Elastic Search vs SingleStore comparison

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Elastic Search

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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: September 2025).

Elastic Search vs. SingleStore

September 2025

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Helped 868,787 peers since 2012

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

3rd

Average Rating

8.2

Reviews Sentiment

6.6

Number of Reviews

Ranking in other categories

Indexing and Search (1st), Cloud Data Integration (9th), Search as a Service (1st)

SingleStore

Ranking in Vector Databases

15th

Average Rating

8.8

Reviews Sentiment

7.4

Number of Reviews

Ranking in other categories

Database as a Service (DBaaS) (12th)

Mindshare comparison

As of October 2025, in the Vector Databases category, the mindshare of Elastic Search is 4.5%, down from 6.9% compared to the previous year. The mindshare of SingleStore is 2.0%, up from 1.1% compared to the previous year. It is calculated based on PeerSpot user engagement data.

Vector Databases Market Share Distribution
Product	Market Share (%)
Elastic Search	4.5%
SingleStore	2.0%
Other	93.5%

Vector Databases

Featured Reviews

Louis McCoy

Director, Software Engineering at Optum Technology

Searches through billions of documents have become impressively fast and consistent

The seamless scalability is something I see as among the best features Elastic Search offers. 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. I find configuring relevant searches within Elastic Search platform very straightforward. Elastic Search is easily scalable. The customer support for Elastic Search is quite good. I advise others looking into using Elastic Search to think about the future of your platform and where you intend it to be in five years, and based on that, which version of Elastic Search best suits the needs of your platform. Additionally, jump into the AI products first as you're in the planning phase so that as you're filling out your data, the AI products and machine learning products can enrich the data real-time early on in the process, which will save you a lot of time later. The overall performance of the platform, scalability of the platform and other additional features, especially when it comes to AI, really earn the nine.

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Yasin Sarı

Senior Data Analyst at a comms service provider with 1,001-5,000 employees

High-speed data processing, seamless scalability, and excellent high availability making it an optimal choice for those prioritizing performance and efficiency in a database solution

There's a noteworthy consideration when it comes to collecting massive amounts of data. It is not the optimal choice for direct data collection through queries, and it's more suited for aggregation tasks. Attempting to use it for direct extraction, for instance, might lead to memory-related challenges. While MySQL version five might lack extensive SQL capabilities, SingleStore also has its constraints, requiring simpler SQL writing. This becomes evident when seeking advanced functionalities like window functions or JSON functions, where SingleStore doesn't offer an extensive toolkit, necessitating a more straightforward approach to SQL.

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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

"The AI-based attribute tagging is a valuable feature."

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

"The most valuable features are the data store and the X-pack extension."

"The solution offers good stability."

"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."

"Elastic Enterprise Search is scalable. On a scale of one to 10, with one being not scalable and 10 being very scalable, I give Elastic Enterprise Search a 10."

"We had many reasons to implement Elasticsearch for search term solutions. Elasticsearch products provide enterprise landscape support for different areas of the company."

"I like how it allows us to connect to Kafka and get this data in a document format very easily. Elasticsearch is very fast when you do text-based searches of documents. That area is very good, and the search is very good."

More Elastic Search pros

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

"The paramount advantage is the exceptional speed."

"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."

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

Cons

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

"Better dashboards or a better configuration system would be very good."

"Something that could be improved is better integrations with Cortex and QRadar, for example."

"Kibana should be more friendly, especially when building dashboards."

"Scalability and ROI are the areas they have to improve."

"The GUI is the part of the program which has the most room for improvement."

"Elasticsearch could improve by honoring Unix environmental variables and not relying only on those provided by Java (e.g. installing plugins over the Unix http proxy)."

"I found an issue with Elasticsearch in terms of aggregation. They are good, yet the rules written for this are not really good."

More Elastic Search cons

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

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

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

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

"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."

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

Pricing and Cost Advice

"The tool is not expensive. Its licensing costs are yearly."

"It can move from $10,000 US Dollars per year to any price based on how powerful you need the searches to be and the capacity in terms of storage and process."

"This product is open-source and can be used free of charge."

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

"The solution is less expensive than Stackdriver and Grafana."

"The tool is an open-source product."

"The solution is free."

More Elastic Search pricing and cost advice

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

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

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

"SingleStore is a bit expensive."

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

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Top Industries

By visitors reading reviews

Computer Software Company

14%

Financial Services Firm

13%

Manufacturing Company

Government

Financial Services Firm

32%

Computer Software Company

12%

Comms Service Provider

University

Company Size

By reviewers

Large Enterprise

Midsize Enterprise

Small Business

By reviewers
Company Size	Count
Small Business	32
Midsize Enterprise	8
Large Enterprise	36

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...

What is your experience regarding pricing and costs for ELK Elasticsearch?

We used the open-source version of Elasticsearch, which was free.

What needs improvement with ELK Elasticsearch?

Elastic Search could improve in areas such as search criteria and query processes, as search times were longer prior to implementing Elastic Search. Elastic Search has limitations for handling huge...

What do you like most about SingleStore DB?

The paramount advantage is the exceptional speed.

What is your experience regarding pricing and costs for SingleStore DB?

Using it for analytical purposes can be cost-effective in the long run, especially in terms of infrastructure. While building an on-premise cluster incurs an initial cost for servers with ample RAM...

What needs improvement with SingleStore DB?

Algolia vs Elastic Search

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Compared 6% of the time

Faiss vs Elastic Search

Compared 5% of the time

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Compared 11% of the time

SQL Server vs SingleStore

Compared 9% of the time

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Compared 8% of the time

CockroachDB vs SingleStore

Compared 7% of the time

Oracle Database vs SingleStore

Compared 6% of the time

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Product Reports

Download Elastic Search product report

Elastic Search

October 2025

Download SingleStore product report

September 2025

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.

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.