The main use cases for Elastic Search are index building and retrieving information using Elastic Search vector, vector search, and related functionalities. Search is the primary use case.
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Fast Data Processing and Great Observability—No Complaints
What do you like best about the product?
What I like best about Elasticsearch is its speed and scalability when working with large volumes of data. It excels at full-text search and real-time querying, making it incredibly useful for applications like log analysis, monitoring, and powering search features.
What do you dislike about the product?
Nothing at all. It's good the way it is.
What problems is the product solving and how is that benefiting you?
Elasticsearch helps solve the problem of quickly searching, analyzing, and visualizing large volumes of data in real time. For me, it simplifies observability and operational intelligence, reducing time to detect and resolve problems while giving deeper insight into system and user behavior.
Boosted search efficiency through real-time querying and seamless indexing for high-volume product data
What is our primary use case?
What is most valuable?
Computation is very good. The scalability is very good because we have a huge customer database that is searching lots of products, and auto-scaling or load balancing are the prominent features we are using in this.
If we look at the impact on operational efficiency, we can see that decision-making has become much faster due to real-time data and quick responses. We have also implemented many automations, which enhance our processes. For example, when we optimize certain fields to improve search functionality, it yields great results.
What needs improvement?
I have not explored Elastic Search at the most. Searching from vector DB is available in Elastic Search, and there is one more concept of graph searching or graph database searching. I have not explored it, but if it is not there, that would be an improvement area where Elastic Search can improve.
For how long have I used the solution?
I have been working with Elastic Search for more than two years.
What do I think about the stability of the solution?
It is very reliable, and it has no downtime.
What do I think about the scalability of the solution?
I believe it is scalable. Every day, we have thousands of users continuously utilizing the search feature. We haven't encountered any problems so far, and there is the potential for auto-scaling. It is currently a scalable solution.
How are customer service and support?
We have not contacted them yet. So far, we haven't had any need.
How would you rate customer service and support?
Positive
How was the initial setup?
The initial setup is straightforward.
What about the implementation team?
We have a team of developers, so it is internally managed.
What was our ROI?
We have not calculated the ROI for Elastic Search, but we are a consumer platform where numerous searches are happening, and we are getting very good results from the current infrastructure of Elastic Search. Though the exact numbers or ROI were never calculated, the performance has been beneficial.
What's my experience with pricing, setup cost, and licensing?
It is average compared to other platforms. There isn’t anything particularly special about the pricing. However, the pay-as-you-go model is advantageous for the organization, as we only pay for what we utilize.
What other advice do I have?
We are using AWS for our solutions. In AWS, we are heavily using Redshift and Glue. We focus more on vector searches and boosting the keywords, and all those features we are using heavily. In search, the key parameter that we boost up during indexing is essential.
We self-implement Elastic Search in our e-commerce application. We are not currently doing a regex setup for RAG Playground, but there is a plan to do that. We are more into vector searches when it comes to how effectively the hybrid search capability meets our needs for combining traditional keyword and vector searches.
Regarding the workflow, we are using the API for real-time inference because lots of data is being loaded at real-time on the application, and it is working well for us.
I can definitely recommend Elastic Search to be used wherever you have consumer search capabilities needed in a large or scalable manner because it is very effective.
I would rate Elastic Search an eight out of ten.
Which deployment model are you using for this solution?
Public Cloud
If public cloud, private cloud, or hybrid cloud, which cloud provider do you use?
Amazon Web Services (AWS)
ECK Kube features and stability
What do you like best about the product?
Elastic ECK for Kubernetes offers useful features and reliable stability. It effectively meets our enterprise search requirements.
What do you dislike about the product?
None, it worked well. met all requirements
What problems is the product solving and how is that benefiting you?
Enterprise search
Very high, if they need to build a search feature or analyze time-series data like logs or metrics.
What do you like best about the product?
The most compelling feature of Elasticsearch is its scalability and performance in handling high-volume, high-velocity data
What do you dislike about the product?
The primary critique of Elasticsearch centers on its operational complexity and resource intensity at scale. While it offers immense power, it is not a tool you can simply 'set and forget.
What problems is the product solving and how is that benefiting you?
we use it for real-time log analysis, application performance monitoring (APM), and security analytics (SIEM) by aggregating, indexing, and visualizing all machine-generated data.
Elasticsearch provides best searching and data aggregation capabilities
What do you like best about the product?
I used Elasticsearch to store salary statistical data and to perform mathematical operations on that data. What I appreciated most about Elasticsearch is that its queries offer built-in support for operations such as calculating the mean, average, and percentiles.
What do you dislike about the product?
The documentation for Elasticsearch could use some improvement. It would be helpful if more detailed information were included.
What problems is the product solving and how is that benefiting you?
Elasticsearch offers outstanding text search capabilities with minimal latency. Along with simple text search, it also provides capabilities like string matching, wildcards, fuzzy logic etc
Elastic elk and anomaly detection
What do you like best about the product?
The elastic feature of collecting logs and monitoring them through ELK is quite useful, especially when the results are displayed on a Kibana dashboard. Additionally, the integration of anomaly detection using machine learning adds significant value to the overall monitoring process.
What do you dislike about the product?
There is nothing to complain about; everything works well, including elk, ml, anomaly detection, and the APM agent, which handles auto discovery effectively.
What problems is the product solving and how is that benefiting you?
Log monitoring and anomaly detection are both available, and the agent installation process supports automatic discovery, which makes it easier to use the APM feature.
Powerful and Flexible
What do you like best about the product?
The flexibility to solve many problems, the expansive feature set allows us to use Elasticsearch in a variety of ways.
What do you dislike about the product?
Slight learning curve, as it can do many things, you need to be aware of the use case you are solving for or it can get overwhelming without proper planning.
What problems is the product solving and how is that benefiting you?
Helping us with enterprise search functions on several of our internal and external facing applications
Elk usage on elastic using kibana dashboards
What do you like best about the product?
Log monitoring and it's feature to identify anomalies using enterprise elk license version and creating the dashboards on elastic are so easy
What do you dislike about the product?
Nothing all features including th exam agents features are very good for elastic
What problems is the product solving and how is that benefiting you?
Log monitoring and other features of elk including the anomaly detection and elastic apn agent where we are monitoring application performance. Capturing all logs and shown for dashboard helped in all ways to reduce incidents in applications
Good product, meets our needs
What do you like best about the product?
Able to consume and collect our data without any surprise costs.
What do you dislike about the product?
Support can take a while to get back with you, and the product is dependent on a lot of other products such as zookeeper that have different timelines and support models.
What problems is the product solving and how is that benefiting you?
Elastic is used to collect, catalog and score security data within the Agency. It provides a useful dashboard that allows access to all underlying data.
Sr. Elastic Engineer
What do you like best about the product?
Elastic's cloud-base solution is easy to configure and deploy. Immediately start to ingest data within minutes. Simply deploy and configure one of many integrations and begin making data driven decisions. Elastic's various components such as observability, search (vector search), SIEM makes it a one stop solution for needs.
What do you dislike about the product?
I have been using this product for over 9 years and there is not an aspect which I dislike.
What problems is the product solving and how is that benefiting you?
Elastic is helping with its SIEM integration and anomaly detection providing us with immediate alerting allowing quick mitigation and/or remediation
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