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Elastic Search vs Tray.io 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:
 

ROI

Sentiment score
3.8
Organizations leverage Elastic Search for faster performance, cost efficiency, and seamless integration, significantly enhancing resource and time management.
Sentiment score
5.8
Tray.io boosts efficiency by reducing redundant tasks, saving 40+ hours weekly, and eliminating the need for engineer integration hours.
We have not purchased any licensed products, and our use of Elastic Search is purely open-source, contributing positively to our ROI.
Software Engineer at Government of India
It is stable, and we do not encounter critical issues like server downtime, which could result in data loss.
SOC A2 at Innodata-ISOGEN
The main benefits observed from using Elastic Search include improvements in operational efficiency, along with cost, time, and resource savings.
Senior Devops Engineer at Ubique Digital LTD
I have seen a return on investment as the company has been renewing the product for the entire 19 months we have been using it, which indicates that trust is high and they likely see value and advantage in using the system.
Principal AI and Data Science Engineer at a manufacturing company with 10,001+ employees
It has even eliminated a position on our team because that person was no longer needed once we started the automations.
Applications Analyst at a healthcare company with 1,001-5,000 employees
The ROI is clear, as it eliminates hundreds of engineer hours required to build and maintain custom integration connectors, while empowering client partners to manage complex data ingest self-sufficiently.
Dev Ops Engineer at a outsourcing company with 201-500 employees
 

Customer Service

Sentiment score
6.4
Elastic Search's support is praised for responsiveness and helpfulness, with strong community resources and comprehensive documentation available.
Sentiment score
4.3
Tray.io is user-friendly, reducing support needs; feedback highlights adequate direct support and praised newsletters and updates.
For P1 tickets, they provide very immediate quick responses and join calls to support and troubleshoot the issue accordingly.
Elastic Engineer at The Unique Identification Authority of India (UIDAI)
The customer support for Elastic Search is one of the best I have ever tried.
Software Developer at a media company with 10,001+ employees
They have always been really responsible and responsive to my requests.
Security Lead at a tech vendor with 501-1,000 employees
I have never used the customer support for Tray.io because the software is very easy to use and we never needed to contact support.
Principal AI and Data Science Engineer at a manufacturing company with 10,001+ employees
 

Scalability Issues

Sentiment score
7.2
Elastic Search provides scalable solutions praised for flexibility, though complex for large datasets, with satisfaction in performance and planning.
Sentiment score
7.3
Tray.io is scalable and adaptable, but faces challenges with complexity and data handling in high-load scenarios.
We can search through that document quite easily, sometimes in 7 milliseconds, sometimes one or two milliseconds.
Product Engineer at A3L
Performance tests involving one million requests at once, we encountered issues with shards and nodes not upscaling as needed, leading to crashes and minimal data loss.
Consultant at a tech vendor with 10,001+ employees
I would rate its scalability a ten.
Backend Developer
We were able to deploy it from a small company within Tata with 200 people to what is now a multinational company with 92,000 people globally.
Principal AI and Data Science Engineer at a manufacturing company with 10,001+ employees
Our company uses it for handling high-volume data ingestion and integration orchestration between our platform and external ad services.
Dev Ops Engineer at a outsourcing company with 201-500 employees
The benefits of it being no-code or low-code started to pale in comparison to the cost of making everything slightly more complicated.
Operations Analyst at a tech vendor with 51-200 employees
 

Stability Issues

Sentiment score
7.7
Elastic Search is praised for stability, with minor issues under heavy load or poor query design, rated highly by users.
Sentiment score
7.9
Tray.io is stable and reliable for workflows, despite setup challenges and memory limitations, enhancing data operations and integrations.
The data transfer sometimes exceeded the bandwidth limits without proper notification, which caused issues.
SOC A2 at Innodata-ISOGEN
The stability of Elasticsearch was very high.
Backend Developer
When you put one keyword, everything related to that keyword in your ecosystem will showcase all the results.
Chief Information Security Officer at CDSL Ventures Limited
In my experience, Tray.io is stable, as we have never experienced issues with it failing or being unavailable.
Principal AI and Data Science Engineer at a manufacturing company with 10,001+ employees
The biggest issue we have with Tray.io is that it runs out of memory space and does not process all of our workflows.
Applications Analyst at a healthcare company with 1,001-5,000 employees
Tray.io is highly stable for daily scheduled production runs and event-driven webhooks, provided proper error handling, timeout management, and payload validation are built into the workflow steps.
Dev Ops Engineer at a outsourcing company with 201-500 employees
 

