Try our new research platform with insights from 80,000+ expert users

Elastic Search vs SingleStore comparison

 

Comparison Buyer's Guide

Executive SummaryUpdated on Mar 5, 2025

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
4.1
Elastic Search boosts efficiency, reduces search times, improves security, lowers costs, and enhances product scaling and performance.
Sentiment score
6.9
SingleStore offers cost-efficient, scalable solutions with easy setup, supporting enterprise-level transactional and analytical needs in one platform.
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
The objective was to scale as data loads with high-performing query model responses.
Senior Software Engineer at Honeywell
 

Customer Service

Sentiment score
6.3
Elastic Search's support is praised for expertise and responsiveness, despite occasional delays and suggestions for faster response times.
Sentiment score
7.6
SingleStore's 24/7 proactive support is highly rated, personalized, and effective, using Zendesk for prioritization and dedicated onboarding support.
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
It has been sufficient to visit conferences such as SCALE in Southern California Linux Expo, where Elastic Search has a booth to talk to their staff.
Principal Scientific Computing Software Engineer at a educational organization with 1,001-5,000 employees
The customer support is very proactive and responsive twenty-four hours per day, seven days per week.
Senior Software Engineer at Honeywell
 

Scalability Issues

Sentiment score
7.3
Elasticsearch is highly scalable and efficient, requiring proper infrastructure planning for expanding and managing large datasets successfully.
Sentiment score
8.1
SingleStore efficiently scales with minimal downtime, handling extensive queries and complex tasks, despite challenges with data growth.
I would rate its scalability a ten.
Backend Developer
Since we're on the cloud, whenever we need to upgrade or add resources, they handle everything.
Security Lead at a tech vendor with 501-1,000 employees
We haven't encountered any problems so far, and there is the potential for auto-scaling.
Head of Data Management at Zeno Health
SingleStore's scalability is high and it can be used by any size of organization and can handle any needs of any organization.
Senior Software Engineer at Honeywell
 

Stability Issues

Sentiment score
7.7
Elastic Search offers strong stability, reliable performance, and efficient scalability across various environments, with occasional configuration needs.
Sentiment score
8.4
SingleStore is rated highly stable, with most downtime caused by external factors, receiving ratings between seven and ten.
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
I have not seen any downtime.
Senior Software Engineer at Honeywell
 

Room For Improvement

Elastic Search needs cost clarity, improved performance, user experience, configuration simplicity, scalability, documentation, and advanced machine learning features.
SingleStore users need improved Azure integration, better documentation, advanced SQL features, and optimized data handling and server tools.
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
Error handling needs attention. When it fails due to memory, it only indicates that but not exactly in which process it failed.
Senior Software Engineer at Honeywell
 

Setup Cost

Elastic Search pricing varies by usage and features, offering flexibility but potential high costs with complex deployments.
SingleStore's pricing is cost-effective for large firms with flexible cloud tiers and free on-premises licensing for startups.
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
My experience with pricing, setup cost, and licensing is that it can be a bit expensive for startups.
Senior Software Engineer at Honeywell
 

Valuable Features

Elastic Search excels in full-text search, scalability, data indexing, visualization, AI features, and integrates well for enterprise solutions.
SingleStore offers fast recovery, high data compression, and scalability, enhancing performance, productivity, and efficient data processing with seamless integration.
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
SingleStore has impacted my organization positively by enabling us to run low-latency analytics and model-driven use cases at scale, which is quite difficult for OLAP and OLTP databases alone.
Senior Software Engineer at Honeywell
 

Categories and Ranking

Elastic Search
Ranking in Vector Databases
2nd
Average Rating
8.2
Reviews Sentiment
6.5
Number of Reviews
90
Ranking in other categories
Indexing and Search (1st), Cloud Data Integration (6th), Search as a Service (1st)
SingleStore
Ranking in Vector Databases
17th
Average Rating
8.8
Reviews Sentiment
7.3
Number of Reviews
7
Ranking in other categories
Database as a Service (DBaaS) (17th)
 

Mindshare comparison

As of March 2026, in the Vector Databases category, the mindshare of Elastic Search is 4.0%, down from 6.2% compared to the previous year. The mindshare of SingleStore is 2.6%, up from 1.7% compared to the previous year. It is calculated based on PeerSpot user engagement data.
Vector Databases Mindshare Distribution
ProductMindshare (%)
Elastic Search4.0%
SingleStore2.6%
Other93.4%
Vector Databases
 

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.
Kelvin  Ben - PeerSpot reviewer
Senior Software Engineer at Honeywell
Real-time analytics has transformed daily decisions and delivers fast dashboards from streaming data
The best features SingleStore offers include fast data recovery and data compression by 80 percent. Having the information in sheets helps me to process the information quickly. Simplicity in T-SQL is another aspect I appreciate. Data recovery and sheet-based processing help my team on a day-to-day basis by enabling us to handle information efficiently. I would like to add that the data compression by 80 percent helps us in an excellent way since we are very fast in obtaining the data for our dashboards and the compression of the information is great. SingleStore has impacted my organization positively by enabling us to run low-latency analytics and model-driven use cases at scale, which is quite difficult for OLAP and OLTP databases alone. It has been very helpful because our internal clients are happy to have the data and make data-driven decisions easily. Making decisions based on data within a two-hour delay to the transactional database is excellent since we went from twenty-four hours to two hours. I think the best contribution is decision-making with data that is close to reality. Reducing that delay from twenty-four hours to two hours has significantly affected my team and business outcomes by increasing productivity. We have been able to serve all our customers, and they are very happy. We can deliver to them on time.
report
Use our free recommendation engine to learn which Vector Databases solutions are best for your needs.
884,873 professionals have used our research since 2012.
 

Top Industries

By visitors reading reviews
Financial Services Firm
12%
Computer Software Company
11%
Manufacturing Company
9%
Retailer
7%
Financial Services Firm
30%
Computer Software Company
9%
Comms Service Provider
8%
Retailer
5%
 

Company Size

By reviewers
Large Enterprise
Midsize Enterprise
Small Business
By reviewers
Company SizeCount
Small Business38
Midsize Enterprise10
Large Enterprise45
By reviewers
Company SizeCount
Small Business4
Large Enterprise4
 

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...
Ask a question
Earn 20 points
 

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.
400+ customers including: 6sense, Adobe, Akamai, Ant Money, Arcules, CARFAX, Cigna, Cisco, Comcast, DELL, DBS Bank, Dentsu, DirectlyApply, EY, Factors.AI, Fathom Analytics, FirstEnergy, GE, Goldman Sachs, Heap, Hulu, IMAX, impact.com, Kroger, LG, LiveRamp, Lumana, Nvidia, OpenDialog, Outreach, Palo Alto Networks, PicPay, RBC, Samsung, SegMetrics, Siemens, SiteImprove, SiriusXM, SK Telecom, SKAI, SONY, STC, SunRun, TATA, Thorn, ZoomInfo.
Find out what your peers are saying about Elastic Search vs. SingleStore and other solutions. Updated: February 2026.
884,873 professionals have used our research since 2012.