaguar@gmail.comwrote:

Our infra guy also provide Google search service. One issue, if not miss
configuration,is that the search result is not stable. You could find the
result one day, but failed the other day.

My 2 cents here.
在 2013-5-24 上午7:10,"Alex Roytman" roytmana@gmail.com写道:

Thanks Tinou,

They have (or would have) google search (I guess appliance) in the data
center. so i do not think latency will be an issue. it is the services it
can provide, and integration I need to understand.
From very briefly going over google documentation my feeling is:

  1.   It is not free like ElasticSearch. The licenses may be quite
    

costly

  1.   It is optimized for document and site indexing and searching
    

and not so much for structured data indexing searching, analytics and
faceting while elastic allows very easy mixing of both

  1.   It is a shrink wrap product which comes with GUI,
    

administration and is centered around searching for documents or web pages
or emails plus some metadata about them not structured data with 100thof fields with need to

  1.   It is not an open source or open platform - it is a shrink
    

wrapped solution with various connectors to pull data from various data
sources.

a. It may be impossible to do something unless google baked it.
For example showing which fields got hits might not even be possible

b. It will be harder to integrate

  1.   Our product will be constrained to what google platform offers
    

and we will be bound to versions, licenses and upgrade schedule the IT Shop
has for the product

  1.   All documentation I found is about configuring and managing
    

nothing much about developing for it, executing complex custom queries etc.

  1.   I checked its user groups – they seems to be dormant unlike
    

elastic search. Not sure where one can get any support unless it is paid
8. Last not the least it will be starting development all over
even if it is possible to achieve the same with google

On Thu, May 23, 2013 at 7:03 PM, Tinou Bao tinou.bao@gmail.com wrote:

I haven't used Google search. Briefly played around w/ Amazon
CloudSearch. One thing is latency that is probably applicable to any cloud
based solution. Within a data center you can update ES and have near
realtime updates. With AWS CloudSearch I remember it does things in batches
and there's also the latency of a network request to Virginia.

On Thursday, May 23, 2013 12:06:02 PM UTC-7, AlexR wrote:

We have a really good pilot with ES and now infrastructure people
pushing google search on us because they have in on their approved stack
(and I bet to charge for licenses too)

What are the weaknesses of google search compared to ES?

Our application works with heavily structured data (large number of
small fields) and has lots of faceting and analytics. Is google search any
good with it structured documents with many fields? Does it have it
advanced faceting? Does it allow fine grained control over indexing?

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To add one more important aspect: performance. It should be possible to
order an evaluation license or something for a limited time (1-3
months). Put your data on the product (if possible) and measure the
"documents per second" while indexing and "queries per second" while
searching, for all your workloads. Compare that numbers to ES on your
favorite platform. Add your findings (ease of administration, network
latency, resource sizing challenges etc) Present the result to
management. Management always listens to technical staff when
performance is the issue - it is expensive to fix performance issues later.

Another more important one to kill every cloud-based app scenario is
data privacy but I'm not sure if your data is relevant to this topic.

Jörg

Am 24.05.13 01:10, schrieb Alex Roytman:

Thanks Tinou,

They have (or would have) google search (I guess appliance) in the
data center. so i do not think latency will be an issue. it is the
services it can provide, and integration I need to understand.
From very briefly going over google documentation my feeling is:

1.It is not free like ElasticSearch. The licenses may be quite costly

2.It is optimized for document and site indexing and searching and not
so much for structured data indexing searching, analytics and faceting
while elastic allows very easy mixing of both

3.It is a shrink wrap product which comes with GUI, administration and
is centered around searching for documents or web pages or emails plus
some metadata about them not structured data with 100^th of fields
with need to

4.It is not an open source or open platform - it is a shrink wrapped
solution with various connectors to pull data from various data sources.

a.It may be impossible to do something unless google baked it. For
example showing which fields got hits might not even be possible

b.It will be harder to integrate

5.Our product will be constrained to what google platform offers and
we will be bound to versions, licenses and upgrade schedule the IT
Shop has for the product

6.All documentation I found is about configuring and managing nothing
much about developing for it, executing complex custom queries etc.

