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Elasticsearch

Distributed search and analytics solution

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Elasticsearch Reviews

Reviews summary

Pros

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.

Keren K.

Flexibility and high performance are the most loved features for us. The fact that we are not using it very effectively is also a ramen of suggestions and guidance.

Onur E.

Features: Excellent flexibility to absorb multiple types of data sources, and great integration with Logstash and Kibana.

Jim N.

Cons

Mostly for developers, other people's would have a hard time to understand and work on it. Also the query is typical or hard to write in terms of SQL queries.

Neelesh B.

The cost of product may inviabilize it's use for small applications or companies. If the configuration goes wrong it may really affect the speed.

Luis Felipe A.

We had lots of network-related log files with millions of records to be processed and identify errors, user activity, and many other pieces of information.

Anonymous Reviewer

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99%
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102 reviews

recommended

Overall Rating
  • Value for money
  • Ease of use
  • Features
  • Customer support
  • Likelihood to recommend9/10

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Best search engine on the market

Reviewed 2 years ago

I work with Elasticsearch as a developer on a daily bases for textual search. It is the greatest tool I've used in years. Really like it.

Pros

It is just the best back end for search engines in the market. A NoSQL database that is trustworthy. Also, it is open source. Incredibly easy to use.

Cons

Mostly for developers: other people would have a hard time with it.

Overall Rating
  • Value for money
  • Ease of use
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  • Customer support
  • Likelihood to recommend10/10

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Scale, Features, Functionality.

Reviewed 2 years ago

Excellent. The ELK stack is the foundation of our audit process, and it's held up really well. The installation can be automated, and archiving in the AWS environment works quite well. We have not yet had a problem in scaling resources to match our resource needs. The integrations with logstash, beats and kibana have been excellent, and used to great effect.

Pros

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.

Cons

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.

Overall Rating
  • Value for money
  • Ease of use
  • Features
  • Customer support
  • Likelihood to recommend7/10

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One of the best data indexing software to look for

Reviewed a month ago

Very positive experience. Easy to learn and use. Highly recommended.

Pros

I have used Elasticsearch for one of the research projects - Visual Search and Autonomous Linkage Tool which would enable Autonomous Data Processing and to improve Big Data Analysis and Reporting, in my previous work place. It served the best in driving the product to it's success with it's great capability and accuracy of indexing data.

Cons

No much negative experience to highlight but sometimes have to deep dive into documentation to learn about more features and their functionality.

Overall Rating
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  • Likelihood to recommend5/10

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Decent Data store but lot of scalable issues

Reviewed 8 months ago
Pros

Its decent search to NOSQL DB and I find it good for content management

Cons

it has scalable and reliability issues. I would not recommend this for your SOR

Overall Rating
  • Value for money
  • Ease of use
  • Features
  • Customer support
  • Likelihood to recommend10/10

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Superb search, logging, and analytics platform

Reviewed 3 months ago

Searching a database of parameterized data to provide results to buyers. Ingesting millions of product updates on a daily basis from dozens of distributors. Logging and analyzing user activity for business metrics, system performance, and security. Elasticsearch has been a vital tool for all these use cases.

Pros

Search functionality is our basic need, and Elasticsearch nails it - scalable, fast, efficient. It is also good at logging, aggregation, and analytics when used in combination with the rest of the Elastic stack.

Cons

It's complex and can be a challenge to dial in performance unless you have a really vanilla use case. Docs are light on details and examples, so there is a fair amount of trial and error.

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  • Value for money
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  • Likelihood to recommend9/10

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Blazing fast in searching through a lot of data!

Reviewed 6 months ago

I am extremely satisfied with Elasticsearch, its speed & querying capabilities among lots of data amaze me!

Pros

The fact that Elasticsearch offers really efficient & quick querying of data without a compromise on the different range of queries it can support is really awesome, also Elasticsearch can rank matching documents based on matching criteria which is also very useful. Elasticsearch also handles distributed queries very efficiently.

Cons

Reindexing documents can be a real pain if there is a major change in the schema, otherwise no complaints.

