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Powerful and Scalable Search Solution
What do you like best about the product?
What I like most about Elasticsearch is its speed and flexibility. It handles large amounts of data efficiently and makes searching very fast. It is also versatile enough to be used for both search and analytics use cases.
What do you dislike about the product?
One thing I dislike about Elasticsearch is that it can become complex to manage as it grows. It requires careful planning and monitoring to avoid performance and stability issues. Licensing and pricing changes over time have also created some uncertainty for users.
What problems is the product solving and how is that benefiting you?
Elasticsearch helps us quickly search and analyze large amounts of data in one place. It makes it easier to find relevant information, monitor systems, and generate insights from logs or application data. This improves visibility and allows us to respond to issues faster and make better decisions.
Powerful Log Database with Helpful Integrations for Easy Parsing
What do you like best about the product?
You can use it as a database and classify all type of logs. The integrations they have helps you to parse them
What do you dislike about the product?
Sometimes correlations can be difficult between different technologies
What problems is the product solving and how is that benefiting you?
Handling logs
Efficient Log Management & Search with Excellent Support
What do you like best about the product?
Very efficient product to manage our logs and search
The support is easy to interact with and the quality of the answers are perfect
The support is easy to interact with and the quality of the answers are perfect
What do you dislike about the product?
When it is self managed, a bit tedious to update
What problems is the product solving and how is that benefiting you?
Centralizing our documentation and making it available in quick search is really great
Best No-SQL Databases with vector search and AI use cases
What do you like best about the product?
It’s one of the best NoSQL databases on the market. It makes it easier to collect logs from many different sources and to define integrations for them. It provides many features within one tool like vector search, machine learning, alerting and a lot
What do you dislike about the product?
I don’t like the breaking changes that come with version upgrades, because they have a big impact when multiple teams depend on the deployment.
What problems is the product solving and how is that benefiting you?
We collect telecom metrics from around 1,000 servers, which helps us search for and debug errors, create KPIs, and set up rules and alerting based on that data. As a result, it reduces manual effort and is easy to integrate with other systems. The best part is elasticsearch can be used for varied use cases. Its a single point of monitoring for our whole telecom stack.
Real-Time Bet Monitoring That Helps Us Improve Before It Happens
What do you like best about the product?
It helps us monitor bets in real time, and we can even see where we need to improve before it happens.
What do you dislike about the product?
It gives us a real-time view of our infrastructure logs. The downside is that shards sometimes get corrupted, and we need to restore them, but we don’t have clear visibility into that process.
What problems is the product solving and how is that benefiting you?
It provides operators with real-time logs and supports the compliance team in meeting regulatory requirements.
Powerful Search Platform for Enterprise-Scale Operations
What do you like best about the product?
What I like best about Elasticsearch is its powerful search and aggregation capabilities combined with high performance at scale. We support over 100 customers who use it daily in their operations, and Elasticsearch consistently handles large data volumes with fast response times.
From a support perspective, features like detailed query capabilities, clear APIs, and strong integration within the Elastic Stack significantly improve our workflow. Kibana dashboards help us quickly analyze customer issues, review logs, and identify performance bottlenecks without needing custom tools. This often reduces troubleshooting time from hours to minutes.
An unexpected benefit has been how flexible and scalable the platform is across different customer environments. It allows us to support diverse use cases while maintaining a relatively standardized architecture.
From a support perspective, features like detailed query capabilities, clear APIs, and strong integration within the Elastic Stack significantly improve our workflow. Kibana dashboards help us quickly analyze customer issues, review logs, and identify performance bottlenecks without needing custom tools. This often reduces troubleshooting time from hours to minutes.
An unexpected benefit has been how flexible and scalable the platform is across different customer environments. It allows us to support diverse use cases while maintaining a relatively standardized architecture.
What do you dislike about the product?
One of the main challenges with Elasticsearch is the complexity of configuration and tuning, especially in larger or high-availability clusters. For customers without deep expertise, settings around JVM tuning, shard allocation, and performance optimization can be difficult to manage. This often increases the support workload and extends troubleshooting time.
Version upgrades can also be demanding. Breaking changes between major versions and strict compatibility requirements sometimes require careful planning and additional testing, which impacts customer environments and maintenance windows.
