Bewertet am 16.11.2019
Great solution for implementing searching over vast amount of data!!
Kommentare: 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.
Vorteile: 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.
Nachteile: 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.
Bewertet am 13.9.2019
Scale, Features, Functionality.
Kommentare: 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.
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.
Nachteile: 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.
Bewertet am 7.1.2020
Kommentare: I've used elasticsearch to index text and some other data. Then it's easy to create different search queries based on text and/or other data.
Vorteile: It's easy to setup and create a poc with it. Elasticsearch search options are support mulpile diffrenet search options.
Nachteile: While creating indexes is easy, the optimization and what to index might be challenging. It requires quite a bit of fine tuning to be ready for production deployment.
Bewertet am 24.4.2019
Review for Elasticsearch
Elastic Search is easy to install
Easy to use as there are loads of documentations present online
Easy to scale up when the need arises
Uses REST FULL API which is light weight.
monitoring of Elastic Search are complex like wise administration
Installation of elastic search on windows OS is not straight forward
Bewertet am 26.5.2019
Best search engine on the market
Adam victor B.
Kommentare: 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.
Vorteile: 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.
Nachteile: Mostly for developers: other people would have a hard time with it.
Bewertet am 3.12.2019
Working On Big Data Is Now More Comfortable
Kommentare: 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.
Vorteile: 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.
Nachteile: The only feature I don't like is that it is Java based.
Bewertet am 3.12.2019
Have too much data to your database?
Luis felipe A.
Kommentare: Our application makes many filters for too much data, without Elasticsearch it just stops
- Almost 100% of uptime
- Great support
- Really fast and easy to use for any application
- Easy to configure
- 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
Bewertet am 4.6.2019
Elastic-search is a distributed, Restful search and analytics engine.
Kommentare: Elastic-search is a distributed, Restful search and analytics engine.
Vorteile: Elastic-search has an important security layer to separate access to data and dashboards.
Nachteile: A bit more of a learning curve for complex searches, indexing more complex things.
Bewertet am 31.12.2019
Best tool for your logs
Kommentare: We are using Elasticsearch along with Logstash and Kibana. This setup provides great tool for parsing and searching through a tons of logs which are centralized in Elasticsearch.
*Very big community base
*Elasticsearch is open-source
*Very powerful REST API
*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.
Bewertet am 13.12.2019
Great solution for searching data
Kommentare: Elasticsearch is used as part of the ELK stack and we used it mainly to search logs.
Vorteile: It's a great tool for managing application and server logs at large scale. Combined with Kibana as part of the ELK stack it is very powerful and extremely useful.
Nachteile: It can be difficult to understand at first when using it and when setting it up, but once configured correctly it does a great job.
Bewertet am 5.9.2018
Essential tool for all my devops needs
Vorteile: 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.
Nachteile: 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.
Bewertet am 11.1.2019
Elasticsearch is a general purpose search engine that can do much more than search
Kommentare: 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.
Vorteile: 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.
Nachteile: 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.
Bewertet am 24.4.2019
Great for indexing a large amount of data
Kommentare: 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 indexes. This keeps the number of shards low. If we don't do this we run into problems because if to many shards. But, you can schedule this via curl and with every new version of Kibana/ElasticSearch you can do more and more via the GUI. For us this is the number one tool to index and search gigabytes of logs on a daily base and we're able to keep months of logs and still be able to search through it.
Indexing large amount of data
Creating a cluster is very easy
Ability to send commands via CURL to the API
Creating snapshots of your data
Managing indexes can be a bit of a pain
Sometimes issues with indexes becoming read only
Bewertet am 29.6.2019
One stop solution for all the heavy search operations across huge set of data
Kommentare: It's been great!
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 :)
Nachteile: The memory optimisation related issues could be alarming sometimes if not taken care of properly. You may end up having some weird system crashes.
Bewertet am 12.3.2019
The perfect searching allied to a RDB
Kommentare: 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.
Vorteile: 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.
Nachteile: 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.
Bewertet am 24.1.2019
Elasticsearch Makes Big Data Possible
Kommentare: We've dramatically improved the stability of our big data analytics compared to any other data store we've used.
Vorteile: 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.
Nachteile: 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.
Bewertet am 23.8.2017
Elastic Search is built on top of Lucene, it provides the most powerful full-text search capability
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.
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.
Bewertet am 20.6.2019
Using ELK stack for monitoring and logging
Kommentare: 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.
Vorteile: 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.
Nachteile: Nothing really comes to mind. The only thing is Json is mandatory data format unlike the Apache Solr which is a competitor.
Bewertet am 18.3.2019
Searching made easy when you need it the most.
Kommentare: and look for log files and then find the issue. ELK sovles this problem efficiently.During troubleshooting, it is biggest pain to open servers
Vorteile: 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.
Nachteile: 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.
Bewertet am 9.8.2017
Best product for search and aggregations
Great full text capabilities.
Highly scale able .
Good set of libraries.
The search is very good and very fast in response.
Documentation is very good for writing NoSQL queries.
Libraries are there for 90% of popular languages.
It would be good to create a standardization for NoSQL.
It would be great, Elastic search provides IDE to write the queries rather than editors.
Bewertet am 28.6.2018
Managing big databases
Vorteile: 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.
Nachteile: I leas like the Elasticsearch itself does not provide much except just storing the information, the additional tools (Kibana and Logstash) are required.
Bewertet am 16.1.2018
One of the best text-based search products in the marketing.
Adam victor B.
Kommentare: We get to solve our search scalability problems on our on-premise product with the ease and consistency of Elasticsearch.
* Easy to use, especially when compared with alternatives s.a. Solr.
* Free software.
* Elastic has a great customer support.
* It is very powerful, supporting heavy loads.
* Demands a specific knowledge of the theory of search.
* While way higher level than most services, it is not as high level as, let us say, a Google search.
* Often used as a NoSQL in inappropriate settings.
Bewertet am 30.11.2018
Vorteile: 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.
Nachteile: Its really easy to make your performance really low, you have to be really careful with your cluster setup, mapping and queries.
Bewertet am 16.11.2018
ElasticSearch - Modern NoSql datanbase
Kommentare: We are building a new and next generation product and we are using elastic in all search or autocomplete area of the application. Its really fast and powerful tool.
Vorteile: ElasticSearch is one of the most popular and fastest growing NoSql data store. one of the best feature we are using is to search and return data quickly. Schema less is making its most powerful features and base of this entire product.
Nachteile: Only cons we are facing right now is its major version Upgrades and breaking change.
Bewertet am 21.2.2019
A revolutionary tool for web applications
Kommentare: By using RoR as a platform we use wrappers developed by Elasticsearch. This is a great, well-documented solution for a quick start, a great help to the developers.
Vorteile: As a web developer, I have been looking for opportunities to make our apps better, smarter and more developed. Elasticsearch made a revolution in our business by providing complex filtration systems and search, which weren't easy to implement previously: too much code and server consumption. Our products got better, we make good money and save our time.
Nachteile: I still haven't figure the implementation of replication and clusterization of Elasticsearch, but maybe it is a lack of information.