At Shopee, I worked with numerous database schemas to find out which table columns belonged to which schema. We utilized Elastic Search to manage metadata for millions of tables, allowing us to search efficiently. Besides that, we used Logstash to put all the log files in Elastic Search for easy searchability.
External reviews
External reviews are not included in the AWS star rating for the product.
Elasticsearch: A Powerhouse for Search, but a Beast to Tame
Scalable architecture
Versatile integrations
Flexible
Support
Using OTEL
Licensing and vendor lock-in
Searching Large logs
Can't select log text and add it for quick search. (double click and add feature)
Doesn't distribute data evenly across the nodes. Thereby increasing costs when auto-scaled at this scale
Auto-scaling not working properly
Quick searches with unstructured data
Proactive monitoring thereby reducing MTTR benefiting business with reduced downtime
Scalable and reliable - 0% downtime
AI features - still exploring but so far impressive
ML features -
Search efficiency improves with enhanced metadata and log management
What is our primary use case?
How has it helped my organization?
Elastic Search significantly improved my work. Previously, when searching for text that appears in the middle of strings, the process was time-consuming. Elastic Search enables efficient searching, enhancing system performance and responsiveness. I can also collect logs through Kafka, send them to Elastic Search, and create indices, thus managing logs and customizing searches easily.
What is most valuable?
Elastic Search provides features such as stemming and range-based queries to search log files efficiently. It allows filtering data easily by searching for specific words based on created indexes. This made searches very efficient, and it also allows for log collection through Kafka and helps with managing logs and customizing searches according to needs, such as grouping by dates or user IDs.
What needs improvement?
Elastic Search could improve in areas such as search criteria and query processes, as search times were longer prior to implementing Elastic Search. Elastic Search has limitations for handling huge amounts of data and updates, especially if updates are frequent. It doesn't handle big data scale efficiently, especially regarding data size and scale, compared to Apache Solr. It doesn't support real-time search effectively, as it refreshes the indexes every few seconds.
What do I think about the stability of the solution?
It is stable as many companies already use Elastic Search. In cloud scenarios, it manages well by scaling up or down based on peak traffic. Otherwise, similar functionality needs to be replicated in a private cloud, including backups.
What do I think about the scalability of the solution?
Elastic Search requires enhancements for handling huge amounts of data and updates. Segmenting or sharding data and complexities regarding the cluster can be issues. Updating in Elastic Search involves index computations and user dependencies. There might be issues regarding data size and scaling, but these can be tuned and improved.
Which other solutions did I evaluate?
I remember Apache Solr, which is generally used for much larger scale data compared to Elastic Search. Apache Solr is used by most companies, and while Elastic Search is very common, there are technologies similar to Elastic Search, though I'm not familiar with all the names.
What other advice do I have?
I have used Elastic Search, but I might not be aware of many internal details; I just used the API to create an index, manage data, and search. It's very useful. On a scale of 1-10, I rate it an eight.
Really amazing experience easy to use easy to understand and easy to analyse
User optimizes data analysis with advanced search features and seeks expanded functionality
What is our primary use case?
What is most valuable?
The full text search capabilities in Elastic Search have proven to be extremely valuable for our operations.
Regarding AI integration, we have not yet implemented any AI-driven projects or initiatives using Elastic Search.
What needs improvement?
For how long have I used the solution?
What do I think about the stability of the solution?
What do I think about the scalability of the solution?
Which solution did I use previously and why did I switch?
How was the initial setup?
What was our ROI?
What other advice do I have?
I am currently working with Elastic Search as the primary solution.
My role is Senior DevOps engineer at UVIK Digital.
On a scale of 1 to 10, with 10 being the highest, I would rate Elastic Search as an 8 overall as a product and solution.
The command-based configuration simplifies data management and setup
What is our primary use case?
What is most valuable?
What needs improvement?
For how long have I used the solution?
What was my experience with deployment of the solution?
What do I think about the stability of the solution?
What do I think about the scalability of the solution?
How are customer service and support?
How would you rate customer service and support?
Positive
How was the initial setup?
What was our ROI?