Room For Improvement

Elastic Search needs better mapping, scalability, AI integration, pricing, support, documentation, usability, and intuitive interfaces for improved user experience.
Tray.io poses challenges for non-technical users with complex workflows, high costs, and limited integration and customization options.
From a technical point of view, there are no significant issues recalled as Elastic Search has been absolutely awesome for this use case and covers 100% of the needs.
Principal Scientific Computing Software Engineer at a educational organization with 1,001-5,000 employees
If I need to parse one million records saved into Elastic Search, it becomes a nightmare because I need to do the pagination, and it is very problematic in that regard.
Lead Engineer at Spidersilk
Observability features like search latency, indexing rate, and maybe rejected requests should be added to make the platform more reliable and accessible for everyone.
Senior System Engineer at EPAM Systems
When an automation fails, it usually provides the JSON format, and if Tray.io could include a summary of what the actual error entails, that would be quite beneficial.
IT Engineer at a consumer goods company with 51-200 employees
I believe Tray.io can be improved by offering integration with Tableau, which is still not available.
Principal AI and Data Science Engineer at a manufacturing company with 10,001+ employees
There is a steep learning curve in user accessibility; the builder is highly developer-centric, making it difficult for a non-technical team member to modify or troubleshoot workflows.
Automation Engineer at a educational organization with 11-50 employees
 

Setup Cost

Elastic Search offers free open-source and paid plans with varied pricing, noted for both complexity and scalability.
On the AWS side, it is very expensive because they charge based on query basis or how much data is transferred in and out, making it very expensive.
Lead Engineer at Spidersilk
Having the hosted solution and not having to pay for essentially a DevOps person on staff to manage makes it affordable.
CTO at a tech services company with 1-10 employees
You can host it on-premises, which would incur zero cost, or take it as a SaaS-based service, where the expenses remain minimal.
Senior Software Engineer at Agoda
No one has complained in the finance department, and it is very rare for Tata Motors to refrain from complaining about pricing.
Principal AI and Data Science Engineer at a manufacturing company with 10,001+ employees
 

Valuable Features

Elastic Search offers high search capabilities, scalability, real-time efficiency, cost-effectiveness, and seamless integration with tools like Kibana.
Tray.io enhances automation with low-code options, robust tools, vast API connections, and insightful logging for improved workflow efficiency.
Elastic Search makes handling large data volumes efficient and supports complex search operations.
Software Engineer at Government of India
The most valuable feature of Elasticsearch was the quick search capability, allowing us to search by any criteria needed.
Backend Developer
The speed with which Elastic Search is able to search through all of the documents we place into it is quite remarkable, as we search through 65 billion documents in less than a second in most cases, on a constant consistent basis.
Director, Software Engineering at a tech vendor with 10,001+ employees
The connector SDK is also very nice; it has a large library of pre-built connectors that can connect a lot of proprietary internal tools directly into Tray.io, allowing the developer to build, test, and deploy custom connectors using Node.js and integrate the data directly into Tray.io.
Automation Engineer at a educational organization with 11-50 employees
The best features Tray.io offers include the visual workflow builder and HTTP client blocks that enable rapid prototyping and deployment of complex API interactions, including raw HTTP requests, data mappers, and dynamic token generation.
Dev Ops Engineer at a outsourcing company with 201-500 employees
The logging and debugging features in Tray.io have helped us considerably, especially when dealing with APIs that return errors sometimes.
Operations Analyst at a tech vendor with 51-200 employees
 

Categories and Ranking

Elastic Search
Ranking in Cloud Data Integration
5th
Average Rating
8.2
Reviews Sentiment
6.5
Number of Reviews
100
Ranking in other categories
Indexing and Search (1st), Search as a Service (1st), Vector Databases (6th)
Tray.io
Ranking in Cloud Data Integration
17th
Average Rating
7.2
Reviews Sentiment
5.4
Number of Reviews
7
Ranking in other categories
Process Automation (16th), Low-Code Development Platforms (19th), Integration Platform as a Service (iPaaS) (15th)
 

Mindshare comparison

As of August 2026, in the Cloud Data Integration category, the mindshare of Elastic Search is 1.7%, down from 1.9% compared to the previous year. The mindshare of Tray.io is 1.4%, up from 0.4% compared to the previous year. It is calculated based on PeerSpot user engagement data.
Cloud Data Integration Mindshare Distribution
ProductMindshare (%)
Elastic Search1.7%
Tray.io1.4%
Other96.9%
Cloud Data Integration
 

