¿Qué es Elastic Stack?

Elasticsearch es un motor de búsqueda y analíticas RESTful distribuido basado en Apache Lucene, capaz de almacenar y buscar datos casi en tiempo real. Elasticsearch, Logstash, Kibana y Beats conforman la "Elastic Stack" desarrollada por Elastic. También se proporciona Hosted Elasticsearch (Elastic Cloud).

¿Quién usa Elastic Stack?

Herramienta de Big Data para empresas de todos los tamaños que ayuda con automatización, reequilibrado de datos, supervisión completa, registro de auditoría, filtrado de IP, API REST y mucho más.

Vídeo de Elastic Stack
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Opinones de Elastic Stack

Evaluación media

En general
4.6
Facilidad de uso
4.1
Atención al cliente
3.9
Funcionalidades
4.6
Relación calidad-precio
4.5

Opiniones por tamaño de empresa (empleados)

  • <50
  • 51-200
  • 201-1,000
  • >1,001

Encontrar opiniones por puntuación

5
65%
4
33%
3
2%
Isak
Developer en Suecia
Tecnología y servicios de la información, 11-50 empleados
Ha utilizado el software durante: Más de un año
Fuente de la reseña

Great tools for data visualization, aggregation and querying

5.0 hace 2 meses

Comentarios: The Elastic Stack allows our team to solve multiple problems, ranging from logging, to analytics and search.

Puntos a favor:

Provides a large and powerful set of features suitable for many different data-dependent areas. Superb support.

Contras:

Depending on use case it might be quite difficult to use - the most intuitive solution might not be the best at all.

Usuario verificado
Data Scientist en India
Usuario de Linkedin verificado
Tecnología y servicios de la información, 10,000+ empleados
Ha utilizado el software durante: Más de un año
Fuente de la reseña

Elastic Stack - A Complete Package for Big Data Visualizations and Fast Data Query!

5.0 hace 4 meses

Comentarios: Elastic Stack is a powerful platform which allows you to quickly search and query on the data even if the data is in huge volume, thanks to its distributed computing and storage. it has enabled me to develop an application which fetches results from TBs of data in seconds.

Puntos a favor:

1.Allows Faster searching and query operations 2.Provides with easy data visualization for analysis 3.Support for multiple data sources 4.Good SDK support for quick integration with application 5.Scalable as per the requirement with support of kubernetes

Contras:

1.UI is simple ,could be made more robust and dynamic 2.Calculations and processing speed can be further improved 3.Proper usage knowledge is required when using it on scalable platforms

Mo
Mo
DevOps Architect en EE. UU.
Usuario de Linkedin verificado
Tecnología y servicios de la información, 2-10 empleados
Ha utilizado el software durante: Más de dos años
Fuente de la reseña

Elastic Cloud on Kubernetes for best scalability

5.0 hace 8 meses

Comentarios: Organizing chat data to be searchable and log management to proactively fix issues.

Puntos a favor:

One of the best features I like is that Elastic built their own kubernetes operator to extend the k8s orchestration and make it easy to deploy, scale, change, secure and configure hot-warm infrastructures. Their operator saves a ton of time during configuration. I have deployed stacks on different k8s architectures like Azure Kubernetes Service, Amazon Elastic Kubernetes Service and small on prem clusters with microk8s without issues. When we reach performance thresholds we add more elastic nodes and ECK secures and joins it to the cluster and in minutes we can leverage the extra compute. A lot of changes that are done after going to PROD are non-disruptive since ECK is aware of the main node and makes sure to pass the master role before the main one is re-deployed. I have also migrated Elastic Cloud Enterprise deployments running on bare metal and the stability of ECK is unmatched.

Contras:

Currently it is not recommended or supported for a PROD cluster to do its own self monitoring so you have to deploy a monitoring cluster. In cloud scenarios this adds costs and extra complexity so it will be great to have this feature supported.

M. Serhat
Senior Software Engineer en Alemania
Aprendizaje en línea, 1,001-5,000 empleados
Ha utilizado el software durante: Más de dos años
Fuente de la reseña

A complete stack for full text search

5.0 hace 3 años

Comentarios: 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.

Puntos a favor:

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.

Contras:

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.

Usuario verificado
Senior Software Developer en EE. UU.
Usuario de Linkedin verificado
Hostelería, 201-500 empleados
Ha utilizado el software durante: Más de dos años
Fuente de la reseña

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

4.0 hace 4 años

Comentarios: 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.

Puntos a favor:

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.

Contras:

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.