Apache Drill vs. MongoDB

Overview
ProductRatingMost Used ByProduct SummaryStarting Price
Apache Drill
Score 8.1 out of 10
N/A
Apache Drill is a schema-free query engine for use with NoSQL or Hadoop data or file storage systems and databases.N/A
MongoDB
Score 8.0 out of 10
N/A
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
Apache DrillMongoDB
Editions & Modules
No answers on this topic
Shared
$0
per month
Serverless
$0.10million reads
million reads
Dedicated
$57
per month
Offerings
Pricing Offerings
Apache DrillMongoDB
Free Trial
NoYes
Free/Freemium Version
NoYes
Premium Consulting/Integration Services
NoNo
Entry-level Setup FeeNo setup feeNo setup fee
Additional DetailsFully managed, global cloud database on AWS, Azure, and GCP
More Pricing Information
Features
Apache DrillMongoDB
NoSQL Databases
Comparison of NoSQL Databases features of Product A and Product B
Apache Drill
-
Ratings
MongoDB
9.1
38 Ratings
4% above category average
Performance00 Ratings9.038 Ratings
Availability00 Ratings9.738 Ratings
Concurrency00 Ratings8.638 Ratings
Security00 Ratings8.638 Ratings
Scalability00 Ratings9.438 Ratings
Data model flexibility00 Ratings9.138 Ratings
Deployment model flexibility00 Ratings9.137 Ratings
Best Alternatives
Apache DrillMongoDB
Small Businesses
IBM Cloudant
IBM Cloudant
Score 8.3 out of 10
IBM Cloudant
IBM Cloudant
Score 8.3 out of 10
Medium-sized Companies
IBM Cloudant
IBM Cloudant
Score 8.3 out of 10
IBM Cloudant
IBM Cloudant
Score 8.3 out of 10
Enterprises
IBM Cloudant
IBM Cloudant
Score 8.3 out of 10
IBM Cloudant
IBM Cloudant
Score 8.3 out of 10
All AlternativesView all alternativesView all alternatives
User Ratings
Apache DrillMongoDB
Likelihood to Recommend
8.0
(1 ratings)
9.4
(78 ratings)
Likelihood to Renew
7.0
(1 ratings)
10.0
(67 ratings)
Usability
-
(0 ratings)
9.0
(14 ratings)
Availability
-
(0 ratings)
9.0
(1 ratings)
Support Rating
-
(0 ratings)
9.6
(13 ratings)
Implementation Rating
-
(0 ratings)
8.4
(2 ratings)
User Testimonials
Apache DrillMongoDB
Likelihood to Recommend
Apache
if you're doing joins from hBASE, hdfs, cassandra and redis, then this works. Using it as a be all end all does not suit it. This is not your straight forward magic software that works for all scenarios. One needs to determine the use case to see if Apache Drill fits the needs. 3/4 of the time, usually it does.
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MongoDB
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.
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Pros
Apache
  • queries multiple data sources with ease.
  • supports sql, so non technical users who know sql, can run query sets
  • 3rd party tools, like tableau, zoom data and looker were able to connect with no issues
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MongoDB
  • 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.
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Cons
Apache
  • deployment. Not as easy
  • configuration isn't as straight forward, especially with the documentation
  • Garbage collection could be improved upon
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MongoDB
  • 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.
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Likelihood to Renew
Apache
if Presto comes up with more support (ie hbase, s3), then its strongly possible that we'll move from apache drill to prestoDB. However, Apache drill needs more configuration ease, especially when it comes to garbage collection tuning. If apache drill could support also sparkSQL and Flume, then it does change drill into being something more valuable than prestoDB
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MongoDB
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.
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Usability
Apache
No answers on this topic
MongoDB
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.
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Support Rating
Apache
No answers on this topic
MongoDB
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.
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Implementation Rating
Apache
No answers on this topic
MongoDB
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.
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Alternatives Considered
Apache
compared to presto, has more support than prestodb. Impala has limitations to what drill can support apache phoenix only supports for hbase. no support for cassandra. Apache drill was chosen, because of the multiple data stores that it supports htat the other 3 do not support. Presto does not support hbase as of yet. Impala does not support query to cassandra
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MongoDB
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.
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Return on Investment
Apache
  • Configuration has taken some serious time out.
  • Garbage collection tuning. is a constant hassle. time and effort applied to it, vs dedicating resources elsewhere.
  • w/ sql support, reduces the need of devs to generate the resultset for analysts, when they can run queries themselves (if they know sql).
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MongoDB
  • 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
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ScreenShots

MongoDB Screenshots

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