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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.
http://www.elasticsearch.org/guide/en/elasticsearch/referenc...
I love when something I've been using in production for what seems like years just announces now that they've reached 1.0.
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.
(IMHO) Unfortunately for most of the people, old habits to be made. Indeed a nice project and great release.
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On ElasticSearch you have to update the whole document, no commands to manipulate them. You don't have commands like: $set, $addToSet, $pop, etc.. You need to have a good understanding of how tokenizers and analyzers work to be able to create good results for your data. I have difficulties matching documents with the exact title being searched for. On MongoDB that just works, on ElasticSearch you need to configure it…
>You need to have a good understanding of how tokenizers and analyzers work to be able to create good results for your data. This is really important. Creating a proper searching experience with auto-complete which works "just like you want" can be a very painful experience with ES, specially if you are new to ES. It bite me some time ago when I was trying to achieve just that.
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Might not matter, but they do not follow the geojson spec for spatial storage.
Sure, ES supports lat/lon as properties, strings, geohash and geojson: http://www.elasticsearch.org/guide/en/elasticsearch/referenc...
> Format in [lon, lat], note, the order of lon/lat here in order to conform with GeoJSON.
.. the data example below is not actually geojson. See the spec:
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This. A THOUSAND TIMES "This". The one drawback ES had in the bad old days was that backup and restore was a nightmare... ESPECIALLY on AWS. The new system they introduced was so simple I was concerned about updating to it because I was SURE something would go south. But it all just worked. I still have the Couch to ES replication running because I'm anal like that... but really... yeah... you can do without Couchbas…
to be fair, the main selling point of mongodb is that developers can access it more easily. i haven't really touched mongodb in over a year and then only for playing, but have you tried the elasticsearch filter query syntax? have you compared mongodbs syntax? also, i have the exact opposite nitpick. people want to use it to do everything, mail indexers, file system indexers. what's the matter with web developer folks…
Because they like a simple web stack. KISS means a faster time to market. Faster time to iterate. Faster time to fix bugs because there are fewer places those bugs can be. All of that doesn't even factor in the productivity benefits gained by not having to switch technologies from project to project.
But to be fair, ES is not some brand new database... ES has been around for a LONG time.
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Sure, ES supports lat/lon as properties, strings, geohash and geojson: http://www.elasticsearch.org/guide/en/elasticsearch/referenc...
I could be totally wrong, but the docs you linked to do not actually conform to the geojson spec. It is geographic and it is json, but not valid geojson. The part where it says: > Format in [lon, lat], note, the order of lon/lat here in order to conform with GeoJSON. .. the data example below is not actually geojson. See the spec: http://geojson.org/geojson-spec.html
Elasticsearch can map any kind of JSON, so you can, without problems, write a mapping for proper GeoJSON points. (map "type" as unanalyzed string, map "coordinate" as GeoPoint). Arrays of values are generally supported in ES.
The biggest problem is that Elasticsearch probably does not provide all kinds of queries you'd like if you are working with complex shapes. Basically, only distance and simple location queries with polygons are supported.
Beyond the technology, Elasticsearch has a very mature, active and helpful community with users groups all over the world. We're well connected. Pick your favourite users group here: http://elasticsearch.meetup.com/ Full disclosure: I started and run the Berlin UG. We set ourselves apart by always providing a small introduction into ES for those that are completely new and would have a hard time following the main ta…
I don't see many tutorials covering usage of ES here: http://www.elasticsearch.org/tutorials/
Could you maybe provide a link to yours?
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I could be totally wrong, but the docs you linked to do not actually conform to the geojson spec. It is geographic and it is json, but not valid geojson. The part where it says: > Format in [lon, lat], note, the order of lon/lat here in order to conform with GeoJSON. .. the data example below is not actually geojson. See the spec: http://geojson.org/geojson-spec.html
I think the documentation is not clear here. ElasticSearch has an internal GeoPoint type, which can be read from any kind of JSON document. One of the possible notations is the GeoJSON coordinate notation. Elasticsearch can map any kind of JSON, so you can, without problems, write a mapping for proper GeoJSON points. (map "type" as unanalyzed string, map "coordinate" as GeoPoint). Arrays of values are generally suppo…
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I think the documentation is not clear here. ElasticSearch has an internal GeoPoint type, which can be read from any kind of JSON document. One of the possible notations is the GeoJSON coordinate notation. Elasticsearch can map any kind of JSON, so you can, without problems, write a mapping for proper GeoJSON points. (map "type" as unanalyzed string, map "coordinate" as GeoPoint). Arrays of values are generally suppo…
Thanks for the explanation. Sounds like ES has equal or slightly more support for spatial stuff than MongoDB then (about as much as most people need).