Cassandra vs Pinecone comparison

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Cassandra

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Executive SummaryUpdated on Mar 5, 2025

Cassandra and Pinecone are competing products in the data management and distributed databases category. Pinecone seems to have the upper hand with its advanced feature set tailored for AI applications, while Cassandra is more cost-effective and easier to integrate.

Features: Cassandra offers scalability, high availability, and an open-source platform. Pinecone provides vector search capabilities, integration with machine learning applications, and supports real-time data processing.

Room for Improvement: Cassandra could improve by offering more AI-focused features and better integration with modern data analytics tools. Pinecone might enhance its offerings with more cost-effective solutions, broader documentation, and open-source availability to attract a wider user base.

Ease of Deployment and Customer Service: Cassandra offers straightforward deployment with extensive community support. Pinecone boasts a streamlined deployment process paired with dedicated customer service, enhancing user experience in complex AI setups.

Pricing and ROI: Cassandra is more affordable with lower setup costs and high ROI due to scalability and open-source structure. Pinecone, while having higher setup costs, justifies its investment through powerful search and AI functionalities that can improve ROI, balancing cost efficiency with feature richness.

To learn more, read our detailed Cassandra vs. Pinecone Report (Updated: September 2025).

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Cassandra vs. Pinecone

September 2025

Helped 872,922 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

Cassandra

Ranking in Vector Databases

14th

Average Rating

8.0

Reviews Sentiment

6.0

Number of Reviews

Ranking in other categories

NoSQL Databases (6th)

Pinecone

Ranking in Vector Databases

6th

Average Rating

8.2

Reviews Sentiment

6.8

Number of Reviews

Ranking in other categories

No ranking in other categories

Mindshare comparison

As of November 2025, in the Vector Databases category, the mindshare of Cassandra is 2.0%, up from 1.6% compared to the previous year. The mindshare of Pinecone is 7.4%, down from 8.4% compared to the previous year. It is calculated based on PeerSpot user engagement data.

Vector Databases Market Share Distribution
Product	Market Share (%)
Pinecone	7.4%
Cassandra	2.0%
Other	90.6%

Vector Databases

Featured Reviews

Monirul Islam Khan

Head, Data Integration & Management at a non-profit with 10,001+ employees

Has maintained secure document storage and efficient data distribution with peer-to-peer architecture

The functions or features in Cassandra that I have found most valuable are that it is a distributed system similar to Mongo. It's good enough for comparison with another SQL database, so it's smooth and organized for distributed database system. The peer-to-peer architecture in Cassandra is helpful for network decentralization, and I have already introduced that feature. Cassandra features in peer-to-peer as well as another monitoring, so basically, it's good enough for our service. The tunable consistency level in Cassandra is good, and we are using that feature already. In terms of built-in caching and lightweight transactions in Cassandra, the transaction level is good, and it's optimized, so there are no more issues in that database. Based on my experience, Cassandra is good for document management system, as well as distributed database system, and the automatic recovery process is there. Additionally, the database monitoring system or auditing system is well-comparable with other database systems, so we are actually happy to be using this Cassandra database.

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Pcg Guripati

Chief Technology Advisor at Kovaad technologies Pvt Ltd

Faced challenges with metadata filtering but have achieved reliable long-term memory for chat applications

We were looking at multiple options for a vector database, and we found Pinecone to be the easiest to integrate into our solution. Plus, it has a very generous free tier, which helps us as a startup. The best features Pinecone offers are quick setup and good indexing for us. The retrieval mechanisms are fast, and the integration with Python as with JavaScript and TypeScript libraries that Pinecone provides are very robust. Authentication is also very good. The namespaces feature allows us to break down or store data for each user separately, reducing interference and maintaining privacy as an important feature. Pinecone has positively impacted our organization by enhancing efficiency for the team, and the long-term effect has been that the chats have become much more personalized due to the memory added through a vector database. We are seeing that the trainees getting trained on the platform are more satisfied with the results or messages generated by AI.

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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's database capabilities are very good."

"The time series data was one of the best features along with auto publishing."

"Since I haven't had years of experience with it, it's still new to me. One valuable feature is its distribution, so I can run it partly in the cloud and part on-prem. That's a feature I'd like to use but haven't yet because we're trying to move to Azure. I don't know if or when that will happen. Ideally, we'd have it distributed over the cloud and on-prem simultaneously, so if something happens to our on-prem, we can keep going in the cloud, like a pay-as-you-go model with Azure."

"The use of Cassandra in real-time data analytics has been pivotal for our e-commerce platform. As our platform operates 24/7, providing services to sellers and customers alike, the need for real-time updates is paramount."

"I'd rate the solution ten out of ten."

"The most valuable feature of Cassandra is its fast retrieval. Additionally, the solution can handle large amounts of data. It is the quickest application we use."

"Some of the valued features of this solution are it has good performance and failover."

"Based on my experience, Cassandra is good for document management system, as well as distributed database system, and the automatic recovery process is there."

More Cassandra pros

"The product's setup phase was easy."

"The best thing about Pinecone is its private local host feature. It displays all the maintenance parameters and lets us view the data sent to the database. We can also see the status of the CD and which application it corresponds to."

"We chose Pinecone because it covers most of the use cases."

"The semantic search capability is very good."

"Pinecone has positively impacted our organization by enhancing efficiency for the team, and the long-term effect has been that the chats have become much more personalized due to the memory added through a vector database."

"The most valuable features of the solution are similarity search and maximal marginal relevance search for retrieval purposes."