7.I checked its user groups – they seems to be dormant unlike elastic
search. Not sure where one can get any support unless it is paid

8.Last not the least it will be starting development all over even if
it is possible to achieve the same with google

On Thu, May 23, 2013 at 7:03 PM, Tinou Bao <tinou.bao@gmail.com
mailto:tinou.bao@gmail.com> wrote:

I haven't used Google search. Briefly played around w/ Amazon
CloudSearch. One thing is latency that is probably applicable to
any cloud based solution. Within a data center you can update ES
and have near realtime updates. With AWS CloudSearch I remember it
does things in batches and there's also the latency of a network
request to Virginia.


On Thursday, May 23, 2013 12:06:02 PM UTC-7, AlexR wrote:


    We have a really good pilot with ES and now infrastructure
    people pushing google search on us because they have in on
    their approved stack (and I bet to charge for licenses too)

    What are the weaknesses of google search compared to ES?

    Our application works with heavily structured data (large
    number of small fields) and has lots of faceting and
    analytics. Is google search any good with it structured
    documents with many fields? Does it have it advanced faceting?
    Does it allow fine grained control over indexing?


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Thanks Louis, looks like you are correct. I can't find it. I thought it was
dynamic results clustering but I do not think it is. I read some articles
where people were talking about faceting in GSA but i do not see it in the
docs

On Thursday, May 23, 2013 9:26:10 PM UTC-4, Louis Chabardes wrote:

To my knowledge, GSA doesn't have any faceting/analytics/counts
capabilities:
http://www.google.com/support/enterprise/static/gsa/docs/admin/70/gsa_doc_set/xml_reference/

On Thu, May 23, 2013 at 6:03 PM, xiong.jaguar <xiong....@gmail.com<javascript:>

wrote:

Our infra guy also provide Google search service. One issue, if not miss
configuration,is that the search result is not stable. You could find the
result one day, but failed the other day.

My 2 cents here.
在 2013-5-24 上午7:10,"Alex Roytman" <royt...@gmail.com <javascript:>>写道:

Thanks Tinou,

They have (or would have) google search (I guess appliance) in the data
center. so i do not think latency will be an issue. it is the services it
can provide, and integration I need to understand.
From very briefly going over google documentation my feeling is:

  1.   It is not free like ElasticSearch. The licenses may be quite 
    

costly

  1.   It is optimized for document and site indexing and searching 
    

and not so much for structured data indexing searching, analytics and
faceting while elastic allows very easy mixing of both

  1.   It is a shrink wrap product which comes with GUI, 
    

administration and is centered around searching for documents or web pages
or emails plus some metadata about them not structured data with 100thof fields with need to

  1.   It is not an open source or open platform - it is a shrink 
    

wrapped solution with various connectors to pull data from various data
sources.

a. It may be impossible to do something unless google baked it.
For example showing which fields got hits might not even be possible

b. It will be harder to integrate

  1.   Our product will be constrained to what google platform offers 
    

and we will be bound to versions, licenses and upgrade schedule the IT Shop
has for the product

  1.   All documentation I found is about configuring and managing 
    

nothing much about developing for it, executing complex custom queries etc.

  1.   I checked its user groups – they seems to be dormant unlike 
    

elastic search. Not sure where one can get any support unless it is paid
8. Last not the least it will be starting development all over
even if it is possible to achieve the same with google

On Thu, May 23, 2013 at 7:03 PM, Tinou Bao <tino...@gmail.com<javascript:>

wrote:

I haven't used Google search. Briefly played around w/ Amazon
CloudSearch. One thing is latency that is probably applicable to any cloud
based solution. Within a data center you can update ES and have near
realtime updates. With AWS CloudSearch I remember it does things in batches
and there's also the latency of a network request to Virginia.

On Thursday, May 23, 2013 12:06:02 PM UTC-7, AlexR wrote:

We have a really good pilot with ES and now infrastructure people
pushing google search on us because they have in on their approved stack
(and I bet to charge for licenses too)

What are the weaknesses of google search compared to ES?

Our application works with heavily structured data (large number of
small fields) and has lots of faceting and analytics. Is google search any
good with it structured documents with many fields? Does it have it
advanced faceting? Does it allow fine grained control over indexing?

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Thanks Jorg. If it gets that far (hope not) we will do performance trails.
I do not think it will have any "cloud" issues because they will run it in
the data center...

