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Dataloader.io vs Elastic Search 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

Dataloader.io
Average Rating
7.6
Reviews Sentiment
7.5
Number of Reviews
2
Ranking in other categories
Data Integration (50th)
Elastic Search
Average Rating
8.2
Reviews Sentiment
6.5
Number of Reviews
91
Ranking in other categories
Indexing and Search (1st), Cloud Data Integration (5th), Search as a Service (1st), Vector Databases (2nd)
 

Featured Reviews

reviewer2542599 - PeerSpot reviewer
Lead Database Administrator at a insurance company with 201-500 employees
Integrating external keys seamlessly while has transaction constraints
I find DataLoader's ability to easily integrate with external keys valuable, which is a bit more challenging with DBM. It provides automation for scheduling data loads, and we use the server's functionality for this. Additionally, DataLoader is cost-effective since it is free. As long as I have stable network access, uploading and downloading data is straightforward.
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.

Quotes from Members

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

Pros

"he product’s most valuable feature is ease of access."
"DataLoader is cost-effective since it is free."
"I find DataLoader's ability to easily integrate with external keys valuable, which is a bit more challenging with DBM."
"Elastic Enterprise Search is a very good solution and they should keep doing good work."
"All the quality features are there. There are about 60 to 70 reports available."
"Big businesses cannot survive without Elastic Search because it gives us very good visibility and handles our use cases very well."
"It is a stable and good platform."
"It's a stable solution and we have not had any issues."
"ELK Elasticsearch is 100% scalable as scalability is built into the design"
"Elastic Search is very quick when handling a large volume of data."
"The ability to aggregate log and machine data into a searchable index reduces time to identify and isolate issues for an application."
 

Cons

"We need help with large data migrations. It only works well for a few thousand records or less than a million records."
"DataLoader has limitations, including constraints with file sizes and transactions."
"Dataloader has limitations, including constraints with file sizes and transactions. Additionally, at times it can be slow, and when integrating DBM, we find it more complex than Dataloader."
"The UI point of view is not very powerful because it is dependent on Kibana."
"We'd like more user-friendly integrations."
"Elastic Search needs to improve its technical support. It should be customer-friendly and have good support."
"I think the first area for improvement is pricing, as the cluster cost for Elastic Search is too high for me."
"The one area that can use improvement is the automapping of fields."
"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."
"It would be useful to include an assistant into Kibana for recommendations, advice, tutorials, or things that can help improve my daily work with Elastic Search."
"According to me, as far as I have seen, people will start moving from Elastic Search sooner or later. Why? Because it is expensive."
 

Pricing and Cost Advice

"The product is inexpensive and economical."
"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."
"we are using a licensed version of the product."
"The cost varies based on factors like usage volume, network load, data storage size, and service utilization. If your usage isn't too extensive, the cost will be lower."
"The price of Elasticsearch is fair. It is a more expensive solution, like QRadar. The price for Elasticsearch is not much more than other solutions we have."
"The solution is less expensive than Stackdriver and Grafana."
"ELK has been considered as an alternative to Splunk to reduce licensing costs."
"The solution is not expensive because users have the option of choosing the managed or the subscription model."
"This is a free, open source software (FOSS) tool, which means no cost on the front-end. There are no free lunches in this world though. Technical skill to implement and support are costly on the back-end with ELK, whether you train/hire internally or go for premium services from Elastic."
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Top Industries

By visitors reading reviews
No data available
Financial Services Firm
11%
Computer Software Company
10%
Manufacturing Company
9%
Retailer
7%
 

Company Size

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

Questions from the Community

What is your experience regarding pricing and costs for Dataloader.io?
Dataloader.io is cost-effective, particularly since it is free.
What needs improvement with Dataloader.io?
DataLoader has limitations, including constraints with file sizes and transactions. Additionally, at times it can be slow, and when integrating DBM, we find it more complex than DataLoader.
What advice do you have for others considering Dataloader.io?
For small to mid-range businesses, DataLoader is perfectly fine, offering everything needed for uploading. On a scale of one to ten, I would rate DataLoader a seven or eight depending on specific n...
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...
 

Also Known As

No data available
Elastic Enterprise Search, Swiftype, Elastic Cloud
 

Overview

 

Sample Customers

UCSF, Box, CareFusion, Unilever, Hershey's
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.
Find out what your peers are saying about Dataloader.io vs. Elastic Search and other solutions. Updated: March 2026.
885,376 professionals have used our research since 2012.