Elastic Search vs PostgreSQL comparison

Read 125 PostgreSQL reviews

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96% willing to recommend

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: March 2025).

Elastic Search vs. PostgreSQL

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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

6.7

Number of Reviews

Ranking in other categories

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

PostgreSQL

Ranking in Vector Databases

9th

Average Rating

8.4

Reviews Sentiment

7.7

Number of Reviews

125

Ranking in other categories

Open Source Databases (2nd)

Mindshare comparison

As of April 2025, in the Vector Databases category, the mindshare of Elastic Search is 5.8%, down from 7.1% compared to the previous year. The mindshare of PostgreSQL is 4.8%, up from 3.4% compared to the previous year. It is calculated based on PeerSpot user engagement data.

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.

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AdityaSharma3

Vice President Business at Techmagnate: Digital Marketing Agency

Transaction processes are fast and good replication capability

Use cases include querying data warehouses and databases to fetch data for clients already working on PostgreSQL. We also use Postgres for building reports It's a transactional database, so we use Postgres for most of our reporting. That's where it's helping. The query speed is fast, and the…

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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 solution offers good stability."

"ELK Elasticsearch is 100% scalable as scalability is built into the design"

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

"It's a stable solution and we have not had any issues."

"The initial installation and setup were straightforward."

"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."

"I appreciate that Elastic Enterprise Search is easy to use and that we have people on our team who are able to manage it effectively."

"I have found the sort capability of Elastic very useful for allowing us to find the information we need very quickly."

More Elastic Search pros

"It is very simple to manage."

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

"Initial setup is simple."

"The product is easy to use and works fast for relational databases."

"We managed to reduce the storage space needed to 10% of the original size, without affecting data integrity, and we significantly improved the performance."

"PostgreSQL is very easy to use. I have experience in Oracle SQL and PostgreSQL uses the same syntax which makes it is easy for me to develop."

"It has completely met our needs. It works, and it is robust. We haven't had any problems with what PostgreSQL does for us and the way it does it. That's why we've been using it for so long. We understand it, and it does the job."

"The initial setup is quick and easy."

Cons

"Elastic Enterprise Search could improve the report templates."

"Both the graph feature and the reporting feature are a little bit lacking. The alerting also needs to be improved."

"Enterprise scaling of what have been essentially separate, free open source software (FOSS) products has been a challenge, but the folks at Elastic have published new add-ons (X-Pack and ECE) to help large companies grow ELK to required scales."

"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."

"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)."

"The metadata gets stored along with indexes and isn't queryable."

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

"While integrating with tools like agents for ingesting data from sources like firewalls is valuable, I believe prioritizing improvements to the core product would be more beneficial."

More Elastic Search cons

"It would be good to have machine learning functionality in this solution, similar to Microsoft SQL Server and other solutions. Machine learning capability for a basic level or a common user would be useful. It can also have good reporting capabilities."

"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."

"Sometimes, it becomes slow because of the network. So, there is room for improvement in performance."

"I'm not really able to customize it."

"It needs more integration."

"The scalability is limited."

"The user interface for the clients could be easier to use as they are small businesses. From a technical support perspective, the documentation could be improved."

"Sometimes, the views create problems. If you don't have the view, sometimes what happens is you need to have the drivers properly set up for PostgreSQL."

Pricing and Cost Advice

"The pricing and license model are clear: node-based model."

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

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

"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."

"The price could be better."

"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."

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

"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 solution requires a license."

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

"Our company pays for it. There are free versions available, but for advanced features, you obviously have to pay."

"It is an open-source platform."

"It is free. There is no license on it."

"PostgreSQL is open-source, so if capable admins are available then the setup cost can be $0."

"The licensing model is good."

"It is free. In terms of operating costs, it basically needs the same platform on which Oracle runs."

Top Industries

By visitors reading reviews

Computer Software Company

18%

Financial Services Firm

15%

Government

Manufacturing Company

Computer Software Company

16%

Financial Services Firm

12%

Comms Service Provider

Manufacturing Company

Company Size

By reviewers

Large Enterprise

Midsize Enterprise

Small Business

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?

I don't know about pricing. That is dealt with by the sales team and our account team. I was not involved with that.

What needs improvement with ELK Elasticsearch?

I found an issue with Elasticsearch in terms of aggregation. They are good, yet the rules written for this are not really good. There is a maximum of 10,000 entries, so the limitation means that if...

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.

Pinecone vs Elastic Search

Comparisons

Milvus vs Elastic Search

Compared 13% of the time

Faiss vs Elastic Search

Compared 9% of the time

Compared 6% of the time

Azure Search vs Elastic Search

Compared 6% of the time

LanceDB vs Elastic Search

Compared 5% of the time

More Elastic Search Competitors

Firebird SQL vs PostgreSQL

Compared 37% of the time

MySQL vs PostgreSQL

Compared 14% of the time

EDB Postgres Advanced Server vs PostgreSQL

Compared 11% of the time

MariaDB vs PostgreSQL

Compared 8% of the time

Chroma vs PostgreSQL

Compared 7% of the time

Product Reports

Elastic Search

Download Elastic Search product report

Download PostgreSQL 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

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

Elastic Search vs. PostgreSQL