Elastic Search vs SingleStore comparison

Elastic and SingleStore are both solutions in the Vector Databases category. Elastic is ranked #2 with an average rating of 8.4, while SingleStore is ranked #17. Elastic holds a 3.9% mindshare in VD, compared to SingleStore’s 2.4% mindshare. Additionally, 97% of Elastic users are willing to recommend the solution, compared to 100% of SingleStore users who would recommend it.

Elastic Search

Read 88 Elastic Search reviews

8,328 Views
3,165 Comparison Views

97% willing to recommend

SingleStore

Read 6 SingleStore reviews

2,429 Views
850 Comparison Views

100% willing to recommend

Elastic Search

SingleStore

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Executive SummaryUpdated on Mar 5, 2025

Elastic Search and SingleStore compete in the data analytics and log monitoring category. Based on feature richness and scalability, Elastic Search appears to have the upper hand, while SingleStore excels in performance and SQL compatibility.

Features: Elastic Search offers advanced log monitoring and flexible data indexing, with tools like Logstash and Kibana that enhance search capabilities and visualization. Its scalability and enterprise landscape support make it a strong choice for analyzing rich data sets. SingleStore is known for its MySQL compatibility, fast data ingestion, and distributed architecture, excelling in high concurrency and in-memory storage for analytical tasks.

Room for Improvement: Elastic Search could improve its open-source security features, machine learning capabilities, and user-friendliness. It also needs better pricing transparency and technical support. SingleStore could benefit from more built-in SQL features, improved partition distribution, and enhanced documentation. Expanding connectivity with other services and simplifying SQL functionalities for complex operations is needed.

Ease of Deployment and Customer Service: Both Elastic Search and SingleStore are deployed widely across on-premises and cloud environments. Elastic Search benefits from a strong community and extensive documentation but could improve its direct technical support. SingleStore provides moderate technical support and could enhance community resources and response times.

Pricing and ROI: Elastic Search provides a good ROI as an open-source product, though premium feature licensing costs can be high and the pricing model complicated. SingleStore offers a competitive, clear pricing structure beneficial for long-term analytical and storage needs. Initial and ongoing costs should be carefully weighed for ROI optimization.

To learn more, read our detailed Elastic Search vs. SingleStore Report (Updated: December 2025).

Buyer's Guide

Elastic Search vs. SingleStore

December 2025

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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 Vector Databases

2nd

Average Rating

8.2

Reviews Sentiment

6.5

Number of Reviews

Ranking in other categories

Indexing and Search (1st), Cloud Data Integration (5th), Search as a Service (1st)

SingleStore

Ranking in Vector Databases

17th

Average Rating

8.8

Reviews Sentiment

7.4

Number of Reviews

Ranking in other categories

Database as a Service (DBaaS) (17th)

Mindshare comparison

As of February 2026, in the Vector Databases category, the mindshare of Elastic Search is 3.9%, down from 6.4% compared to the previous year. The mindshare of SingleStore is 2.4%, up from 1.6% compared to the previous year. It is calculated based on PeerSpot user engagement data.

Vector Databases Market Share Distribution
Product	Market Share (%)
Elastic Search	3.9%
SingleStore	2.4%
Other	93.7%

Vector Databases

Featured Reviews

Vaibhav Shukla

Senior Software Engineer at Agoda

Search performance has transformed large-scale intent discovery and hybrid query handling

While Elastic Search is a good product, I see areas for improvement, particularly regarding the misconception that any amount of data can simply be dumped into Elastic Search. When creating an index, careful consideration of data massaging is essential. Elastic Search stores mappings for various data types, which must remain below a certain threshold to maintain functionality. Users need to throttle the number of fields for searching to avoid overloading the system and ensure that the design of the document is efficient for the Elastic Search index. Additionally, I suggest utilizing ILM periodically throughout the year to manage data shuffling between clusters, preventing hotspots in the distribution of requests across nodes.

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Vignesh KR

Solution Architect at Wipro Limited

An excellent choice for diverse data processing needs with exceptional in-memory capabilities, robust failover mechanisms, easy scalability and high performance

Scalability is its key strength. Adding servers for scalability is a straightforward process involving simply incorporating a few additional servers and recycling the cluster triggers automatic repartitioning and redistribution of data. For instance, if the initial database creation involved a hundred servers and later, four more servers are added, specific commands can be executed to increase the partitions to one hundred twenty. The data is then efficiently redistributed across the expanded partitions without the need for manual data movement, ensuring a seamless and efficient scalability process. In my current organization, approximately three projects involve the usage of SingleStore, with a team size ranging from ten to twenty individuals.

