Elasticsearch is a distributed, RESTful search and analytics engine capable of solving a growing number of use cases. As the heart of the Elastic Stack, it centrally stores your data so you can discover the expected and uncover the unexpected. Elasticsearch lets you perform and combine many types of searches — structured, unstructured, geo, metric — any way you want.
| Support | 24/7 (Live rep) Business Hours Online | Customer Type | Large Enterprises Medium Business Small Business |
| API | Location / Phone Number | Mountain View, California / +1 650 458 2620 | |
| Deployment | SaaS/Web/Cloud | Category | Site Search Software |
Disclaimer: The pricing details were last updated on 07/06/2019 from the vendor website and may be different from actual. Please confirm with the vendor website before purchasing.
Elasticsearch is Site Search Software. Elasticsearch offers the following functionalities:
Learn more about Elasticsearch features.
Yes, Elasticsearch provides API.
Most likely functions are fuzziness, synonyms and other all functions. Review collected by and hosted on G2.com.
There is nothing that I can say that dislike this product. Review collected by and hosted on G2.com.
I am recommending to use Elasticsearch and move your application backend side (I mean the part where frontend call to backend retrieve a data) to Elasticsearch Review collected by and hosted on G2.com.
It's easy to use, I am switching my application backend API call side to ElastSearch. Review collected by and hosted on G2.com.
Elastic search worked on the top of Lucene Engine .Elastic search is an open source search engine which is very good in performance. As Elastic search is a document oriented database that is why it worked on full text search that is why it is fast in searching . I like the performance of elastic search.
Till now everything is good, I personally feel good while using elastic search.
I used elastic search for searching logs while implementing ELK stack to monitoring logs. I feel elastic search good because it is very fast in searching and also scalable.
Elasticsearch support JSON format which makes it a lot easier for developers to integrate it with the backend. It has a powerful REST API and creates redundancy to avoid the loss of data.
When doing many search request, the server shutdowns sometimes. Also, the speed of accessing the data even when using the bulk API is low.
I advice anyone looking for a NO--SQL search engine supporting document types to take a look at elasticsearch. Its not hard to setup and I'm sure you will not regret it.
I worked on elasticseardh during my internship. My Job was to create a NO-SQL clusters and store data comming from an ETL tool in them. I choosed elasticsearch because it support document types and has a very powerfull java API.
Elasticsearch is NO-SQL search engine full of features and support document format. It support REST API and makes it easy for user to send a search request using any language (backend). Also, if the document type is not recognized by elasticsearch, it adds it automatically which is awesome. Furthermore, the fact that elasticsearch output the search request result in JSON format make it a life saver especially for front-end users.
Honestly, I can't think of any major bugs or cons worth mentioning but I would say that the document upload speed (even using bluk) is a bit slow.
I advice anyone looking for a NO-SQL search engine which stores its data as documents to go for elasticsearch, it is really easy to implement and the fact that it support json format makes it easy for anyone to parse the search result to the front end
I used elasticsearch during my internship at tunisia in sagemcom company. my task was to create a NO-SQL cluster with document format and store certain log files and data in it Since elasticsearch supported document format, I went for it and it was a really good decision. Now, I have my own search engine with multiple cluster (also backups) and the data stored can be accessed easily by using a search API and parsing the JSON result.
Elasticsearch website has a very good documentation. It makes everything easier and clear. The No-SQL search engine uses "document" as a storage type and can recognize any new document type (it adds it automatically). It has apis practicly for every programming language such as java, c++. I like also how it makes cluster and always back up the data.
Well, I think that elasticsearch should support more ETL softwares such as talend. Also, when implementing Kibana with elasticsearch, sometimes the data is not updated instantly and I have to restart the whole server or wait some time.
If you are looking for a NO-SQL search engine, I recommend using elasticsearch. It is easy to implement and uses the document structure to store your data. Also, it is flexible and can add all new documents even if their structure is not pre-defined. I used the documentation in the official website when implementing it and it made everything easier and clear.
I used elasticsearch, specificly its java api, to integrate it with an ETL tool. The ETL tool extract several data from various type of files and store in the elastic search search engine. My data become accessible everywhere and organized in my own structure. Also I used the Bulk feature in the java API, this way my data is uploaded faster.
Don't let the name fool you. It's not just for search. It does a lot more! Running analytical queries are blazing fast. Filtering, segmenting and classifying data is ultra-quick.
A query builder package for Javascript would be really useful for developers. We had to manually write a wrapper for it.
We have used Elasticsearch to build trend reports, quick filters, and insight engines. All the queries were super fast.
Elasticsearch solved our scaling problems. Postgres started becoming sluggish after a few thousands of entries for analytical queries. Elasticsearch was always blazing fast for us.
Its search engine, its best for indexing whole document and search word by word
Have cluster capability
Latest version is very stable
it has the feature to separate the indices based on the category of the metrics or logs we dealing with
it provides various features to customise the restart capabilities
its hard to achieve performance, not enough direction on benchmarking the performance. Faced lot of issues with stability and resiliency of the cluster
Has issues with older versions of es with respect to resiliency, cluster management etc
has issues in understanding some of internal
use it in right way, use it only for search engine purpose not for any time series or sql way
Store and search through logs
we also store and retrieve counters
analyse data
helps to achieve good search, ranking, scoring etc
Apache Elasticsearch is very fast search engine. It is very easy to use. It is real time, open source and distributed. Its response time is in milliseconds. It is json based on search engine. It also has HTTP web interface. Elasticsearch is developed in Java. We have many java libraries available to access Elastic search for example Jest client. I also has Kibana which is an open source data visualization plugin for Elasticsearch.
Nothing as such. Only the Elasticsearch json queries we need to learn before using this.
There are other search engines in the market, Cosmos DB is one of them, but costly to use. This one is easy to use and 2 digit millisecond response time. So please go for it.
It is document based, that is no-sql. It helps to me search, filter and sort the data in real time. If we manually implement such then that may cause serious performance issue. It can be used as a document based database as well.
Apache Elasticsearch is very fast search engine. It is very easy to use. It is real time, open source and distributed. Its response time is in milliseconds. It is json based on search engine. It also has HTTP web interface. Elasticsearch is developed in Java. We have many java libraries available to access Elastic search for example Jest client. I also has Kibana which is an open source data visualization plugin for Elasticsearch.
Nothing as such. Only the Elasticsearch json queries we need to learn before using this.
There are other search engines in the market, Cosmos DB is one of them, but costly to use. This one is easy to use and 2 digit millisecond response time. So please go for it.
It is document based, that is no-sql. It helps to me search, filter and sort the data in real time. If we manually implement such then that may cause serious performance issue. It can be used as a document based database as well.
Very good REST API support to search and index documents/ data. The documentation is pretty solid and verbose as well which makes it easy to understand and write queries. Very good support for issues. They even released elastic cloud recently which makes it even better to set up clusters and interact with your data.
Wish the REST browser plugin was still supported. But it's fine without it as well
Search of product configs
