Apache Cassandra vs. Hortonworks Data Platform

Overview
ProductRatingMost Used ByProduct SummaryStarting Price
Cassandra
Score 7.7 out of 10
N/A
Cassandra is a no-SQL database from Apache.N/A
Hortonworks Data Platform
Score 7.0 out of 10
N/A
Hortonworks Data Platform (HDP) is an open source framework for distributed storage and processing of large, multi-source data sets. HDP modernizes IT infrastructure and keeps data secure—in the cloud or on-premises—while helping to drive new revenue streams, improve customer experience, and control costs. Hortonworks merged with Cloudera in eary 2019.N/A
Pricing
Apache CassandraHortonworks Data Platform
Editions & Modules
No answers on this topic
No answers on this topic
Offerings
Pricing Offerings
CassandraHortonworks Data Platform
Free Trial
NoNo
Free/Freemium Version
NoNo
Premium Consulting/Integration Services
NoNo
Entry-level Setup FeeNo setup feeNo setup fee
Additional Details
More Pricing Information
Community Pulse
Apache CassandraHortonworks Data Platform
Top Pros
Top Cons
Features
Apache CassandraHortonworks Data Platform
NoSQL Databases
Comparison of NoSQL Databases features of Product A and Product B
Apache Cassandra
8.0
5 Ratings
9% below category average
Hortonworks Data Platform
-
Ratings
Performance8.55 Ratings00 Ratings
Availability8.85 Ratings00 Ratings
Concurrency7.65 Ratings00 Ratings
Security8.05 Ratings00 Ratings
Scalability9.55 Ratings00 Ratings
Data model flexibility6.75 Ratings00 Ratings
Deployment model flexibility7.05 Ratings00 Ratings
Best Alternatives
Apache CassandraHortonworks Data Platform
Small Businesses
IBM Cloudant
IBM Cloudant
Score 8.3 out of 10

