Elastic Search vs SingleStore comparison

Read 6 SingleStore reviews

2,242 Views
583 Comparison Views

100% willing to recommend

Elastic Search

Comparison Buyer's Guide

Download the report

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: July 2025).

Elastic Search vs. SingleStore

July 2025

Download the complete report

Helped 866,218 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

6.7

Number of Reviews

Ranking in other categories

Indexing and Search (1st), Cloud Data Integration (10th), 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 August 2025, in the Vector Databases category, the mindshare of Elastic Search is 4.7%, down from 6.9% compared to the previous year. The mindshare of SingleStore is 2.0%, up from 1.0% compared to the previous year. It is calculated based on PeerSpot user engagement data.

Vector Databases Market Share Distribution
Product	Market Share (%)
Elastic Search	4.7%
SingleStore	2.0%
Other	93.3%

Vector Databases

Featured Reviews

Anand_Kumar

Enterprise Architect at DXC Technology

Captures data from all other sources and becomes a MOM aka monitoring of monitors

Scalability and ROI are the areas they have to improve. Their license terms are based on the number of cores. If you increase the number of cores, it becomes very difficult to manage at a large scale. For example, if I have a $3 million project, I won't sell it because if we're dealing with a 10 TB or 50 TB system, there are a lot of systems and applications to monitor, and I have to make an MOM (Mean of Max) for everything. This is because of the cost impact. Also, when you have horizontal scaling, it's like a multi-story building with only one elevator. You have to run around, and it's not efficient. Even the smallest task becomes difficult. That's the problem with horizontal scaling. They need to improve this because if they increase the cores and adjust the licensing accordingly, it would make more sense.

Read full review

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.

Read full review

Quotes from Members

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

Pros

"A nonstructured database that can manage large amounts of nonstructured data."

"The UI is very nice, and performance wise it's quite good too."

"The products comes with REST APIs."

"The tool's stability and performance are good."

"The solution has great scalability."

"The search speed is most valuable and important."

"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."

"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

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

"The paramount advantage is the exceptional speed."

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

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

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

"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."

Cons

"Performance improvement could come from skipping background refresh on search idle shards (which is already being addressed in the upcoming seventh version)."

"Elasticsearch should have simpler commands for window filtering."

"There should be more stability."

"New Relic could be more flexible, similar to Elasticsearch."

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

"There are potential improvements based on our client feedback, like unifying the licensing cost structure."

"The solution must provide AI integrations."

"Its licensing needs to be improved. They don't offer a perpetual license. They want to know how many nodes you will be using, and they ask for an annual subscription. Otherwise, they don't give you permission to use it. Our customers are generally military or police departments or customers without connection to the internet. Therefore, this model is not suitable for us. This subscription-based model is not the best for OEM vendors. Another annoying thing about Elasticsearch is its roadmap. We are developing something, and then they say, "Okay. We have removed that feature in this release," and when we are adapting to that release, they say, "Okay. We have removed that one as well." We don't know what they will remove in the next version. They are not looking for backward compatibility from the customers' perspective. They just remove a feature and say, "Okay. We've removed this one." In terms of new features, it should have an ODBC driver so that you can search and integrate this product with existing BI tools and reporting tools. Currently, you need to go for third parties, such as CData, in order to achieve this. ODBC driver is the most important feature required. Its Community Edition does not have security features. For example, you cannot authenticate with a username and password. It should have security features. They might have put it in the latest release."

More Elastic Search cons

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

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

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

"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."

"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."

Pricing and Cost Advice

"ELK has been considered as an alternative to Splunk to reduce licensing costs."

"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."

"An X-Pack license is more affordable than Splunk."

"The premium license is expensive."

"To access all the features available you require both the open source license and the production license."

"The solution is free."

"The version of Elastic Enterprise Search I am using is open source which is free. The pricing model should improve for the enterprise version because it is very expensive."

"There is a free version, and there is also a hosted version for which you have to pay. We're currently using the free version. If things go well, we might go for the paid version."

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."

"SingleStore is a bit expensive."

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

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

See which vendors are best for you

Use our free recommendation engine to learn which Vector Databases solutions are best for your needs.

See recommendations

866,218 professionals have used our research since 2012.

Top Industries

By visitors reading reviews

Computer Software Company

14%

Financial Services Firm

13%

Government

Manufacturing Company

Financial Services Firm

32%

Computer Software Company

12%

Comms Service Provider

Retailer

Company Size

By reviewers

Large Enterprise

Midsize Enterprise

Small Business

By reviewers
Company Size	Count
Small Business	33
Midsize Enterprise	8
Large Enterprise	33

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?

It would be useful if a feature for renaming indices could be added without affecting the performance of other features. However, overall, the consistency and stability of Elasticsearch are already...

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

Comparisons

Xapien vs Elastic Search

Compared 10% of the time

Milvus vs Elastic Search

Compared 9% of the time

Compared 8% of the time

Faiss vs Elastic Search

Compared 6% of the time

Azure AI Search vs Elastic Search

Compared 6% of the time

More Elastic Search Competitors

ClickHouse vs SingleStore

Compared 13% of the time

SQL Server vs SingleStore

Compared 8% of the time

Supabase Vector vs SingleStore

Compared 7% of the time

CockroachDB vs SingleStore

Compared 6% of the time

OpenText Analytics Database (Vertica) vs SingleStore

Compared 6% of the time

More SingleStore Competitors

Product Reports

Download Elastic Search product report

Elastic Search

August 2025

Download SingleStore product report

August 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.