Overall Rating
  • Value for money
  • Ease of use
  • Features
  • Customer support
  • Likelihood to recommend9/10

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Best way to process application log data

Reviewed 10 months ago

We had lots of network-related log files with millions of records to be processed and identify errors, user activity, and many other pieces of information. If we didn't have Elasticsearch its a nightmare to process those. With the help of Elasticsearch, we were able to process those and even visualize them with nice graphs and charts. ultimately we were able to build an automated alerting system when there is an error or unusual user activity in the network system.

Pros

It's really easy to set up and there are not many configurations need to get started with. It comes with other supporting tools such as Filebeats to collect the logs from the files, Logstash to ship data to Elasticsearch, and Kibana to visualize the data. It processes millions of data within seconds. Elasticsearch can be clustered with multiple nodes and it guarantees higher data availability. Elasticsearch has lots of proper documentation and community support. It's easy to integrate with programming languages such as Java

Cons

Elasticsearch doesn't provide backward version compatibility. We have to use the same version of Elasticsearch, Logstash, and Kibana. Data is getting saved as files inside Elasticsearch and those can get deleted. There is no easy way to edit the data.

Overall Rating
  • Value for money
  • Ease of use
  • Features
  • Customer support
  • Likelihood to recommend9/10

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Industry standard for search

Reviewed 9 months ago

As a developer, was using it for quite a lot of time for different projects and would say it is almost impossible to find an alternative for this product due to the fact it is the best product in the segment.

Pros

- the overall performance is great, easily handles big amount of data and provides near instant response times; - fail tolerance and high availability features out from the box; - open-source; - elk stack is mostly the best tool to analyze the logs of your applications;

Cons

- could be hard to setup / maintain even for technical people, so probably you will need to use some services which provide support and better analytics - migration between versions could require some additional efforts due breaking changes

Overall Rating
  • Value for money
  • Ease of use
  • Features
  • Customer support
  • Likelihood to recommend7/10

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Best open source search engine, offers fast and speedy search

Reviewed 4 months ago

Elasticsearch is an essential part of the our operations architecture.

Pros

Adding elasticsearch to most projects is a great way to have high performant full text or json document search. The common use case is for searching through log files (ELK or EFK stack) which is now the canonical way to handle logging for most distributed systems such as Kubernetes. Installing elasticsearch is not trivial but has been made much simpler in recent years due to being able to run ES in containers (i.e. helm charts). We use ES to accelerate general search, as well as being a core component in our logging stack.

Cons

There are many different configuration options available so there is still some ramp time required. There's also the issue of Elastic changing the licensing from Apache 2.0 to SSPL and Elastic. While this is probably not unexpected due to Amazon's predatory behavior when it comes to OSS and AWS, it doesn't help customers and the community to have two different projects.

Overall Rating
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  • Ease of use
  • Features
  • Customer support
  • Likelihood to recommend9/10

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One of the Best No sql Document Base Database

Reviewed 3 months ago

In our projects, we use elasticsearch in database queries that need fast answers. It is especially useful for search and autocomplete operations.

Pros

When you want to run queries in big data and get results, you can get results much faster from relational databases. Queries are also easy to create

Cons

We sometimes have problems during the integration of Kibana. But we couldn't figure out why Other than that, I didn't have any problems

Overall Rating
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  • Customer support
  • Likelihood to recommend10/10

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Great solution for implementing searching over vast amount of data!!

Reviewed 2 years ago

Elasticsearch helps in performing optimised searching over the vast amount of data present in your system. The configuration for Elasticsearch can have some learning curve, but once setup completely, the indexed searches are really fast as compared to other basic solutions and helps users in searching your system from vast amount of data. Its ideal for Big data and can be used in other e-commerce solutions also. Text searching is really fast and helps your system in maintaining performance and scalability over search operations.

Pros

Elasticsearch is a great solution for implementing optimised searches over the data you have lying in your databases. The setup and configuration is a bit tricky, but once you have configured the data points and the indexes, the search is lighting fast. You can go for the complete text search or for the autocomplete bases suggestions which can help your users to quickly search for the right things in your system.

Cons

The setup of Elasticsearch does have a learning curve for the developers, but the documentation is really helpful in getting you over the curve. Setting up indexes or data points for search can be tricky. Elasticsearch needs to setup a more proactive customer support so that developers who are facing deadlines, can easily sort their issues with the help of tech support.

