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Cassandra vs MongoDB vs OpenText Analytics Database (Vertica) comparison

 

Comparison Buyer's Guide

Executive Summary

Review summaries and opinions

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

Mindshare comparison

NoSQL Databases
NoSQL Databases
Data Warehouse
 

Q&A Highlights

it_user1272297 - PeerSpot reviewer
Apr 19, 2020
 

Featured Reviews

Himanshu Amodwala - PeerSpot reviewer
Well-equipped to handle a massive influx of data and billions of requests
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. For instance, when a customer leaves comments or feedback on an image, they anticipate an immediate reflection of these changes on the portal. Similarly, sellers altering product attributes or updating images expect instant visibility of these modifications. Handling large data volumes with Cassandra has been an excellent experience. Despite challenges related to the influx, these were not attributed to Cassandra itself but rather to middle-layer issues. Generally, it demonstrated scalability with workloads, thanks to its horizontal scaling capabilities. We could easily add new nodes to the system as needed, ensuring the platform coped well with increasing loads. The tool's most beneficial feature for scalability is its entire architecture. The absence of a single point of failure or a leader within the ecosystem contributes to its robust scalability. This key aspect influenced our decision to opt for the Cassandra ecosystem. In terms of performance, it demonstrated the ability to handle approximately 1.6 billion requests per day. This was achieved on AWS using EC2 instances, and it was during a period about four to five years ago.
Uzair Faruqi - PeerSpot reviewer
Transforms data flow with adaptable schema and smooth public cloud deployment
One of our business units uses MongoDB, and we developed an ETL pipeline that extracts data from MongoDB and transfers it into our data warehouse MongoDB is a NoSQL database that is similar to a document database. It offers flexibility in schema adaptation, allowing us to change the schema and…
T Venkatesh - PeerSpot reviewer
Processes query faster through multiple systems simultaneously, but it could support different data types
We use the solution for various tasks, including preparing data marts and generating offers. It helps extract data based on rules from the policy team and provides insights to enhance business operations. We also analyze transactions to target customers and improve business performance The…

Quotes from Members

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

Pros

"Overall, I would rate Cassandra as nine because of its fast writes, which really suit our use cases mostly."
"Our primary use case for the solution is testing."
"I am satisfied with the performance."
"Cassandra has some features that are more useful for specific use cases where you have time series where you have huge amounts of writes. That should be quick, but not specifically the reads. We needed to have quicker reads and writes and this is why we are using Cassandra right now."
"Cassandra offers high availability and fault tolerance, making it suitable for large-scale data storage and real-time processing."
"The most valuable features of Cassandra are its scaling capabilities and its non-SQL nature capabilities."
"The most valuable features are the counter features and the NoSQL schema. It also has good scalability. You can scale Cassandra to any finite level."
"I'd rate the solution ten out of ten."
"We haven't had any issues with stability."
"like its performance and the stability. It's very stable and, performance-wise, it's really great."
"It is very fast - faster than an SQL or MySQL Server."
"It is really a pretty easy product to use. It's very reliable, it's proven."
"MongoDB is relatively fast compared to relational databases."
"It's super easy to develop a couple of solutions for clients with MongoDB, like a quick web page with no clear data structure that they need to spin up quickly to validate some sort of MDTP."
"MongoDB is highly stable, and I would rate its stability at nine out of ten."
"MongoDB is simpler to learn and implement than traditional SQL solutions like MySQL."
"DBAs don’t need to add a partition every month/quarter like with other DBs."
"Vertica enabled us to close large deals. Customers with large data sets had to be migrated from PostgreSQL to Vertica due to performance."
"Any novice user can tune vertical queries with minimal training (or no training at all)."
"The solution has great capabilities. The tool that instructs the internal database forward is easy to use and is very powerful."
"It maximizes cloud economics with Eon Mode by scaling cluster size to meet variable workload demands."
"The feature of the product that is most important is the speed. I needed a columnar database, and its speed is what it's built to do, and so that's what really does differentiate Vertica from its competitors."
"Vertica is easy to use and provides really high performance, stability, and scalability."
"Its projections and encoding are excellent tools for tuning large volumes."
 