On Friday, May 24, 2013 5:42:31 AM UTC-4, Jörg Prante wrote:

To add one more important aspect: performance. It should be possible to
order an evaluation license or something for a limited time (1-3
months). Put your data on the product (if possible) and measure the
"documents per second" while indexing and "queries per second" while
searching, for all your workloads. Compare that numbers to ES on your
favorite platform. Add your findings (ease of administration, network
latency, resource sizing challenges etc) Present the result to
management. Management always listens to technical staff when
performance is the issue - it is expensive to fix performance issues
later.

Another more important one to kill every cloud-based app scenario is
data privacy but I'm not sure if your data is relevant to this topic.

Jörg

Am 24.05.13 01:10, schrieb Alex Roytman:

Thanks Tinou,

They have (or would have) google search (I guess appliance) in the
data center. so i do not think latency will be an issue. it is the
services it can provide, and integration I need to understand.
From very briefly going over google documentation my feeling is:

1.It is not free like ElasticSearch. The licenses may be quite costly

2.It is optimized for document and site indexing and searching and not
so much for structured data indexing searching, analytics and faceting
while elastic allows very easy mixing of both

3.It is a shrink wrap product which comes with GUI, administration and
is centered around searching for documents or web pages or emails plus
some metadata about them not structured data with 100^th of fields
with need to

4.It is not an open source or open platform - it is a shrink wrapped
solution with various connectors to pull data from various data sources.

a.It may be impossible to do something unless google baked it. For
example showing which fields got hits might not even be possible

b.It will be harder to integrate

5.Our product will be constrained to what google platform offers and
we will be bound to versions, licenses and upgrade schedule the IT
Shop has for the product

6.All documentation I found is about configuring and managing nothing
much about developing for it, executing complex custom queries etc.

7.I checked its user groups – they seems to be dormant unlike elastic
search. Not sure where one can get any support unless it is paid

8.Last not the least it will be starting development all over even if
it is possible to achieve the same with google

On Thu, May 23, 2013 at 7:03 PM, Tinou Bao <tino...@gmail.com<javascript:>
<mailto:tino...@gmail.com <javascript:>>> wrote:

I haven't used Google search. Briefly played around w/ Amazon 
CloudSearch. One thing is latency that is probably applicable to 
any cloud based solution. Within a data center you can update ES 
and have near realtime updates. With AWS CloudSearch I remember it 
does things in batches and there's also the latency of a network 
request to Virginia. 


On Thursday, May 23, 2013 12:06:02 PM UTC-7, AlexR wrote: 


    We have a really good pilot with ES and now infrastructure 
    people pushing google search on us because they have in on 
    their approved stack (and I bet to charge for licenses too) 

    What are the weaknesses of google search compared to ES? 

    Our application works with heavily structured data (large 
    number of small fields) and has lots of faceting and 
    analytics. Is google search any good with it structured 
    documents with many fields? Does it have it advanced faceting? 
    Does it allow fine grained control over indexing? 


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I think you need to focus on your structured data and how you have complete
control of how that is indexed/searched with ES. With the GSA (Google
Search Appliance) it is really good at crawling as you might expect. It
can handle structured data but it is quite limited from what I hear. Based
on all the threads and issues I have seen you hoping, you have some very
strict requirements on what fields get searched, proximity and boosts
between matches across fields, etc. Meeting these requirements with ES is
going to be much easier and quicker than with the GSA.

On Fri, May 24, 2013 at 8:12 AM, AlexR roytmana@gmail.com wrote:

Thanks Jorg. If it gets that far (hope not) we will do performance trails.
I do not think it will have any "cloud" issues because they will run it in
the data center...

On Friday, May 24, 2013 5:42:31 AM UTC-4, Jörg Prante wrote:

To add one more important aspect: performance. It should be possible to
order an evaluation license or something for a limited time (1-3
months). Put your data on the product (if possible) and measure the
"documents per second" while indexing and "queries per second" while
searching, for all your workloads. Compare that numbers to ES on your
favorite platform. Add your findings (ease of administration, network
latency, resource sizing challenges etc) Present the result to
management. Management always listens to technical staff when
performance is the issue - it is expensive to fix performance issues
later.

Another more important one to kill every cloud-based app scenario is
data privacy but I'm not sure if your data is relevant to this topic.