What's my experience with pricing, setup cost, and licensing?
Which other solutions did I evaluate?
What other advice do I have?
Improved performance in data aggregation and has a fast performance
What is our primary use case?
I use the solution to store historical data and logs to find anomalies within the logs. That is about it. I don't create dashboards from it.
What is most valuable?
I find the solution to be fast. Aggregation is faster than querying directly from a database, like Postgres or Vertica. It's much faster if I want to do aggregation. These features allow me to store logs and find anomalies effectively.
What needs improvement?
I found an issue with Elasticsearch in terms of aggregation. They are good, yet the rules written for this are not really good.
There is a maximum of 10,000 entries, so the limitation means that if I wanted to analyze certain IP addresses more than 10,000 times, I wouldn't be able to dump or print that information. I need to use paging or something similar as a workaround. That's what the limitation is all about.
For how long have I used the solution?
I have probably used it for three or four years, maybe longer.
What do I think about the stability of the solution?
The solution is very good with no issues or glitches.
What do I think about the scalability of the solution?
In terms of scalability, I have multiple Search instances. I can actually add more storage and memory because I host it in the cloud. It's much easier in terms of scalability, and I have no complaints about it.
How are customer service and support?
I have never talked to technical support.
How would you rate customer service and support?
Neutral
Which solution did I use previously and why did I switch?
I am using Elasticsearch.
How was the initial setup?
The initial setup is very easy.
What about the implementation team?
I did not use any outside assistance.
What's my experience with pricing, setup cost, and licensing?
I don't know about pricing. That is dealt with by the sales team and our account team. I was not involved with that.
Which other solutions did I evaluate?
I am evaluating InfluxDB as well. Timescub is a kind of database.
What other advice do I have?
I would rate Elasticsearch at eight out of ten.
Efficient large data handling and good scalability empowers legal search
What is our primary use case?
We are using Elastic Search for free text search. We scan cache files and convert them into OCR. This allows our end users to search for any judgment given in the 1980s or 1990s based on their criteria.
What is most valuable?
Elastic Search is very quick when handling a large volume of data. The facet search is particularly valuable. It is scalable. Elastic Search makes handling large data volumes efficient and supports complex search operations.
What needs improvement?
There should be more stability. When we started learning it, new versions came out frequently in one quarter with extended features. This can create problems for new developers because they have to quickly switch to another version. Stability could be improved, as it sometimes requires quick adaptation to new versions.
For how long have I used the solution?
We have been using Elastic Search for two years.
What do I think about the stability of the solution?
Elastic Search is generally stable, however, the frequent release of new versions can cause challenges for stability. If asked to rate stability, I would give it an eight out of ten.
What do I think about the scalability of the solution?
Elastic Search is scalable. Our supreme court uses it for the whole nation across all judgments, so it must be scalable.
How are customer service and support?
We have not contacted customer service. We rely on documentation for solutions.
How would you rate customer service and support?
Positive
Which solution did I use previously and why did I switch?
We are using Elastic Search for free text search in our project.
How was the initial setup?
The documentation for Elastic Search is very well structured. It provides easy-to-follow steps for installation, making it a straightforward process.
What about the implementation team?
One person can install Elastic Search by following the documentation steps.
What was our ROI?
Our organization prioritizes open-source tools. We have not purchased any licensed products, and our use of Elastic Search is purely open-source, contributing positively to our ROI. We adopt open-source tools due to the organization's policy.
Which other solutions did I evaluate?
Our experience has been positive, finding solutions in documentation without needing customer support. We also use supporting technologies like PostgreSQL, Spring Boot, and Subversion for seamless integration.
What other advice do I have?
I rate Elastic Search nine out of ten.
Enhanced security operations with good logging and real-time threat analysis
What is our primary use case?
I am an end user, and we use Elasticsearch for our logs. Specifically, we use it for security logs for our enterprise, including machines, networks, and endpoints, as part of our IT infrastructure.
How has it helped my organization?
We have been able to collect our live logs, which helps us run security operations more effectively. It has enabled us to identify false positives and detect real-time malicious activities in the network.
What is most valuable?
