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Elasticsearch 1.0.0 released

elasticsearch.org

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Re: Elasticsearch 1.0.0 released

#31

Post by sjs382 »

axefrog wrote: post #18
RyanZAG wrote: post #7

Elasticsearch is really awesome for searching, but what most people don't realize is that it makes a better MongoDB than MongoDB while giving you that searching too.

What limitations should one be aware of that would make ElasticSearch not a viable candidate where something like MongoDB would be a better fit?

I'm not sure if ElasticSearch does anything like this, but I make use of MongoDB's GeoJSON queries, namely the $geoIntersects operator.

http://docs.mongodb.org/manual/applications/geospatial-index...

Re: Elasticsearch 1.0.0 released

#33

Post by sjs382 »

sjs382 wrote: post #31
axefrog wrote: post #18

Earlier quoted context omitted.

What limitations should one be aware of that would make ElasticSearch not a viable candidate where something like MongoDB would be a better fit?

I'm not sure if ElasticSearch does anything like this, but I make use of MongoDB's GeoJSON queries, namely the $geoIntersects operator. http://docs.mongodb.org/manual/applications/geospatial-index...

Wow, it looks like they do... http://www.elasticsearch.org/guide/en/elasticsearch/referenc...

Re: Elasticsearch 1.0.0 released

#34

Post by RyanZAG »

ddorian43 wrote: post #20
axefrog wrote: post #18

Earlier quoted context omitted.

What limitations should one be aware of that would make ElasticSearch not a viable candidate where something like MongoDB would be a better fit?

presharding You create a number of shards for each index(database) that you can't later expand.

Is this still a limitation? I haven't run into any use cases where this has been a problem yet. Since the default shards are 10 and 2 replicas, does that not mean each index should be able to scale up to 20 servers? I'd think that if your data grew enough that 1/10th does not fit on a server, you could do a one time maintenance and rebuild all your servers.

I have my doubts mongodb would scale up that well to 20+ servers without some maintenance as well. So I'm not sure how that's really a limitation anyone should use for choosing mongodb or ES. If you're expecting that kind of data, just make a large number of shards in your index creation as it will work fine on fewer servers too?

Re: Elasticsearch 1.0.0 released

#35

Post by polyfractal »

sjs382 wrote: post #33
sjs382 wrote: post #31

Earlier quoted context omitted.

I'm not sure if ElasticSearch does anything like this, but I make use of MongoDB's GeoJSON queries, namely the $geoIntersects operator. http://docs.mongodb.org/manual/applications/geospatial-index...

Wow, it looks like they do... http://www.elasticsearch.org/guide/en/elasticsearch/referenc...

In addition to the various geo filters/queries, there are also two aggregations for geo related stuff:

Geohash Grid: http://www.elasticsearch.org/guide/en/elasticsearch/referenc...

Geodistance: http://www.elasticsearch.org/guide/en/elasticsearch/referenc...

Re: Elasticsearch 1.0.0 released

#36

Post by RyanZAG »

nzadrozny wrote: post #29
bryanh wrote: post #27

The thing that worried me the most about Elasticsearch was how fragile it got around the limits of its performance. Run out of memory because of a nasty query? Boom, data corrupted. I hope you weren't using it as your primary persistence layer... Otherwise, we love ES. The other comment about it being a better Mongo than Mongo rings true. With the backup/restore API and the some of the circuit breakers, I'm hopeful t…

Ditto open file handles, which is easy to push when aggressively over-sharding. Not an uncommon mistake for the enthusiastic newbie. Having supported Solr/ES/Lucene in production for 4+ years now (websolr.com / bonsai.io) I would be pretty hesitant to trust Lucene in general as a primary data store. Beautiful for secondary indexing, but otherwise, Why Not Postgres?™ ;)

Complexity. Having two copies of the data means more dev time, more resources required to shift the data around, etc. Having just 1 data store that can also handle all your searching is like the holy grail. As you say, not sure if Solr/ES/Lucene are there yet - but they're definitely very very close. There is no theoretical barrier either - it just comes down to closing bugs, and the ES/Lucene team are very good at closing bugs.

EDIT: I don't think MongoDB is there yet either. There are definite benefits and drawbacks between Postgres and ES, tipping heavily towards Postgres for structured heavy write data. But for ES and MongoDB? I think MongoDB falls a bit short there.

Re: Elasticsearch 1.0.0 released

#37

Post by morganherlocker »

sjs382 wrote: post #33
sjs382 wrote: post #31

Earlier quoted context omitted.

I'm not sure if ElasticSearch does anything like this, but I make use of MongoDB's GeoJSON queries, namely the $geoIntersects operator. http://docs.mongodb.org/manual/applications/geospatial-index...

Wow, it looks like they do... http://www.elasticsearch.org/guide/en/elasticsearch/referenc...

Might not matter, but they do not follow the geojson spec for spatial storage.

Re: Elasticsearch 1.0.0 released

#38

Post by g9yuayon »

RyanZAG wrote: post #7

Elasticsearch is really awesome for searching, but what most people don't realize is that it makes a better MongoDB than MongoDB while giving you that searching too.

I don't know much about MongoDB, but it's true that Elasticsearch is a great NoSQL db with support of boolean search. Netflix has a number of use cases that use Elasticsearch as such NoSQL db: http://www.slideshare.net/g9yuayon/elasticsearch-in-netflix

Re: Elasticsearch 1.0.0 released

#39

Post by sandGorgon »

RyanZAG wrote: post #7

Elasticsearch is really awesome for searching, but what most people don't realize is that it makes a better MongoDB than MongoDB while giving you that searching too.

I had a live production logistics system running on top of Elasticsearch 0.6 (as a NoSQL database ) back in 2012. This powered one of India's largest ecommerce systems (at that time).

Elasticsearch is brilliant as a NoSQL - and if you were already using elasticsearch as a search system, you dont need to introduce yet another component into your stack.

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