Overall Rating
  • Value for money
  • Ease of use
  • Features
  • Customer support
  • Likelihood to recommend7/10

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A complete stack for full text search

Reviewed a year ago

Elasticsearch might be overkill if you are working with a small or mid-sized applications. However it's a serious solution for big-scale apps that are dealing with millions of records. The setup of the Elasticsearch might seem easy, but the maintenance is not. If you have simpler needs, I would suggest the full-text search functionality of modern PostgreSQL versions.

Pros

Elasticsearch is quite powerful and fast. You can implement it to any enterprise software independent of the scale. It's well documented and getting frequent updates. It's also a reliable software that you can use in mission-critical operations.

Cons

Breaking changes between different versions are hard to deal with. Each major version upgrade of ElasticSearch is bringing new functionality, improved security, and speed - but at the same time, it requires you to update your indexes, which is not an easy task if you don't have a strong infrastructure team.

Overall Rating
  • Value for money
  • Ease of use
  • Features
  • Customer support
  • Likelihood to recommend9/10

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Essential tool for all my devops needs

Reviewed 3 years ago
Pros

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.

Cons

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.

Overall Rating
  • Value for money
  • Ease of use
  • Features
  • Customer support
  • Likelihood to recommend10/10

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Working On Big Data Is Now More Comfortable

Reviewed 2 years ago

Our company uses elasticsearch to analyze data in very large data. Successful indexing is designed in a cluster (node) structure, which has made our work much easier. Thanks to this search engine, we can reach the desired analysis results in the data. It is a blessing for our sector employees to have a free application running in this performance.

Pros

Flexibility and high performance are the most loved features for us. The fact that we are not using it very effectively is also a ramen of suggestions and guidance.

Cons

The only feature I don't like is that it is Java based.

Overall Rating
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  • Ease of use
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  • Likelihood to recommend10/10

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Elasticsearch is a general purpose search engine that can do much more than search

Reviewed 3 years ago

We use Elasticsearch to filter and sort search results in our marketplace. We've built out many complicated queries that allow us to do interesting things like geo-based queries, personalization, and time boxed deals.

Pros

Elasticsearch offers a very flexible system for adding search capability to your systems. It is also capable of much more. The REST API and great documentation makes getting started very simple. Elasticsearch was also designed with scaling in mind. Adding nodes and self balancing is quite easy. AWS offers hosted Elasticsearch that makes spinning up your first cluster as simple as a few clicks.

Cons

Writing complicated queries can be quite tedious at times. The JSON interface is not always easy to read when trying to match up parentheses. Upgrading from older versions is not a simple process.

Overall Rating
  • Value for money
  • Ease of use
  • Features
  • Customer support
  • Likelihood to recommend9/10

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Great for indexing a large amount of data

Reviewed 2 years ago

We're ElasticSearch mainly to index large amount of logs from several servers. Its makes it very easy for us to index and search logs. Logstash sends the logs and with Kibana we access to logs and create nice dashboards. But, you have to manage your indexes. For our log an index is created every day which we reindex monthly to a new index, then we do a forcemerge and after that we delete the daily...

Pros

Indexing large amount of data Searching data Very scalable Creating a cluster is very easy Ability to send commands via CURL to the API Creating snapshots of your data

Cons

Managing indexes can be a bit of a pain Sometimes issues with indexes becoming read only

Overall Rating
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  • Ease of use
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  • Likelihood to recommend10/10

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One stop solution for all the heavy search operations across huge set of data

Reviewed 2 years ago

It's been great!

Pros

As a backend developer, I know for a fact that I can rely upon elasticsearch for all the times when I have to support search based on string across the database. You throw some set of documents to elasticseatch, and you are good to go to search anything amongst the provided documents. They have some supercool features to support string based search for say support for distributed systems, support for aggregations and analysers & folding, etc. The documentation out there makes it lot easier to get going with it :)

Cons

The memory optimisation related issues could be alarming sometimes if not taken care of properly. You may end up having some weird system crashes.