Customers often ask about the possibility of reverting to the previous version, but this is not possible.
In such cases, we have to come up with our own workarounds.
Improved backward compatibility, clearer upgrade paths, and more built-in automated diagnostics for cluster health and performance tuning would significantly reduce operational overhead for both customers and support teams.
Version upgrades can also be demanding. Breaking changes between major versions and strict compatibility requirements sometimes require careful planning and additional testing, which impacts customer environments and maintenance windows.
Customers often ask about the possibility of reverting to the previous version, but this is not possible.
In such cases, we have to come up with our own workarounds.
Improved backward compatibility, clearer upgrade paths, and more built-in automated diagnostics for cluster health and performance tuning would significantly reduce operational overhead for both customers and support teams.
What problems is the product solving and how is that benefiting you?
Many of our customers struggled with slow database searches, limited reporting capabilities, and fragmented log storage. Troubleshooting incidents often required manually checking multiple systems, which was time-consuming and inefficient.
With Elasticsearch, they can centralize logs and operational data, perform fast full-text searches, and build real-time dashboards. As a result, tasks that previously took hours - such as identifying the root cause of an issue - can now often be completed in minutes.
For us as a support team, this has significantly reduced resolution times and improved SLA compliance. In many cases, incident investigation time has decreased by 50% or more, which directly benefits both our customers and our internal operations.
With Elasticsearch, they can centralize logs and operational data, perform fast full-text searches, and build real-time dashboards. As a result, tasks that previously took hours - such as identifying the root cause of an issue - can now often be completed in minutes.
For us as a support team, this has significantly reduced resolution times and improved SLA compliance. In many cases, incident investigation time has decreased by 50% or more, which directly benefits both our customers and our internal operations.
Fast, Flexible, and Innovative—Elasticsearch at Its Best
What do you like best about the product?
I appreciate its speed, flexibility, and innovation.
What do you dislike about the product?
There isn’t much to dislike about Elastic Search.
What problems is the product solving and how is that benefiting you?
It’s helping us improve our search platform and making it better overall.
Elasticsearch: The Best Engine for Fast Data Search and Analysis
What do you like best about the product?
Elasticsearch is the best platform/engine to analyze and search your data. With the AI capabilities Elastic is developing, it becomes even more powerful. Besides the company offers an excellent support.
I cannot imagine the current internet and technological world without Elasticsearch.
I cannot imagine the current internet and technological world without Elasticsearch.
What do you dislike about the product?
Documentation is sometimes hard to follow and navigating it feels confusing.
What problems is the product solving and how is that benefiting you?
You just put your data in Elasticsearch, and it can produce value. No matter if the data comes from old databases, files, logs, etc. Once it´s in Elasticsearch you extract all the value and knowledge from it.
Elasticsearch unifies multi-platform insights with powerful log search
What do you like best about the product?
Elasticsearch help to gather information from multiple platforms. Providing a single view for searching UI, search effectively from massive log data
What do you dislike about the product?
So far, we do not use much advance features in Elastic at this moment. When we have to use a certain feature in Elastic. We have to study the methodology and check from community for case reference. Also, there is less reference cases or examples that I cannot find easily if I want to arrange integration between Elasticsearch with third party application such as Oracle DB / Fortigate Firewall etc.
What problems is the product solving and how is that benefiting you?
For Telcom internal use: usually operator has many IoT device and application such as switch, router, server, VM and also many log file generated from them. The inventory is large and complex. We have use Elasticsearch to summarize the view to keep record and search these devices log. Also, with some known behavior or threshold for potential fault issue, we have set the alarm mechanism to trigger support team for troubleshooting for quick respond. In conclude, it helps me for inventory, reporting, monitoring and troubleshooting.
Easy to Use, Seamless GCP Integration with Zero Issues
What do you like best about the product?
The platform is very easy to use and very easy to integrate with GCP. We were able to get it to work directly in our tool with 0 issues.
What do you dislike about the product?
Expensive to scale. We have a lot of data we use to search and elastic just costs a lot so we need to set up lifecycle management
What problems is the product solving and how is that benefiting you?
search and full text lookup. We are in ecomm and customers need to look through products
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