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Elastic Search pros and cons

Vendor: Elastic

4.1 out of 5

66 reviews
97% willing to recommend

362 followers

Pros & Cons summary

Elastic Search enhances efficiency through log aggregation and real-time analytics, commendably handling large data volumes with scalability. Integration with data sources like Kafka supports diverse processing needs. Security features aid in analyzing alerts, but authentication improvements are needed. Licensing clarity, better documentation, and a user-friendly onboarding process are necessary for broader adoption. Enhancements in machine learning would optimize data handling and insights for tech buyers.

Buyer's Guide

Get pricing advice, tips, use cases and valuable features from real users of this product.

Prominent pros & cons

PROS

Elastic Search offers seamless scalability and high performance, making it adaptable to various infrastructure needs.

X-Pack provides essential features like authorization and alerts, enhancing enterprise-level operations.

Kibana integration allows for analytics configuration and visualization creation, facilitating data insights.

Elastic Search's stability and reliability are consistent, ensuring uninterrupted operation and performance.

The ability to efficiently process and index large volumes of unstructured data is a key strength of Elastic Search.

CONS

Enterprise scaling of separate FOSS products has been challenging, requiring additional add-ons like X-Pack and ECE to grow ELK to the required scales.

Machine learning on search needs improvement and better integrations with Cortex and QRadar.

Email notification capabilities are lacking, pushing users to alternatives like Logentries for server error alerts.

Elasticsearch needs better documentation and technical support, with improvements in licensing and pricing clarity.

Indexing issues occur as data volume increases, necessitating enhancements in performance management and scalability.

Elastic Search Pros review quotes

ED

Owner & director at Pulsar ICT

Jun 18, 2020

There's lots of processing power. You can actually just add machines to get more performance if you need to. It's pretty flexible and very easy to add another log. It's not like 'oh, no, it's going to be so much extra data'. That's not a problem for the machine. It can handle it.

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KB

Chief Data Scientist at Everlytics Data Science Pte Ltd

Nov 30, 2020

ELK Elasticsearch is 100% scalable as scalability is built into the design

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Enterprise Architect at DXC Technology

Jul 18, 2024

All the quality features are there. There are about 60 to 70 reports available.

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LK

Senior Solutions Architect at a tech services company with 51-200 employees

Sep 22, 2022

The solution has great scalability.

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Cloud and Big Data Engineer | Developer at Huawei Cloud Middle East

Nov 20, 2023

A good use case is saving metadata of your systems for data cataloging. Various systems, like those opened in metadata and similar applications, use Elasticsearch to store their text data.

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PO

PHILIP OLANIYAN

Relationship Manager at Snapnet Ltd

Jan 8, 2024

It provides deep visibility into your cloud and distributed applications, from microservices to serverless architectures. It quickly identifies and resolves the root causes of issues, like gaining visibility into all the cloud-based and on-prem applications.

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Dave Ezrakhovich

Site Reliability Engineering at WiseTech Global

Nov 15, 2023

It is highly valuable because of its simplicity in maintenance, where most tasks are handled for you, and it offers a plethora of built-in features.

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KR

Head of Technology Operations at a financial services firm with 11-50 employees

Oct 30, 2020

The most valuable feature is the out of the box Kibana.

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Consultant at High Key Consulting llc

Nov 30, 2023

The most valuable features are its user-friendly interface and seamless navigation.

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ME

Owner and CEO at Karmasis

Apr 6, 2021

The search speed is most valuable and important.

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Elastic Search Cons review quotes

ED

Owner & director at Pulsar ICT

Jun 18, 2020

The solution has quite a steep learning curve. The usability and general user-friendliness could be improved. However, that is kind of typical with products that have a lot of flexibility, or a lot of capabilities. Sometimes having more choices makes things more complex. It makes it difficult to configure it, though. It's kind of a bitter pill that you have to swallow in the beginning and you really have to get through it.

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KB

Chief Data Scientist at Everlytics Data Science Pte Ltd

Nov 30, 2020

The metadata gets stored along with indexes and isn't queryable.

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Enterprise Architect at DXC Technology

Jul 18, 2024

Scalability and ROI are the areas they have to improve.

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Free Report: Elastic Search Reviews and More

Learn what your peers think about Elastic Search. Get advice and tips from experienced pros sharing their opinions. Updated: January 2025.

831,158 professionals have used our research since 2012.

LK

Senior Solutions Architect at a tech services company with 51-200 employees

Sep 22, 2022

Both the graph feature and the reporting feature are a little bit lacking. The alerting also needs to be improved.

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Cloud and Big Data Engineer | Developer at Huawei Cloud Middle East

Nov 20, 2023

There are challenges with performance management and scalability.

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PO

PHILIP OLANIYAN

Relationship Manager at Snapnet Ltd

Jan 8, 2024

There are potential improvements based on our client feedback, like unifying the licensing cost structure.

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Dave Ezrakhovich

Site Reliability Engineering at WiseTech Global

Nov 15, 2023

While integrating with tools like agents for ingesting data from sources like firewalls is valuable, I believe prioritizing improvements to the core product would be more beneficial.

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KR

Head of Technology Operations at a financial services firm with 11-50 employees

Oct 30, 2020

I would like to be able to do correlations between multiple indexes.

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Consultant at High Key Consulting llc

Nov 30, 2023

Elastic Search could benefit from a more user-friendly onboarding process for beginners.

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ME

Owner and CEO at Karmasis

Apr 6, 2021

Its licensing needs to be improved. They don't offer a perpetual license. They want to know how many nodes you will be using, and they ask for an annual subscription. Otherwise, they don't give you permission to use it. Our customers are generally military or police departments or customers without connection to the internet. Therefore, this model is not suitable for us. This subscription-based model is not the best for OEM vendors. Another annoying thing about Elasticsearch is its roadmap. We are developing something, and then they say, "Okay. We have removed that feature in this release," and when we are adapting to that release, they say, "Okay. We have removed that one as well." We don't know what they will remove in the next version. They are not looking for backward compatibility from the customers' perspective. They just remove a feature and say, "Okay. We've removed this one." In terms of new features, it should have an ODBC driver so that you can search and integrate this product with existing BI tools and reporting tools. Currently, you need to go for third parties, such as CData, in order to achieve this. ODBC driver is the most important feature required. Its Community Edition does not have security features. For example, you cannot authenticate with a username and password. It should have security features. They might have put it in the latest release.

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Product Categories

Product Categories

Indexing and Search

Cloud Data Integration

Search as a Service

Vector Databases

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Product Categories

Product Categories

Indexing and Search

Cloud Data Integration

Search as a Service

Vector Databases

Popular Comparisons

Popular Comparisons

Microsoft FAST vs Elastic Search

Lucidworks vs Elastic Search

IBM Watson Discovery vs Elastic Search

OpenText IDOL vs Elastic Search

Coveo vs Elastic Search

Sinequa vs Elastic Search

Exalead vs Elastic Search

Attivio vs Elastic Search

Oracle Endeca vs Elastic Search

See all alternatives

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