The security portion of Elasticsearch is particularly beneficial, allowing me to view and analyze security alerts. It serves as a query engine for the database, enabling us to analyze logs for potential threats.
What needs improvement?
An improvement would be to have an interface that allows easier navigation and tracing of logs. The current system requires manually inputting dates to verify alerts. A visual timeline that pinpoints possible anomalies would be beneficial.
For how long have I used the solution?
I have been using Elasticsearch for approximately one year.
What do I think about the stability of the solution?
I would rate the stability of the solution as nine out of ten. It is very robust.
What do I think about the scalability of the solution?
I would rate the scalability as either nine out of ten. It's a very robust solution.
How are customer service and support?
I do not interface directly with technical support from Elastic. Another colleague manages that aspect.
How would you rate customer service and support?
Positive
Which solution did I use previously and why did I switch?
We did not use any different solution before Elasticsearch.
How was the initial setup?
I was not involved in the setup process. Our architects and technical officer managed it.
What's my experience with pricing, setup cost, and licensing?
I am not directly involved with pricing or setup costs. While I know a portion is open-source, a paid version might be necessary.
Which other solutions did I evaluate?
It was not my duty to evaluate other options. The architects and chief technical officer handled those decisions.
What other advice do I have?
For someone wanting to be a security analyst, Elasticsearch is a valuable tool. It helps organizations collect large amounts of logs from various platforms like Windows, Ubuntu, and Palo Alto Networks.
I'd rate the solution eight out of ten.
Flexible notifications and good alerts with good scalability
How has it helped my organization?
It has helped by notifying me when something happens. I deploy my team to the infrastructure to fix the application. However, receiving alerts before something happens would be more beneficial.
What is most valuable?
New Relic is very similar to Elasticsearch in functionality; it's easier to use.
What needs improvement?
New Relic could be more flexible, similar to Elasticsearch. It could improve on providing notifications before something happens instead of when something happens.
What do I think about the stability of the solution?
It is a stable and good platform.
What do I think about the scalability of the solution?
It's scalable. There's no need to worry about the environment. You just configure it, and it runs without issues.
How are customer service and support?
I haven't used their support, however, a colleague I talked to about this platform with has used it.
How would you rate customer service and support?
Positive
How was the initial setup?
The initial setup is not complex. The only part that may require specific knowledge is communicating your cloud environment with New Relic and managing the cloud environment configurations.
What's my experience with pricing, setup cost, and licensing?
Comparing the costs between New Relic and Elasticsearch is difficult as New Relic's cost is for processing metrics, whereas Elasticsearch's cost is for storage.
What other advice do I have?
I recommend New Relic, however, it depends on the specific use case you have. I'd rate the solution eight out of ten.
Offers good search interface and visualization capabilities with good stability
What is our primary use case?
We use Elasticsearch as an alternative to Splunk. It is basically for log monitoring.
What is most valuable?
It's probably a cost-efficient alternative to Splunk. The search interface is nearly the same. When it comes to visualizations, Elastic is a bit better than Splunk.
What needs improvement?
Elastic Search needs better guides for developers. Better guides for development.
For how long have I used the solution?
I have been using it for a year.
What do I think about the stability of the solution?
I would rate the stability an eight out of ten.
What do I think about the scalability of the solution?
It's fairly scalable. I would rate the scalability of this solution a ten out of ten.
There are around five end users using it in my team.
How are customer service and support?
Till date, we did not have any issues with customer service and support. Like, initially, we had issues in accessing the portal. But that was the only issue, but it was resolved pretty quick.
How was the initial setup?
The initial setup is fairly simple. Initially, it was on-prem, but right now, it's on the cloud.
It is pretty easy to integrate as well.
What was our ROI?
It's like, when someone is buidling products for scale, it reduces the time to market.
What's my experience with pricing, setup cost, and licensing?
I would rate the pricing a seven out of ten, with one being high price and ten being low price. It could be cheaper for certain use cases, but since it gets the job done, no complaints for the pricing.
What other advice do I have?
Overall, I would rate it a nine out of ten. I would definitely recommend it to other users.