Hortonworks Data Platform (HDP) was an open source framework for distributed storage and processing of large, multi-source data sets. Hortonworks merged with Cloudera in eary 2019. Cloudera has since stopped supporting Hortonworks, and it is no longer publicly available for download.
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MongoDB
Score8.8 out of 10
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MongoDB is an open source document-oriented database system. It is part of the NoSQL family of database systems. Instead of storing data in tables as is done in a "classical" relational database, MongoDB stores structured data as JSON-like documents with dynamic schemas (MongoDB calls the format BSON), making the integration of data in certain types of applications easier and faster.
$0.10
million reads
Pricing
Hortonworks Data Platform (discontinued)
MongoDB
Editions & Modules
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Shared
$0
per month
Serverless
$0.10million reads
million reads
Dedicated
$57
per month
Offerings
Pricing Offerings
Hortonworks Data Platform (discontinued)
MongoDB
Free Trial
No
Yes
Free/Freemium Version
No
Yes
Premium Consulting/Integration Services
No
No
Entry-level Setup Fee
No setup fee
No setup fee
Additional Details
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Fully managed, global cloud database on AWS, Azure, and GCP
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.
A de minimis incentive was given to thank the reviewer for their time. The incentive was not used to bias or drive a particular response, nor was the incentive contingent on a positive endorsement. More Info
If asked by a colleague I would highly recommend MongoDB. MongoDB provides incredible flexibility and is quick and easy to set up. It also provides extensive documentation which is very useful for someone new to the tool. Though I've used it for years and still referenced the docs often. From my experience and the use cases I've worked on, I'd suggest using it anywhere that needs a fast, efficient storage space for non-relational data. If a relational database is needed then another tool would be more apt.
A de minimis incentive was given to thank the reviewer for their time. The incentive was not used to bias or drive a particular response, nor was the incentive contingent on a positive endorsement. More Info
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.
A de minimis incentive was given to thank the reviewer for their time. The incentive was not used to bias or drive a particular response, nor was the incentive contingent on a positive endorsement. More Info
Being a JSON language optimizes the response time of a query, you can directly build a query logic from the same service
You can install a local, database-based environment rather than the non-relational real-time bases such a firebase does not allow, the local environment is paramount since you can work without relying on the internet.
Forming collections in Mango is relatively simple, you do not need to know of query to work with it, since it has a simple graphic environment that allows you to manage databases for those who are not experts in console management.
A de minimis incentive was given to thank the reviewer for their time. The incentive was not used to bias or drive a particular response, nor was the incentive contingent on a positive endorsement. More Info
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.
A de minimis incentive was given to thank the reviewer for their time. The incentive was not used to bias or drive a particular response, nor was the incentive contingent on a positive endorsement. More Info
An aggregate pipeline can be a bit overwhelming as a newcomer.
There's still no real concept of joins with references/foreign keys, although the aggregate framework has a feature that is close.
Database management/dev ops can still be time-consuming if rolling your own deployments. (Thankfully there are plenty of providers like Compose or even MongoDB's own Atlas that helps take care of the nitty-gritty.
A de minimis incentive was given to thank the reviewer for their time. The incentive was not used to bias or drive a particular response, nor was the incentive contingent on a positive endorsement. More Info
I am looking forward to increasing our SaaS subscriptions such that I get to experience global replica sets, working in reads from secondaries, and what not. Can't wait to be able to exploit some of the power that the "Big Boys" use MongoDB for.
A de minimis incentive was given to thank the reviewer for their time. The incentive was not used to bias or drive a particular response, nor was the incentive contingent on a positive endorsement. More Info
NoSQL database systems such as MongoDB lack graphical interfaces by default and therefore to improve usability it is necessary to install third-party applications to see more visually the schemas and stored documents. In addition, these tools also allow us to visualize the commands to be executed for each operation.
A de minimis incentive was given to thank the reviewer for their time. The incentive was not used to bias or drive a particular response, nor was the incentive contingent on a positive endorsement. More Info
Finding support from local companies can be difficult. There were times when the local company could not find a solution and we reached a solution by getting support globally. If a good local company is found, it will overcome all your problems with its global support.
A de minimis incentive was given to thank the reviewer for their time. The incentive was not used to bias or drive a particular response, nor was the incentive contingent on a positive endorsement. More Info
A de minimis incentive was given to thank the reviewer for their time. The incentive was not used to bias or drive a particular response, nor was the incentive contingent on a positive endorsement. More Info
While the setup and configuration of MongoDB is pretty straight forward, having a vendor that performs automatic backups and scales the cluster automatically is very convenient. If you do not have a system administrator or DBA familiar with MongoDB on hand, it's a very good idea to use a 3rd party vendor that specializes in MongoDB hosting. The value is very well worth it over hosting it yourself since the cost is often reasonable among providers.
A de minimis incentive was given to thank the reviewer for their time. The incentive was not used to bias or drive a particular response, nor was the incentive contingent on a positive endorsement. More Info
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
A de minimis incentive was given to thank the reviewer for their time. The incentive was not used to bias or drive a particular response, nor was the incentive contingent on a positive endorsement. More Info
We have [measured] the speed in reading/write operations in high load and finally select the winner = MongoDBWe have [not] too much data but in case there will be 10 [times] more we need Cassandra. Cassandra's storage engine provides constant-time writes no matter how big your data set grows. For analytics, MongoDB provides a custom map/reduce implementation; Cassandra provides native Hadoop support.
A de minimis incentive was given to thank the reviewer for their time. The incentive was not used to bias or drive a particular response, nor was the incentive contingent on a positive endorsement. More Info
Open Source w/ reasonable support costs have a direct, positive impact on the ROI (we moved away from large, monolithic, locked in licensing models)
You do have to balance the necessary level of HA & DR with the number of servers required to scale up and scale out. Servers cost money - so DR & HR doesn't come for free (even though it's built into the architecture of MongoDB