Jörg

Am 24.05.13 01:10, schrieb Alex Roytman:

Thanks Tinou,

They have (or would have) google search (I guess appliance) in the
data center. so i do not think latency will be an issue. it is the
services it can provide, and integration I need to understand.
From very briefly going over google documentation my feeling is:

1.It is not free like ElasticSearch. The licenses may be quite costly

2.It is optimized for document and site indexing and searching and not
so much for structured data indexing searching, analytics and faceting
while elastic allows very easy mixing of both

3.It is a shrink wrap product which comes with GUI, administration and
is centered around searching for documents or web pages or emails plus
some metadata about them not structured data with 100^th of fields
with need to

4.It is not an open source or open platform - it is a shrink wrapped
solution with various connectors to pull data from various data
sources.

a.It may be impossible to do something unless google baked it. For
example showing which fields got hits might not even be possible

b.It will be harder to integrate

5.Our product will be constrained to what google platform offers and
we will be bound to versions, licenses and upgrade schedule the IT
Shop has for the product

6.All documentation I found is about configuring and managing nothing
much about developing for it, executing complex custom queries etc.

7.I checked its user groups – they seems to be dormant unlike elastic
search. Not sure where one can get any support unless it is paid

8.Last not the least it will be starting development all over even if
it is possible to achieve the same with google

On Thu, May 23, 2013 at 7:03 PM, Tinou Bao <tino...@gmail.com
mailto:tino...@gmail.com> wrote:

I haven't used Google search. Briefly played around w/ Amazon
CloudSearch. One thing is latency that is probably applicable to
any cloud based solution. Within a data center you can update ES
and have near realtime updates. With AWS CloudSearch I remember it
does things in batches and there's also the latency of a network
request to Virginia.


On Thursday, May 23, 2013 12:06:02 PM UTC-7, AlexR wrote:


    We have a really good pilot with ES and now infrastructure
    people pushing google search on us because they have in on
    their approved stack (and I bet to charge for licenses too)

    What are the weaknesses of google search compared to ES?

    Our application works with heavily structured data (large
    number of small fields) and has lots of faceting and
    analytics. Is google search any good with it structured
    documents with many fields? Does it have it advanced faceting?
    Does it allow fine grained control over indexing?


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Precisely my thoughts Matt, thank you! I have already crafted a draft
response along these lines just wanted to get some confirmation from the
user community that I am not missing existing GSA features and strong
points missrepresenting its value in my desire to stick with ES

On Fri, May 24, 2013 at 11:22 AM, Matt Weber matt.weber@gmail.com wrote:

I think you need to focus on your structured data and how you have
complete control of how that is indexed/searched with ES. With the GSA
(Google Search Appliance) it is really good at crawling as you might
expect. It can handle structured data but it is quite limited from what I
hear. Based on all the threads and issues I have seen you hoping, you have
some very strict requirements on what fields get searched, proximity and
boosts between matches across fields, etc. Meeting these requirements with
ES is going to be much easier and quicker than with the GSA.

On Fri, May 24, 2013 at 8:12 AM, AlexR roytmana@gmail.com wrote:

Thanks Jorg. If it gets that far (hope not) we will do performance
trails. I do not think it will have any "cloud" issues because they will
run it in the data center...

On Friday, May 24, 2013 5:42:31 AM UTC-4, Jörg Prante wrote:

To add one more important aspect: performance. It should be possible to
order an evaluation license or something for a limited time (1-3
months). Put your data on the product (if possible) and measure the
"documents per second" while indexing and "queries per second" while
searching, for all your workloads. Compare that numbers to ES on your
favorite platform. Add your findings (ease of administration, network
latency, resource sizing challenges etc) Present the result to
management. Management always listens to technical staff when
performance is the issue - it is expensive to fix performance issues
later.

Another more important one to kill every cloud-based app scenario is
data privacy but I'm not sure if your data is relevant to this topic.

Jörg

Am 24.05.13 01:10, schrieb Alex Roytman:

Thanks Tinou,

They have (or would have) google search (I guess appliance) in the
data center. so i do not think latency will be an issue. it is the
services it can provide, and integration I need to understand.
From very briefly going over google documentation my feeling is:

1.It is not free like ElasticSearch. The licenses may be quite costly

2.It is optimized for document and site indexing and searching and not
so much for structured data indexing searching, analytics and faceting
while elastic allows very easy mixing of both

3.It is a shrink wrap product which comes with GUI, administration and
is centered around searching for documents or web pages or emails plus
some metadata about them not structured data with 100^th of fields
with need to

4.It is not an open source or open platform - it is a shrink wrapped
solution with various connectors to pull data from various data
sources.

a.It may be impossible to do something unless google baked it. For
example showing which fields got hits might not even be possible

b.It will be harder to integrate

5.Our product will be constrained to what google platform offers and
we will be bound to versions, licenses and upgrade schedule the IT
Shop has for the product

6.All documentation I found is about configuring and managing nothing
much about developing for it, executing complex custom queries etc.