Featured Reviews

reviewer2817942 - PeerSpot reviewer
Senior Software Engineer at a consultancy with 11-50 employees
Logging and vector search have transformed observability and empowered reliable ai agents
Elastic Search is not specifically being used for certain purposes. I deploy Elastic Search database on the cloud and use cloud services so that nobody can attack. However, I do not use Elastic Search to resolve attack issues. The basic main purpose of Elastic Search, as of now, I feel it can do more in the AI area. Sometime I saw that when I am developing RAG and have to generate the embeddings, which I call metadata, sometimes it tries to fail. That durability or issue handling should be improved, but apart from that, I did not find anything as of now. As per my use case, whatever I am using seems pretty good. Apart from that, some definitely improvement will be there. One improvement is that it should be faster. Whenever I am searching any logs, it takes much time. For example, if I open my log in Notepad or a similar tool, I can search the text within a second. With Elastic Search, it takes a little bit of time, ten to fifteen seconds. That can be improved. Sometimes, engineers take time to assign when I create a ticket.
Amrit Dash - PeerSpot reviewer
Automation Engineer at a educational organization with 11-50 employees
Automated student enrollments have reduced manual work and now free our team for higher-value support
Tray.io is definitely a highly powerful tool, but there are three main areas that I feel could be improved. There is a steep learning curve in user accessibility; the builder is highly developer-centric, making it difficult for a non-technical team member to modify or troubleshoot workflows. Introducing a more intuitive visual interface similar to what we have in make.com right now would make the platform much more collaborative and easier to work with for any non-technical folks or newly onboarded engineers, allowing them to be briefed faster. Visual debugging is another area where troubleshooting complex nested loops can feel very abstract. Having clearer, more visual step-by-step data tracking during test runs would speed up the development and testing process. The pricing model is geared heavily towards enterprise budgets; offering more flexible mid-market pricing tiers would make it more accessible for a growing organization that wants a small start and scale up gradually. The core platform security is highly robust and easily meets our requirements for SOC 2 and GDPR compliance. However, when utilizing their AI features such as Merlin AI with sensitive student data, we maintain a very cautious approach. While Tray.io provides enterprise-grade governance guardrails and data masking capabilities, our internal compliance policies prevent us from passing any personally identifiable student information directly through AI-driven processors. We trust Tray.io's underlying infrastructure security, but we believe organizations must still enforce strict data filtering protocols on their end to ensure student privacy is maintained. During our evaluation, we tested the AI capabilities in a sandbox environment, primarily using it to generate workflow drafts and natural language prompts from web data schemas. Strength-wise, it is highly capable when it comes to translating simple text descriptions into functional workflow templates. It serves as a great accelerator, helping to map standard files quickly and reducing the initial setup time for basic integrations. For issues, in the case of highly custom APIs or deeply nested data structures, accuracy declines. We noticed occasional misinterpretation of complex schemas, meaning our developers still had to manually review and correct the outputs. It is a highly helpful productivity booster but still requires human oversight for enterprise-grade reliability.
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Top Industries

By visitors reading reviews
Financial Services Firm
11%
Manufacturing Company
9%
Computer Software Company
7%
Outsourcing Company
7%
Construction Company
14%
Comms Service Provider
13%
Outsourcing Company
11%
Healthcare Company
9%
 

Company Size

By reviewers
Large Enterprise
Midsize Enterprise
Small Business
By reviewers
Company SizeCount
Small Business40
Midsize Enterprise12
Large Enterprise50
By reviewers
Company SizeCount
Small Business4
Midsize Enterprise1
Large Enterprise4
 

Questions from the Community

What is your experience regarding pricing and costs for ELK Elasticsearch?
The pricing for Elastic Search is mainly budgeted according to the organization budget, so we take it as a yearly subscription, and that is acceptable since we do get a fair discount when we are ta...
What needs improvement with ELK Elasticsearch?
When we get the logs, it is mostly about how we edit the configurations and how we make changes according to the requirements of our organization. In these cases, the logs sometimes can be a bit in...
What is your primary use case for ELK Elasticsearch?
I am the Elastic Search admin for my organization, and we are using Elastic Search to handle the traffic to GCP. The monitoring of all the clusters and all the deployments are quite good, and compa...
What needs improvement with Tray.io?
To improve Tray.io, I wish that there was an easier way to download the information of our workflows to have it in some form of an Excel file that explains our workflows that we built, because we h...
What is your primary use case for Tray.io?
My main use case for Tray.io is creating workflows to work with our Zendesk and our other application services. A specific example of a workflow I have set up with Tray.io is that we use our employ...
What advice do you have for others considering Tray.io?
Honestly, I am not sure that we have used anything that really shows how AI helps us with Tray.io at this point. We are still at the basic level of just doing the very basics and have not used any ...
 

Comparisons

 

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.
Copper, DigitalOcean, Udemy, AdRoll, FICO, Outreach
Find out what your peers are saying about Elastic Search vs. Tray.io and other solutions. Updated: August 2026.
909,948 professionals have used our research since 2012.