Overall Rating
  • Value for money
  • Ease of use
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  • Customer support
  • Likelihood to recommend9/10

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The perfect searching allied to a RDB

Reviewed 2 years ago

We've been pairing Elasticsearch with a traditional RDB in many projects with great results. This way we don't compromise our data reliability and searching speed is blazing fast.

Pros

Searching is where elasticsearch is second to none, either in terms, n-grams or full-text. Latest releases have greatly improved the aggregation performance, so it's also a great fit for analytics workloads. The customizable sharding and replica configurations make is very reliable too.

Cons

Searching and joining different documents has room for improvement, it's usualy not as fast as we would like it to be, so most of the times we end up un-normalizing documents and en-richening their data to boost searching performance.

Overall Rating
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  • Ease of use
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  • Likelihood to recommend8/10

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Highly recommended for search platforms

Reviewed a year ago

Setting up a search platform using Elasticsearch was super fun and easy. I was able to get some great search query response times and development efforts were minimal compared to dealing with Lucene directly.

Pros

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.

Cons

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.

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  • Likelihood to recommend10/10

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Elasticsearch Makes Big Data Possible

Reviewed 3 years ago

We've dramatically improved the stability of our big data analytics compared to any other data store we've used.

Pros

Elasticsearch is the single most valuable tool I have come across in my career for solving big data problems. No other datastore scales as well and as easily as ES. The premium features that come with a license are extremely powerful and definitely make a case for upgrading beyond just the need for support like most database solutions.

Cons

Elasticsearch definitely has a significant learning curve for developers and administrators experienced with a more relational database solution. However with some time and with the aid of the fantastic UI Kibana these hurdles are small in comparison to the power you can reap.

Overall Rating
  • Value for money
  • Ease of use
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  • Customer support
  • Likelihood to recommend8/10

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Elastic Search is built on top of Lucene, it provides the most powerful full-text search capability

Reviewed 4 years ago
Pros

Easier to horizontally scale Distributed by design Excellent full-text search Elastic Search is schema free'instead, it accepts JSON documents, as well as tries to detect the data structure, index the data, and make it searchable. Elastic Search is document-oriented. It stores real world complex entities as structured JSON documents and indexes all fields by default, with a higher performance result. Elastic Search is API driven; actions can be performed using a simple Restful API. Elastic Search records any changes made in transactions logs on multiple nodes in the cluster to minimize the chance of data loss.

Cons

Elastic-search query DSL is less common and less flexible than Postgres SQL . Everything is indexed by default, which creates an index overhead. in order to understand how to properly query your data and how it is stored, you have less control over consistency.

Overall Rating
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  • Ease of use
  • Features
  • Customer support
  • Likelihood to recommend9/10

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Distributed Search and analytics engine available in cloud

Reviewed a year ago

Best search and analytics software available in cloud, flexible to use and available free trial to evaluate it.

Pros

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.

Cons

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.

Overall Rating
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  • Ease of use
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  • Customer support
  • Likelihood to recommend10/10

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Using ELK stack for monitoring and logging

Reviewed 2 years ago

It has been really good. We only have JSON data and we stream it to the elastic search. We can search and index data as we need and it is really bast and performant.

Pros

This is the most awesome software stack for data analysis and searching. We stream data to the elastic search and index it so we can search it and analyse what we receive on the fly. It does the job extremely well. On top of that, the software comes as a managed service on cloud providers which means it comes with almost no maintenance overhead.

Cons

Nothing really comes to mind. The only thing is Json is mandatory data format unlike the Apache Solr which is a competitor.

Overall Rating
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  • Ease of use
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  • Likelihood to recommend10/10

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Searching made easy when you need it the most.

Reviewed 2 years ago

and look for log files and then find the issue. ELK sovles this problem efficiently.During troubleshooting, it is biggest pain to open servers

Pros

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.

Cons

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.

Overall Rating
  • Value for money
  • Ease of use
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  • Customer support
  • Likelihood to recommend9/10

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This is the best in the market.

Reviewed 2 years ago

Elasticsearch is one of the best in the market, it's efficient and highly scalable.

Pros

It's user friendly, considering the fact it has a complete stack (ELK) associated with it, which not only stores data, but collects log(Logstash) and it's capable of showing those data in it's visualization tool(Kibana).

Cons

I have not come across anything associated with this too that I did not like.