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Quotes from Members

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

Pros

"There's lots of processing power. You can actually just add machines to get more performance if you need to. It's pretty flexible and very easy to add another log. It's not like 'oh, no, it's going to be so much extra data'. That's not a problem for the machine. It can handle it."

"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 analytics with Elastic benefits us due to the huge traffic volume in our organization, which reaches up to 60,000 requests per second. With logs of approximately 25 GB per day, manually analyzing traffic behavior, payloads, headers, user agents, and other details is impractical."

"The product is scalable with good performance."

"You have dashboards, it is visual, there are maps, you can create canvases. It's more visual than anything that I've ever used."

"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."

"Elastic Search has impacted my organization positively as we use it for logging and APM."

"X-Pack provides good features, like authorization and alerts."

"Using real-time search functionality to support operational decisions has been helpful."

More Elastic Search pros

"MemSQL supports the MySQL protocol, and many functions are similar, so the learning curve is very short."

"The ability to store data in memory is a standout feature, enhanced by robust failover mechanisms."

"It's a distributed relational database, so it does not have a single server, it has multiple servers. Its architecture itself is fast because it has multiple nodes to distribute the workload and process large amounts of data."

"The most valuable feature is the ability to create pipelines, streamline and extract data from the pipelines."

"The product can automatically reinstall and reconfigure in case of a shutdown."

"The paramount advantage is the exceptional speed."

Cons

"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. With every kind of search engine, there is some kind of special function that you need to do. A simple out-of-the-box search would be useful."

"It needs email notification, similar to what Logentries has. Because of the notification issue, we moved to Logentries, as it provides a simple way to receive notification whenever a server encounters an error or unexpected conditions (which we have defined using RegEx)."

"The one area that can use improvement is the automapping of fields."

"What they need is to be more transparent about the actual setup of the cluster and the deployment process."

"I think the pricing of Elastic Search is really, really expensive."

"Elastic Search needs to improve authentication. It also needs to work on the Kibana visualization dashboard."

"The solution must provide AI integrations."

"There is another solution I'm testing which has a 500 record limit when you do a search on Elastic Enterprise Search. That's the only area in which I'm not sure whether it's a limitation on our end in terms of knowledge or a technical limitation from Elastic Enterprise Search. There is another solution we are looking at that rides on Elastic Enterprise Search. And the limit is for any sort of records that you're doing or data analysis you're trying to do, you can only extract 500 records at a time. I know the open-source nature has a lot of limitations, Otherwise, Elastic Enterprise Search is a fantastic solution and I'd recommend it to anyone."

More Elastic Search cons

"We don't get good discounts in Pakistan."

"For new customers, it's very tough to start. Their documentation isn't organized, and there's no online training available. SingleStore is working on it, but that's a major drawback."

"Having the ability to migrate servers using a single command would be extremely beneficial."

"There should be more pipelines available because I think that if MemSQL can connect to other services, that would be great."

"Poor key distribution can significantly impact performance, requiring a backward approach in design rather than adding tables incrementally."

"It is not the optimal choice for direct data collection through queries, and it's more suited for aggregation tasks."

Pricing and Cost Advice

"The pricing model is questionable and needs to be addressed because when you would like to have the security they charge per machine."

"we are using a licensed version of the product."

"The solution is not expensive because users have the option of choosing the managed or the subscription model."

"The price of Elastic Enterprise is very, very competitive."

"I rate Elastic Search's pricing an eight out of ten."

"We are paying $1,500 a month to use the solution. If you want to have endpoint protection you need to pay more."

"Elastic Search is open-source, but you need to pay for support, which is expensive."

"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."

More Elastic Search pricing and cost advice

"I would advise users to try the free 128GB version."

"They have two main options: cloud installation and bare-metal installation, each with different pricing models."

"The product's licensing is not expensive. It is comparable."

"Using it for analytical purposes can be cost-effective in the long run, especially in terms of infrastructure."

"SingleStore is a bit expensive."

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Top Industries

By visitors reading reviews

Financial Services Firm

12%

Computer Software Company

12%

Manufacturing Company

Government

Financial Services Firm

30%

Computer Software Company

10%

Comms Service Provider

Retailer

Company Size

By reviewers

Large Enterprise

Midsize Enterprise

Small Business

By reviewers
Company Size	Count
Small Business	37
Midsize Enterprise	10
Large Enterprise	43

By reviewers
Company Size	Count
Small Business	4
Large Enterprise	3

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...

