Elasticsearch Reviews

It's a great tool to setup a search platform almost of any size in a company. I have worked with Apache Lucene and Elasticsearch just saves all that trouble of dealing with the indices all the time in Lucene and rather provides seamless integration through APIs for search queries. It was really easy to setup the cluster and shards and manage the stack. The APIs offer a wide range of search features and saves a lot of effort coding hundreds of line for every small advanced search filtering function.

The documentation of the APIs could be improved. It was a bit overwhelming at times to lookup the correct functionality we wanted to actually implement. The tutorials and courses are quite expensive.

This is best search software for data searching and analytics on stream data in cloud. It is so flexible complex keyword searches and very efficient. Great tool for analyzing logs very powerful. 24/7 customer support.

Not really a negative side but if you have low bandwidth web interface will become very slow.And think learning manual still needs some improvement.

I loved how easy this was to spin up and get going in our environment with minimal research, trial, and error.

I think to cluster Elasticsearch was my least favorite part about the implementation. there were a lot of "nitty gritty" config details to be ironed out

A consolidated UI to search and find the patterns in log file. Speed of search return is also very good. The way this product manages the files at the backend, it does conserve a lot of space considering the amound of data it stores.

Search pattern bar could be more user friendly. When the load increases, serach bar is the first to show impact and starts to deviate from an efficient behaviour. Cursor keeps going away during such times making it difficult to tweak the attern.

We were looking for a solution to help us store and sort documents. We have a large dataset that needs to be organized and quickly sortable by end-users. Confidentiality is also a key requirement. Elasticsearch fit the bill, it's very easy to setup and also quite scalable. We are working with the 6.8 version of Elasticsearch and find it to be robust and resilient. There are a LOT of features that we haven't even tapped yet. The UI is fast and performant, we integrated Grafana for its dashboarding capabilities.

Filtering and searching does require some ramp time to understand the syntax. ES comes with a lot of features so it can be overwhelming at first. Hit a UI glitch with 7.x which is why we rolled down to 6.x. Support is community unless you want to pay.

The product is very popular among many companies, therefore there is a big community who can share their knowledge, the search is very fast and the installation process and integration are very easy.

I leas like the Elasticsearch itself does not provide much except just storing the information, the additional tools (Kibana and Logstash) are required.

Its a really good solution for people looking to process large volumes of data, it allows to filter, make aggregations and other operations really fast even when you need to rely on text search.

Its really easy to make your performance really low, you have to be really careful with your cluster setup, mapping and queries.

The flexibility, it's free, large community and plenty of tools

You have to use 3rd party tools in order to make the best of it (management mainly).
It's JAVA, so GC could be an issue.

It's simply the industry standard for search. The extensive functionalities make complex problems look easy.

Documentation could be a bit more helpful, especially in dealing with breaking changes.

ElasticSearch provides some of the mos accurate & fast search results of the market. We moved from a Sphinx installation into ES and have never looked back. Multiple indexes, lots of querying options & great support from tooling.

Can be a bit hard to get into at first. However, the product is very well documented, so you just need to invest some time in their docs.

Mainly it an open source.
Improved Scalability with full-text search, sharding & Aggregations.

When it comes to querying, it's less flexible comparing to PostresSQL.
Not much recommended as a "Data Store" when comparing to Hadoop or MongoDB.

If you worked in a big online store on the analytics side you can really understand the hard work that this software is doing, and the value that it adds to your conversion rate.
It has great potential and used in combination with Kibana it proves a very good choice for fast and great search results.

Depending on your users conversion rate and volume it can become a high cost operation, if you have low margins.

*Very big community base
*Elasticsearch is open-source
*Very powerful REST API
*Well documented
*Easy to install, just a few commands
*You do not need knowledge of databases
*Elasticsearch can be integrated to 3rd-Party software.

*For some of premium features (included in X-pack) you must buy subscription, which cost too much money.
*If you want subscription, least number of licensed nodes must be more than 3.
*

The flexibility provided for the configuration of the indexes and the searching criteria makes it suitable any kind of data and search needs. The query building flow is also easy to understand.

A server crash could result in a total
loss of data, so it can’t be used to store important data.

A great option for an in-memory database. The documentation is very complete and concise, making even some hard topics very easy to work with. It has SaaS/PaaS options if you have to migrate or don't want to grow up your development team.

Sometimes the documentation is a little bit confusing, because they give you every version option, and you have to look carefully to not read other versions syntax and DSL.

Best storage for searching, very quick in response
Documentation is good
Highly scalable
Good command line interface for administration

NoSQL help is not much clear with samples.
Not suitable for transactions.
Every NoSQL db has different standardization that makes little irritating
Not suitable for single pc installation

Indexing is Fast
Replacing the RDBMS is good
Retrieval of records are fast
Easy to install and configure

Term is very confusing (i.e. should, must)
Query Structure is very complicated.
Built-in GUI Component should be there

It is very easy to integrate with javascript projects because it stores data in json format. Querying is easy with lot of selectors and modifiers available.

Reindexing is very time taking due to which there is data mismatch sometimes.

Excellent to use smart text, to management number of impression on search, distribution of data, autosuggest, soundex search. So more efficiently and quickly than search on a data base.

It has not a table of error, errors are so much generic. Documentation is very ambiguous and so short.

Elasticsearch is a open source platform which we can use for multiple kind of projects.We have used the platform to have centralized log managing ability and as a replacement of our OLAP databases.We can have in-detailed analytics with the aid of Elasticsearch platform. Also, we can have highly performed powerful search engine with fast indexing ability.

It would be great if we have more detailed documentations and learning materials to learn this kind of valuable technology.

It's an inexpensive solution that's easy to configure for searching of complex content like major support portals.

There is quite a lot of initial setup, as you'd probably expect, although the results we got made it worth the effort.

Qbox.io supports AWS and RackSpace

Qbox.io doesn't offer enough support for automatic scaling

Very easy to set up and lean working with its interface. Tones of plug-ins for displaying data/graph analytics. It performance seems to be faster than solr on the same data. AND its opensource

Querying is not that simple and you will need to spend some time to get the hang of it for advanced use.

Scale: You can run this from a single server or even co-installed on a database or file server. I wouldn't recommend it, but let's just say it will run in a small box. On the top side, Elasticsearch will run in clusters managing multiple Terabytes of data.
Features: Excellent flexibility to absorb multiple types of data sources, and great integration with Logstash and Kibana.

The upgrades in terms of archived data. This platform changes significantly on an annual basis. If you do a ton of customization, automation, or work with a lot of data, this can be an issue as you will need to update ALL of your data for every upgrade.

I've been using Elasticsearch since early days, with very different things in mind.

I started with simple text search - with some additional tweaks, stemming and other cool features it helped us drive enormous traffic to our website. I can't imaging pulling it off so easily with any other tool.

Every day I use it for web server log analytics. Search and great visualizations make it an absolute essential in work my toolset.

We also run a lot of algorithm analytics on top of our Elasticsearch cluster.

If you're looking for managed options check AWS Elasticsearch Service, or the recently introduced Elastic Cloud.

My only concern with Elasticsearch is that it might get expensive to run pretty quickly. But with a certain amount of effort put into optimization it's gonna be worth it.