Elastic Search vs PostgreSQL comparison

Read 125 PostgreSQL reviews

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Elastic Search

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Executive SummaryUpdated on Mar 5, 2025

PostgreSQL and Elasticsearch compete in the database and search engine markets respectively, addressing versatile data management needs. In terms of features, PostgreSQL offers extensive database functionalities, while Elasticsearch excels in search capabilities, making them leaders in their domains for specific use cases.

Features: PostgreSQL includes full SQL compliance, support for various programming languages, and robust documentation. It is known for write-intensive task scalability and extensibility. Elasticsearch, on the other hand, provides real-time search capabilities, is optimized for handling extensive text-based data, and integrates well with other tools for data indexing and search.

Room for Improvement: PostgreSQL could improve its read-only query performance and add SQL features like 'INSERT IGNORE' to compete with NoSQL in handling large data volumes. Elasticsearch faces challenges in usability and data management over large indices. Enhancing its machine learning integration and adopting more flexible licensing could enhance its enterprise appeal.

Ease of Deployment and Customer Service: Both PostgreSQL and Elasticsearch offer on-premises and cloud deployment options. PostgreSQL provides broader hybrid cloud deployment support, whereas Elasticsearch sees frequent implementation in both private and public cloud environments. Community support is rich for both, but PostgreSQL enjoys more commendations for active engagement, unlike Elasticsearch, which could benefit from improved documentation and streamlined support services.

Pricing and ROI: PostgreSQL's open-source nature keeps it free, bringing immediate ROI against commercial rivals like Oracle, reducing costs significantly. Elasticsearch, also open-source, offers paid features for advanced capabilities. It balances skilled support costs with node-based licensing, making it cost-effectively flexible compared to expensive solutions like Splunk, with suitability depending on whether traditional data management or advanced search analytics is the focus.

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

Elastic Search vs. PostgreSQL

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 (6th), Search as a Service (1st)

PostgreSQL

Ranking in Vector Databases

11th

Average Rating

8.4

Reviews Sentiment

7.7

Number of Reviews

125

Ranking in other categories

Open Source Databases (2nd)

Mindshare comparison

As of January 2026, in the Vector Databases category, the mindshare of Elastic Search is 4.0%, down from 6.5% compared to the previous year. The mindshare of PostgreSQL is 5.7%, up from 4.1% compared to the previous year. It is calculated based on PeerSpot user engagement data.

Vector Databases Market Share Distribution
Product	Market Share (%)
Elastic Search	4.0%
PostgreSQL	5.7%
Other	90.3%

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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Akhilesh Chipre

Senior Assosiate Consultant at Applied Materials

Real-time data capture optimizes database performance but Views create problems

One of the most valuable features is real-time data capture; it optimizes database performance. I think using real-time data capture reduces job running time and the amount of data sent at once with batch loads. Replicating the same data daily isn't optimal, so real-time reception improves application performance and reduces latency.

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

"The solution has good security features. I have been happy with the dashboards and interface."

"The most valuable feature for us is the analytics that we can configure and view using Kibana."

"Elastic Search's main advantages are the visuals that represent and visualize all entities and system components in a simplified diagram, which provides the ability to identify which component in the system has an issue."

"The product is scalable with good performance."

"The initial setup is very easy for small environments."

"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."

"Elastic Search makes handling large data volumes efficient and supports complex search operations."

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

More Elastic Search pros

"The solution is open-source and free to use."

"We use the solution to store tables. It is stable and performs well."

"The PostgreSQL database is similar to the SQL Server but has a slightly different technology that has similar resources as well. If the customer has the confidence using SQL Server, they will be fairly comfortable using this solution."

"The product is very similar to the SQL Server."

"It's a standard reliable database management system."

"It is very useful for both structured and unstructured data. You can store unstructured and structured data in PostgreSQL. It is easy to use. You can easily manage things through PostgreSQL Admin. It is cost-effective. Its on-premise version is free. It is agnostic of on-premise or cloud. You can install it on the cloud or on-premises. It is available with all clouds, and you can also install it on desktop or Windows Servers."

"The solution is scalable, it is very good."

"Initial setup is simple."

Cons

"We see the need for some improvements with Elasticsearch. We would like the Elasticsearch package to include training lessons for our staff."

"Elastic Search should provide better guides for developers."

"The documentation for Elastic Search can be challenging if you're not already familiar with the platform."

"Ratio aggregation is not supported in this solution."

"I would rate technical support from Elastic Search as three out of ten. The main issue is a general sum of all factors."

"I think the first area for improvement is pricing, as the cluster cost for Elastic Search is too high for me."

"Could have more open source tools and testing."