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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.

See all answers

What needs improvement with ELK Elasticsearch?

See all answers

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Comparisons

Xapien vs Elastic Search

Compared 15% of the time

Algolia vs Elastic Search

Compared 8% of the time

Azure AI Search vs Elastic Search

Compared 6% of the time

Milvus vs Elastic Search

Compared 4% of the time

LanceDB vs Elastic Search

Compared 3% of the time

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ClickHouse vs SingleStore

Compared 7% of the time

SQL Server vs SingleStore

Compared 6% of the time

Supabase Vector vs SingleStore

Compared 5% of the time

CockroachDB vs SingleStore

Compared 5% of the time

OpenText Analytics Database (Vertica) vs SingleStore

Compared 5% of the time

More SingleStore Competitors

Product Reports

Buyer's Guide

Elastic Search

January 2026

Download Elastic Search product report

Buyer's Guide

SingleStore

January 2026

Download SingleStore product report

Also Known As

Elastic Enterprise Search, Swiftype, Elastic Cloud

No data available

Overview

Elasticsearch is a prominent open-source search and analytics engine known for its scalability, reliability, and straightforward management. It's a favored choice among enterprises for real-time data search, analysis, and visualization. Open-source Elasticsearch is free, offering a comprehensive feature set and scalability. It allows full control over deployments but requires managing and maintaining the infrastructure. On the other hand, Elastic Cloud provides a managed service with features like automated provisioning, high availability, security, and global reach.

Elasticsearch excels in handling time-sensitive data and complex search requirements across large datasets. Its scalability allows it to handle growing data volumes efficiently, maintaining high performance and fast response times. Integrated with Kibana, Elasticsearch enables powerful data visualization, providing real-time insights crucial for data-driven decision-making.

Elastic Cloud reduces operational overhead and improves scalability and performance, though it comes with associated costs. It is available on your preferred cloud provider — AWS, Azure, or Google Cloud. Customers who want to manage the software themselves, whether on public, private, or hybrid cloud, can download the Elastic Stack.

At its core, Elasticsearch is renowned for its full-text search capabilities, capable of performing complex queries and supporting features like fuzzy matching and auto-complete.

Peer reviews from various professionals highlight its strengths and weaknesses. Pros include its detection and correlation features, flexibility, cloud-readiness, extensibility, and efficient search capabilities. However, users have noted challenges like steep learning curves, data analysis limitations, and integration complexities. The platform is generally viewed as stable and scalable, with varying degrees of satisfaction regarding its usability and feature set.

In summary, Elasticsearch stands out for its high-speed search, scalability, and versatile analytics, making it a go-to solution for organizations managing large datasets. Its adaptability to different enterprise needs, robust community support, and continuous development keep it at the forefront of enterprise search and analytics solutions. However, potential users should be aware of its learning curve and the need for skilled personnel for optimization.

Elastic

SingleStore delivers the performance you need for enterprise AI, providing the most performant data platform for apps and analytics at scale. SingleStore enables organizations to scale from one to one million customers in one unified platform. SingleStore offers transparent pricing as shown here https://www.singlestore.com/pricing/

SingleStore caters to over 400 customers globally, including major banks and tech companies in 50+ countries and 40+ verticals. It offers seamless scaling for both transactional and analytical workloads, simplifying data management with its MySQL compatibility and real-time processing capabilities. SingleStore's distributed architecture ensures speed and reliability, efficiently handling large data volumes.

What are the key features of SingleStore?

MySQL Compatibility: Eases the learning curve for users.
Built-in Pipelines: Connects to S3, Kafka, and more.
High Concurrency: Processes billions of records swiftly.
Replication & Failover: Enhances speed and reliability.
In-memory Storage: Ensures data safety and quick access.

What benefits can users find in SingleStore reviews?

Automatic Reconfiguration: Simplifies management tasks.
Impressive SQL Performance: Supports complex queries efficiently.
Scalability: Handles large datasets with a multi-node setup.

Top banks and fintech companies leverage SingleStore for efficient management of financial data, while media and telecom industries use it for scalable metadata management and improved data processing. Retail and eCommerce sectors benefit from enhanced transactional capabilities, reducing the need for separate databases and optimizing reporting processes. SingleStore's capacity to unite diverse workloads makes it a strategic choice across many sectors.

SingleStore

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.

Buyer's Guide

Elastic Search vs. SingleStore

December 2025

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