7.I checked its user groups – they seems to be dormant unlike elastic
search. Not sure where one can get any support unless it is paid

8.Last not the least it will be starting development all over even if
it is possible to achieve the same with google

On Thu, May 23, 2013 at 7:03 PM, Tinou Bao <tino...@gmail.com
mailto:tino...@gmail.com> wrote:

I haven't used Google search. Briefly played around w/ Amazon
CloudSearch. One thing is latency that is probably applicable to
any cloud based solution. Within a data center you can update ES
and have near realtime updates. With AWS CloudSearch I remember it
does things in batches and there's also the latency of a network
request to Virginia.


On Thursday, May 23, 2013 12:06:02 PM UTC-7, AlexR wrote:


    We have a really good pilot with ES and now infrastructure
    people pushing google search on us because they have in on
    their approved stack (and I bet to charge for licenses too)

    What are the weaknesses of google search compared to ES?

    Our application works with heavily structured data (large
    number of small fields) and has lots of faceting and
    analytics. Is google search any good with it structured
    documents with many fields? Does it have it advanced faceting?
    Does it allow fine grained control over indexing?


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On 5/24/2013 8:29 AM, Alex Roytman wrote:

Precisely my thoughts Matt, thank you! I have already crafted a draft
response along these lines just wanted to get some confirmation from
the user community that I am not missing existing GSA features and
strong points missrepresenting its value in my desire to stick with ES

I also understood that GSA has no ability to deal with access control
which you could provide in an ES product be it in-house or 3rd party.

Another issue is that it brings several parts of the web algorithms to
the enterprise. At first this sounds like a feature, but it is not
necessarily.

Statistics work great over large populations of search queries when
searching. An example from today (May 24, 2013) of searching for a word
like "Skagit", or "bridge collapse" (in the news from Washington State
USA) brings up great results on the WWW because of dynamic changes in
searches for those terms etc., but "popularity" and other learning
algorithms can get curious or misleading results in a department or a
division. This is just one example of where fantastic high-end advanced
algorithms are great for the WWW but don't all apply to enterprise data
sets.

It seems to me that lack of faceting would pretty much be a deal breaker
for me. In a large enterprise, as a user, MOST of my searches would be
for things in my division or department, I'd really get tired of having
to trick the engine by always remembering to use something from the
path, title, text that IDs my region, division, area of interest etc.

-Paul

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Excellent observations Paul, thank you. Added to my list.

I believe GSA has pretty good access control but it is based on URL pattern
which is pretty useless to us :slight_smile:
Yes learning algorithms will be entirely useless to us. we have

On Fri, May 24, 2013 at 12:31 PM, Paul Hill parehill1@gmail.com wrote:

On 5/24/2013 8:29 AM, Alex Roytman wrote:

Precisely my thoughts Matt, thank you! I have already crafted a draft
response along these lines just wanted to get some confirmation from the
user community that I am not missing existing GSA features and strong
points missrepresenting its value in my desire to stick with ES

I also understood that GSA has no ability to deal with access control
which you could provide in an ES product be it in-house or 3rd party.

Another issue is that it brings several parts of the web algorithms to the
enterprise. At first this sounds like a feature, but it is not
necessarily.

Statistics work great over large populations of search queries when
searching. An example from today (May 24, 2013) of searching for a word
like "Skagit", or "bridge collapse" (in the news from Washington State USA)
brings up great results on the WWW because of dynamic changes in searches
for those terms etc., but "popularity" and other learning algorithms can
get curious or misleading results in a department or a division. This is
just one example of where fantastic high-end advanced algorithms are great
for the WWW but don't all apply to enterprise data sets.

It seems to me that lack of faceting would pretty much be a deal breaker
for me. In a large enterprise, as a user, MOST of my searches would be for
things in my division or department, I'd really get tired of having to
trick the engine by always remembering to use something from the path,
title, text that IDs my region, division, area of interest etc.

-Paul

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