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Elastic Search vs Meilisearch comparison

 

Comparison Buyer's Guide

Executive Summary

Review summaries and opinions

We asked business professionals to review the solutions they use. Here are some excerpts of what they said:
 

Categories and Ranking

Elastic Search
Ranking in Indexing and Search
1st
Average Rating
8.2
Reviews Sentiment
6.5
Number of Reviews
92
Ranking in other categories
Cloud Data Integration (5th), Search as a Service (1st), Vector Databases (2nd)
Meilisearch
Ranking in Indexing and Search
15th
Average Rating
10.0
Number of Reviews
1
Ranking in other categories
No ranking in other categories
 

Featured Reviews

Anurag Pal - PeerSpot reviewer
Technical Lead at a consultancy with 10,001+ employees
Search and aggregations have transformed how I manage and visualize complex real estate data
Elastic Search consumes lots of memory. You have to provide the heap size a lot if you want the best out of it. The major problem is when a company wants to use Elastic Search but it is at a startup stage. At a startup stage, there is a lot of funds to consider. However, their use case is that they have to use a pretty significant amount of data. For that, it is very expensive. For example, if you take OLTP-based databases in the current scenario, such as ClickHouse or Iceberg, you can do it on 4GB RAM also. Elastic Search is for analytical records. You have to do the analytics on it. According to me, as far as I have seen, people will start moving from Elastic Search sooner or later. Why? Because it is expensive. Another thing is that there is an open source available for that, such as ClickHouse. Around 2014 and 2012, there was only one competitor at that time, which was Solr. But now, not only is Solr there, but you can take ClickHouse and you have Iceberg also. How are we going to compete with them? There is also a fork of Elastic Search that is OpenSearch. As far as I have seen in lots of articles I am reading, users are using it as the ELK stack for logs and analyzing logs. That is not the exact use case. It can do more than that if used correctly. But as it involves lots of cost, people are shifting from Elastic Search to other sources. When I am talking about pricing, it is not only the server pricing. It is the amount of memory it is using. The pricing is basically the heap Java, which is taking memory. That is the major problem happening here. If we have to run an MVP, a client comes to me and says, "Anurag, we need to do a proof of concept. Can we do it if I can pay a 4GB or 16GB expense?" How can I suggest to them that a minimum of 16GB is needed for Elastic Search so that your proof of concept will be proved? In that case, what I have to suggest from the beginning is to go with Cassandra or at the initial stage, go with PostgreSQL. The problem is the memory it is taking. That is the only thing.
reviewer2797689 - PeerSpot reviewer
CTO at a tech vendor with 1-10 employees
Improved search performance has reduced our operational costs and simplified ongoing maintenance
I use it for 50% text search and 50% vector search They drastically reduce operation costs for both human resources and compute compared to OpenSearch. Everything was an upgrade compared to Amazon OpenSearch, with the exception of resiliency. The resiliency of their service needs improvement.…

Quotes from Members

We asked business professionals to review the solutions they use. Here are some excerpts of what they said:
 

Pros

"From the customer side, Elastic Search is super fast and very efficient, delivering results quickly."
"It is a stable and good platform."
"Using real-time search functionality to support operational decisions has been helpful."
"The stability of Elasticsearch was very high, and I would rate it a ten."
"The most valuable features of Elastic Enterprise Search are it's cloud-ready and we do a lot of infrastructure as code. By using ELK, we're able to deploy the solution as part of our ISC deployment."
"The UI is very nice, and performance wise it's quite good too."
"Elasticsearch includes a graphical user interface (GUI) called Kibana, and the GUI features are extremely beneficial to us."
"Elastic Search has impacted my organization positively as we use it for logging and APM."
"Everything was an upgrade compared to Amazon OpenSearch, with the exception of resiliency."
 

Cons

"It should be easier to use. It has been getting better because many functions are pre-defined, but it still needs improvement."
"We'd like to see more integration in the future, especially around service desks or other ITSM tools."
"I think the first area for improvement is pricing, as the cluster cost for Elastic Search is too high for me."
"There are some features lacking in ELK Elasticsearch."
"I think the pricing of Elastic Search is really, really expensive."
"According to me, as far as I have seen, people will start moving from Elastic Search sooner or later. Why? Because it is expensive."
"Elastic Enterprise Search can improve by adding some kind of search that can be used out of the box without too much struggle with configuration."
"What they need is to be more transparent about the actual setup of the cluster and the deployment process."
"The resiliency of their service needs improvement. There have been several outages."
 

Pricing and Cost Advice

"We are using the Community Edition because Elasticsearch's licensing model is not flexible or suitable for us. They ask for an annual subscription. We also got the development consultancy from Elasticsearch for 60 days or something like that, but they were just trying to do the same trick. That's why we didn't purchase it. We are just using the Community Edition."
"The solution is less expensive than Stackdriver and Grafana."
"There is a free version, and there is also a hosted version for which you have to pay. We're currently using the free version. If things go well, we might go for the paid version."
"The tool is an open-source product."
"The tool is not expensive. Its licensing costs are yearly."
"An X-Pack license is more affordable than Splunk."
"The pricing model is questionable and needs to be addressed because when you would like to have the security they charge per machine."
"The price could be better."
Information not available
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Top Industries

By visitors reading reviews
Financial Services Firm
12%
Computer Software Company
10%
Manufacturing Company
9%
Retailer
6%
No data available
 

Company Size

By reviewers
Large Enterprise
Midsize Enterprise
Small Business
By reviewers
Company SizeCount
Small Business38
Midsize Enterprise10
Large Enterprise46
No data available
 

Questions from the Community

What do you like most about ELK Elasticsearch?
Logsign provides us with the capability to execute multiple queries according to our requirements. The indexing is very high, making it effective for storing and retrieving logs. The real-time anal...
What is your experience regarding pricing and costs for ELK Elasticsearch?
On the subject of pricing, Elastic Search is very cost-efficient. You can host it on-premises, which would incur zero cost, or take it as a SaaS-based service, where the expenses remain minimal.
What needs improvement with ELK Elasticsearch?
From the UI point of view, we are using most probably Kibana, and I think they can do much better than that. That is something they can fine-tune a little bit, and then it will definitely be a good...
What needs improvement with Meilisearch?
The resiliency of their service needs improvement. There have been several outages.
What is your primary use case for Meilisearch?
I use it for 50% text search and 50% vector search.
 

Comparisons

No data available
 

Also Known As

Elastic Enterprise Search, Swiftype, Elastic Cloud
No data available
 

Overview

 

Sample Customers

T-Mobile, Adobe, Booking.com, BMW, Telegraph Media Group, Cisco, Karbon, Deezer, NORBr, Labelbox, Fingerprint, Relativity, NHS Hospital, Met Office, Proximus, Go1, Mentat, Bluestone Analytics, Humanz, Hutch, Auchan, Sitecore, Linklaters, Socren, Infotrack, Pfizer, Engadget, Airbus, Grab, Vimeo, Ticketmaster, Asana, Twilio, Blizzard, Comcast, RWE and many others.
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