Cons

"We experience configuration issues when accommodating the volumes we require, which often necessitates consultation with the Cassandra development team."
"Maybe they can improve their performance in data fetching from a high volume of data sets."
"Cassandra is very complex to manage. Sometimes, I need to involve a senior DevOps engineer if we encounter a problem."
"There could be more integration, and it could be more user-friendly."
"The solution is limited to a linear performance."
"The secondary index in Cassandra was a bit problematic and could be improved."
"Batching bulk data can cause performance issues."
"Cassandra can improve by adding more built-in tools. For example, if you want to do some maintenance activities in the cluster, we have to depend on third-party tools. Having these tools build-in would be e benefit."
"They could improve the UI and the analytics part."
"The performance can be improved."
"Sometimes, the tool goes down temporarily. There are some stability issues in the product."
"I feel that most people don't know a lot about MongoDB, so maybe they could add some more documentation and tutorials."
"MongoDB should be more stable, and support should be more efficient."
"It would be much more useful if I have an admin user and a password."
"MongoDB would be improved with more integration, particularly for cloud environments like Google BigQuery."
"Enhancing the documentation to make it more beginner-friendly is crucial."
"The integration with AI has room for improvement."
"It's hard to make it slow for a small data volume. For large volumes, it's hard to make it work. It's also hard to make it faster, and to make it scale."
"There are a lot of limitations within this product and it makes things extremely hard for developers. It lacks Stored Procedure, packages, and triggers like other RDBMs."
"Vertica offers a platform-as-a-service version, but their software-as-a-service solution is only available on AWS. They need to get a SaaS version on Azure and GCP as fast as possible."
"The product could improve by adding support for a wider variety of data types and enhancing features to better compete with other databases."
"Fact-to-fact joins on multi-billion record tables perform poorly."
"It needs integration with multiple clouds."
"Vertica seems to scale well, except for one use case where you are on a multi-node cluster. For example, if you had a nine-node cluster, one node goes down, then the eight nodes don't scale, because the absence of the node is very apparent, which is a problem. If you have nine nodes or multiple nodes, the whole idea is that if one of those nodes goes down, then you should not see an impact on the system if you have enough capacity. Even though we have enough capacity, you can still see the impact of the one node going down."
 

Pricing and Cost Advice

"I don't have the specific numbers on pricing, but it was fairly priced."
"We pay for a license."
"There are licensing fees that must be paid, but I'm not sure if they are paid monthly or yearly."
"I use the tool's open-source version."
"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."
"The solution is open source so is free."
"It's open-source."
"I currently use the solution's community edition which is free."
"The product is affordable."
"MongoDB is an open-source solution."
"MongoDB is an open-source product."
"The solution is open source, so it is free."
"I only used the open-source version."
"It's an expensive product"
"It is fast to purchase through the AWS Marketplace."
"It's free up to three nodes and 1TB, and then get in contact with their sales guys."
"The price is reasonable. We use a pay per license model. Firstly, you need to buy a license. After that, you mainly pay the annual support fee of around 20% or 25%. I think their prices are quite reasonable."
"The solution is relatively cost-effective."
"The pricing could improve, it is a little expensive."
"It's difficult today to compete with open-source solutions. In these areas, there is a lot of competition and the price of this solution is a bit pricy."
"The first TB is free and you can use all the Vertica features. After 1TB you have to pay for licensing. The product is worth it, but be aware of this condition, and plan. The compression ratio is explained in the documentation."
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Answers from the Community

it_user1272297 - PeerSpot reviewer
Apr 19, 2020
Apr 19, 2020
I haven't used SQream personally. However, if you are only considering GPU based rdbms's please check the following https://hackernoon.com/which-gpu-database-is-right-for-me-6ceef6a17505
2 out of 4 answers
Russell Rothstein - PeerSpot reviewer
Jan 27, 2020
Morten, the most popular comparisons of SQream can be found here: https://www.itcentralstation.com/products/sqream-db-alternatives-and-competitors The top ones include Cassandra, MemSQL, MongoDB, and Vertica.
reviewer1219965 - PeerSpot reviewer
Jan 27, 2020
I haven't used SQream personally. However, if you are only considering GPU based rdbms's please check the following https://hackernoon.com/which-gpu-database-is-right-for-me-6ceef6a17505
 

Top Industries

By visitors reading reviews
Financial Services Firm
20%
Computer Software Company
14%
Comms Service Provider
7%
Retailer
6%
Financial Services Firm
16%
Computer Software Company
13%
University
8%
Manufacturing Company
8%
Financial Services Firm
19%
Computer Software Company
17%
Manufacturing Company
8%
Comms Service Provider
4%
 

Company Size

By reviewers
Large Enterprise
Midsize Enterprise
Small Business
 

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 operat...
What needs improvement with Cassandra?
While Cassandra can handle NoSQL, I think there should be more flexibility for whole schema design when data is store...
What do you like most about MongoDB?
MongoDB's approach to handling data in documents rather than traditional tables has been particularly beneficial.
What is your experience regarding pricing and costs for MongoDB?
We pay approximately 2,000 euros per month for MongoDB.
What needs improvement with MongoDB?
I'm not sure about the documentation or the knowledge bases available for MongoDB because I don't interact with it at...
What do you like most about Vertica?
Vertica is easy to use and provides really high performance, stability, and scalability.
What is your experience regarding pricing and costs for Vertica?
The solution is relatively cost-effective. Pricing and licensing are reasonable compared to other solutions.
What needs improvement with Vertica?
The product could improve by adding support for a wider variety of data types and enhancing features to better compet...
 

Also Known As

No data available
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Micro Focus Vertica, HPE Vertica, HPE Vertica on Demand
 

Overview

 

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
Facebook, MetLife, City of Chicago, Expedia, eBay, Google
Cerner, Game Show Network Game, Guess by Marciano, Supercell, Etsy, Nascar, Empirix, adMarketplace, and Cardlytics.
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