"The most valuable feature of Pinecone is its managed service aspect. There are many vector databases available, but Pinecone stands out in the market. It is very flexible, allowing us to input any kind of data dimensions into the platform. This makes it easy to use for both technical and non-technical users."

Cons

"We experience configuration issues when accommodating the volumes we require, which often necessitates consultation with the Cassandra development team."

"Doesn't support a solution that can give aggregation."

"Some issues arise from our vendors like Apache slowness and distribution or load balancing from HAProxy, which should better handle consumption for high-level concurrency."

"Maybe they can improve their performance in data fetching from a high volume of data sets."

"I want Cassandra to update its open-source version more quickly. It's already feature-rich, but I'd appreciate better integration with other NoSQL databases like MariaDB or MongoDB. If I ever need to work with customers or vendors using different NoSQL databases, having native integration in Cassandra would make managing and interacting with their databases much easier."

"Batching bulk data can cause performance issues."

"The disc space is lacking. You need to free it up as you are working."

"The solution doesn't have joins between tables so you need other tools for that."

More Cassandra cons

"Pinecone can be made more budget-friendly."

"For testing purposes, the product should offer support locally as it is one area where the tool has shortcomings."

"The tool does not confirm whether a file is deleted or not."

"Onboarding could be better and smoother."

"The product fails to offer a serverless type of storage capacity."

"One major issue I have noticed with Pinecone is that it does not allow me to search based on metadata."

"I want to suggest that Pinecone requires a login and API key, but I would prefer not to have a login system and to use the environment directly."

Pricing and Cost Advice

"Cassandra is a free open source solution, but there is a commercial version available called DataStax Enterprise."

"We are using the open-source version of Cassandra, the solution is free."

"I don't have the specific numbers on pricing, but it was fairly priced."

"There are licensing fees that must be paid, but I'm not sure if they are paid monthly or yearly."

"We pay for a license."

"I use the tool's open-source version."

"I have experience with the tool's free version."

"I think Pinecone is cheaper to use than other options I've explored. However, I also remember that they offer a paid version."

"Pinecone is not cheap; it's actually quite expensive. We find that using Pinecone can raise our budget significantly. On the other hand, using open-source options is more budget-friendly."

"The solution is relatively cheaper than other vector DBs in the market."

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Top Industries

By visitors reading reviews

Financial Services Firm

17%

Computer Software Company

11%

Retailer

Comms Service Provider

Computer Software Company

15%

Financial Services Firm

Manufacturing Company

Comms Service Provider

Company Size

By reviewers

Large Enterprise

Midsize Enterprise

Small Business

By reviewers
Company Size	Count
Small Business	8
Midsize Enterprise	1
Large Enterprise	14

By reviewers
Company Size	Count
Small Business	4
Midsize Enterprise	2
Large Enterprise	1

Questions from the Community

What do you like most about Cassandra?

The use of Cassandra in real-time data analytics has been pivotal for our e-commerce platform. As our platform operates 24/7, providing services to sellers and customers alike, the need for real-ti...

What is your experience regarding pricing and costs for Cassandra?

We are using Cassandra locally and as open-source.

What needs improvement with Cassandra?

While Cassandra can handle NoSQL, I think there should be more flexibility for whole schema design when data is stored in wide columns. Additionally, I believe that eventual consistency should be e...

What do you like most about Pinecone?

We chose Pinecone because it covers most of the use cases.

What needs improvement with Pinecone?

One major issue I have noticed with Pinecone is that it does not allow me to search based on metadata. This can cause problems because while vector indexing or vector search is good, if you populat...

What is your primary use case for Pinecone?

My main use case for Pinecone involves storage of chat data, specifically chat transcripts, and retrieval of matched chat messages. We store chat transcripts as vectors in Pinecone. When we have a ...

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Product Reports

Download Cassandra product report

Cassandra

November 2025

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October 2025

Overview

Cassandra is a distributed and scalable database management system used for real-time data processing.

It is highly valued for its ability to handle large amounts of data, scalability, high availability, fault tolerance, and flexible data model.

It is commonly used in finance, e-commerce, and social media industries.

Apache

Pinecone is a powerful tool for efficiently storing and retrieving vector embeddings. It is highly praised for its scalability, speed, and ease of integration with existing workflows.

Users find it particularly useful for similarity search, recommendation systems, and natural language processing.

Its efficient search capabilities, seamless integration with existing systems, and ability to handle large-scale datasets make it a valuable tool for data analysis and retrieval.

Sample Customers

1. Apple 2. Netflix 3. Facebook 4. Instagram 5. Twitter 6. eBay 7. Spotify 8. Uber 9. Airbnb 10. Adobe 11. Cisco 12. IBM 13. Microsoft 14. Yahoo 15. Reddit 16. Pinterest 17. Salesforce 18. LinkedIn 19. Hulu 20. Airbnb 21. Walmart 22. Target 23. Sony 24. Intel 25. Cisco 26. HP 27. Oracle 28. SAP 29. GE 30. Siemens 31. Volkswagen 32. Toyota

1. Airbnb 2. DoorDash 3. Instacart 4. Lyft 5. Pinterest 6. Reddit 7. Slack 8. Snapchat 9. Spotify 10. TikTok 11. Twitter 12. Uber 13. Zoom 14. Adobe 15. Amazon 16. Apple 17. Facebook 18. Google 19. IBM 20. Microsoft 21. Netflix 22. Salesforce 23. Shopify 24. Square 25. Tesla 26. TikTok 27. Twitch 28. Uber Eats 29. WhatsApp 30. Yelp 31. Zillow 32. Zynga