No answers on this topic

Medium-sized Companies
IBM Cloudant
IBM Cloudant
Score 8.3 out of 10
Cloudera Manager
Cloudera Manager
Score 9.7 out of 10
Enterprises
IBM Cloudant
IBM Cloudant
Score 8.3 out of 10
IBM Analytics Engine
IBM Analytics Engine
Score 8.8 out of 10
All AlternativesView all alternativesView all alternatives
User Ratings
Apache CassandraHortonworks Data Platform
Likelihood to Recommend
6.0
(16 ratings)
7.0
(9 ratings)
Likelihood to Renew
8.6
(16 ratings)
-
(0 ratings)
Usability
7.0
(1 ratings)
-
(0 ratings)
Support Rating
7.0
(1 ratings)
-
(0 ratings)
Implementation Rating
7.0
(1 ratings)
9.0
(1 ratings)
User Testimonials
Apache CassandraHortonworks Data Platform
Likelihood to Recommend
Apache
Apache Cassandra is a NoSQL database and well suited where you need highly available, linearly scalable, tunable consistency and high performance across varying workloads. It has worked well for our use cases, and I shared my experiences to use it effectively at the last Cassandra summit! http://bit.ly/1Ok56TK It is a NoSQL database, finally you can tune it to be strongly consistent and successfully use it as such. However those are not usual patterns, as you negotiate on latency. It works well if you require that. If your use case needs strongly consistent environments with semantics of a relational database or if the use case needs a data warehouse, or if you need NoSQL with ACID transactions, Apache Cassandra may not be the optimum choice.
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Cloudera
I find HDP easy to use and solves most of the problems for people looking to manage their big data. Evaluating the Hortonworks Data Platform is easy as it is free to download and install in your cluster. Single node cluster available as Sandbox is also easy for POCs.
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Pros
Apache
  • Continuous availability: as a fully distributed database (no master nodes), we can update nodes with rolling restarts and accommodate minor outages without impacting our customer services.
  • Linear scalability: for every unit of compute that you add, you get an equivalent unit of capacity. The same application can scale from a single developer's laptop to a web-scale service with billions of rows in a table.
  • Amazing performance: if you design your data model correctly, bearing in mind the queries you need to answer, you can get answers in milliseconds.
  • Time-series data: Cassandra excels at recording, processing, and retrieving time-series data. It's a simple matter to version everything and simply record what happens, rather than going back and editing things. Then, you can compute things from the recorded history.
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Cloudera
  • It does a good job of packaging a lot of big data components into bundles and lets you use the ones you are interested in or need. It supports an extensive list of components which lets us solve many problems.
  • It provides the ability to manage installations and maintenance using Apache Ambari. It helps us in using management packs to install/upgrade components easily. It also helps us add, remove components, add, remove hosts, perform upgrades in a convenient manner. It also provides alerts and notifications and monitors the environment.
  • What they excel in is packaging open source components that are relevant and are useful to solve and complement each other as well as contribute to enhancing those components. They do a great job in the community to keep on top of what would be useful to users, fixing bugs and working with other companies and individuals to make the platform better.
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Cons
Apache
  • Cassandra runs on the JVM and therefor may require a lot of GC tuning for read/write intensive applications.
  • Requires manual periodic maintenance - for example it is recommended to run a cleanup on a regular basis.
  • There are a lot of knobs and buttons to configure the system. For many cases the default configuration will be sufficient, but if its not - you will need significant ramp up on the inner workings of Cassandra in order to effectively tune it.
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Cloudera
  • Since it doesn't come with propriety tools for big data management, additional integration is need (for query handling, search, etc).
  • It was very straightforward to store clinical data without relations, such as data from sensors of a medical device. But it has limitations when needed to combine the data with other clinical data in structured format (e.g. lab results, diagnosis).
  • Overall look and feel of front-end management tools (e.g. monitoring) are not good. It is not bad but it doesn't look professional.
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Likelihood to Renew
Apache
I would recommend Cassandra DB to those who know their use case very well, as well as know how they are going to store and retrieve data. If you need a guarantee in data storage and retrieval, and a DB that can be linearly grown by adding nodes across availability zones and regions, then this is the database you should choose.
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Cloudera
No answers on this topic
Usability
Apache
It’s great tool but it can be complicated when it comes administration and maintenance.
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Cloudera
No answers on this topic
Support Rating
Apache
Sometimes instead giving straight answer, we ‘re getting transfered to talk professional service.
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Cloudera
No answers on this topic
Implementation Rating
Apache
No answers on this topic
Cloudera
Try not to change variable names.
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Alternatives Considered
Apache
We evaluated MongoDB also, but don't like the single point failure possibility. The HBase coupled us too tightly to the Hadoop world while we prefer more technical flexibility. Also HBase is designed for "cold"/old historical data lake use cases and is not typically used for web and mobile applications due to its performance concern. Cassandra, by contrast, offers the availability and performance necessary for developing highly available applications. Furthermore, the Hadoop technology stack is typically deployed in a single location, while in the big international enterprise context, we demand the feasibility for deployment across countries and continents, hence finally we are favor of Cassandra
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Cloudera
We chose [Hortonworks Data Platform] because it's free and because [it] was an IBM partner, suggested as big data platform after biginsights platform.
You can install in more physical computer without high specs, then you can use it in order to learn how to deploy, configure a complete big data cluster.
We installed also in a cloud infrastructure of 5 virtual machine
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Return on Investment
Apache
  • I have no experience with this but from the blogs and news what I believe is that in businesses where there is high demand for scalability, Cassandra is a good choice to go for.
  • Since it works on CQL, it is quite familiar with SQL in understanding therefore it does not prevent a new employee to start in learning and having the Cassandra experience at an industrial level.
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Cloudera
  • It is difficult to have a negative impact, because the required investment is not that high.
  • The big open community behind Hortonworks and related Apache Project makes it easy to put 'the wheel to meet the road' quite quickly.
  • We have seen management meetings where the attendants were impressed by the results achieved with the datalake built on HDP.
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