"The most significant issue I find with Elastic Search is that it gets out of sync, and this has happened in both cases where I have implemented it."

More Elastic Search cons

"It still needs to be more mature and have some backup feature. We are normally dealing with Oracle's data, and we have very strong online tools to back up the data and do other things. PostgreSQL still needs to do more in this area as well as in the high availability area. There are many external tools that you can use for PostgreSQL's high availability, but there is no embedded tool within PostgreSQL for high availability. It could have a feature similar to Oracle for working on a distributed system. It can have some scripts to improve the monitoring and some tools to do performance analysis. We have a workaround for most of such requirements except for the support for a distributed system, which is very difficult to have. This area should be included in the core of the database itself."

"The interface climate could be better."

"There are some products out there that have a slightly different method of implementation for the SQL language. Some of those are slightly better in some areas, and PostgreSQL is slightly better in some areas. I would probably like to match all of those products together. It is just down to the functionality. For example, Oracle has a number of options within SQL that are outside of what you would class as the SQL standard. PostgreSQL misses some of those, but PostgreSQL does other things that are better than what Oracle does. I would like to merge those two products so that there is a certain amount of functionality in a single product."

"Integration with other platforms could be improved."

"It could be improved by using parallelization. You want basically, distributed computing."

"PostgreSQL uses high memory compared to its counterparts when a highly demanding load is involved, especially one that makes many concurrent connections to the database."

"I had some issues when I integrated with the Jupyter Notebook."

"PostgreSQL could improve by providing a geographical solution for tracking trucks and people in the field. They might already have features similar to this and I have not found them. I haven't done research about this topic."

Pricing and Cost Advice

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

"The basic license is free, but it comes with a lot of features that aren't free. With a gold license, we get active directory integration. With a platinum license, we get alerting."

"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."

"It can be expensive."

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

"The tool is an open-source product."

"Although the ELK Elasticsearch software is open-source, we buy the hardware."

"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."

More Elastic Search pricing and cost advice

"The community version of Postgre is basically free."

"It is open source. There is no licensing."

"It is also open-source so it is free."

"The licensing model is good."

"We do not pay for licensing."

"We use the open-source version of PostgreSQL and not the enterprise edition."

"We are using the free version of PostgreSQL."

"It is an open-source platform."

Top Industries

By visitors reading reviews

Financial Services Firm

13%

Computer Software Company

12%

Manufacturing Company

10%

Government

Computer Software Company

13%

Financial Services Firm

11%

Comms Service Provider

10%

Manufacturing Company

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	57
Midsize Enterprise	26
Large Enterprise	46

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?

Elastic Search's pricing totally depends on the server. Managed services from AWS are used, and we have worked on a self-managed Elastic Search cluster. On the AWS side, it is very expensive becaus...

What needs improvement with ELK Elasticsearch?

To be honest, there is only one downside of Elastic Search that makes sense because we use a basic license, which is a free license. We do not have some features available because of the free licen...

How does Firebird SQL compare with PostgreSQL?

PostgreSQL was designed in a way that provides you with not only a high degree of flexibility but also offers you a cheap and easy-to-use solution. It gives you the ability to redesign and audit yo...

What do you like most about PostgreSQL?

It's a transactional database, so we use Postgres for most of our reporting. That's where it's helping.

What is your experience regarding pricing and costs for PostgreSQL?

The tool is free of cost. For now, it's not about making money. But once we perfect it, we can offer it to customers willing to pay for support and other services. Most of my deployments are free.

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Compared 25% of the time

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Compared 10% of the time

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Product Reports

Download Elastic Search product report

Elastic Search

January 2026

Download PostgreSQL product report

January 2026

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

PostgreSQL is a versatile and reliable database management system commonly used for web development, data analysis, and building scalable databases.

It offers advanced features like indexing, replication, and transaction management. Users appreciate its flexibility, performance, and ability to handle large amounts of data efficiently. Its robustness, scalability, and support for complex queries make it highly valuable.

Additionally, PostgreSQL's extensibility, flexibility, community support, and frequent updates contribute to its ongoing improvement and stability.

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.

1. Apple 2. Cisco 3. Fujitsu 4. Instagram 5. Netflix 6. Red Hat 7. Sony 8. Uber 9. Cisco Systems 10. Skype 11. LinkedIn 12. Etsy 13. Yelp 14. Reddit 15. Dropbox 16. Slack 17. Twitch 18. WhatsApp 19. Snapchat 20. Shazam 21. SoundCloud 22. The New York Times 23. Cisco WebEx 24. Atlassian 25. Cisco Meraki 26. Heroku 27. GitLab 28. Zalando 29. OpenTable 30. Trello 31. Square Enix 32. Bloomberg