Apache Drill vs. Azure Data Lake Storage

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
Azure Data Lake Storage
Score 8.7 out of 10
N/A
Azure Data Lake Storage Gen2 is a highly scalable and cost-effective data lake solution for big data analytics. It combines the power of a high-performance file system with massive scale and economy to help you speed your time to insight. Data Lake Storage Gen2 extends Azure Blob Storage capabilities and is optimized for analytics workloads.N/A
Pricing
Apache DrillAzure Data Lake Storage
Editions & Modules
No answers on this topic
No answers on this topic
Offerings
Pricing Offerings
Apache DrillAzure Data Lake Storage
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 DrillAzure Data Lake Storage
Top Pros
Top Cons
Best Alternatives
Apache DrillAzure Data Lake Storage
Small Businesses
IBM Cloudant
IBM Cloudant
Score 7.9 out of 10
Backblaze B2 Cloud Storage
Backblaze B2 Cloud Storage
Score 9.7 out of 10
Medium-sized Companies
IBM Cloudant
IBM Cloudant
Score 7.9 out of 10
Azure Blob Storage
Azure Blob Storage
Score 8.3 out of 10
Enterprises
IBM Cloudant
IBM Cloudant
Score 7.9 out of 10
Azure Blob Storage
Azure Blob Storage
Score 8.3 out of 10
All AlternativesView all alternativesView all alternatives
User Ratings
Apache DrillAzure Data Lake Storage
Likelihood to Recommend
8.0
(1 ratings)
8.2
(13 ratings)
Likelihood to Renew
7.0
(1 ratings)
-
(0 ratings)
User Testimonials
Apache DrillAzure Data Lake Storage
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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Microsoft
Azure Data Lake is an absolutely essential piece of a modern data and analytics platform. Over the past 2 years, our usage of Azure Data Lake as a reporting source has continued to grow and far exceeds more traditional sources like MS SQL, Oracle, etc.
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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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Microsoft
  • Setting up Azure Data Lake Storage account, container is quite easy
  • Access from anywhere and easy maintenance
  • Integration with Azure Data Factory service for end to end pipeline is pretty easy
  • Can store Any form of data (Structured, Unstructured, Semi) in faster manner
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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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Microsoft
  • study for the certifications also to have them as a reference for work when you have any questions about applying a configuration to the equipment.
  • The Internet interface is simple and easy to use. Capacity is good and it's good that HP continues to innovate with this technology
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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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Microsoft
No answers on this topic
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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Microsoft
Azure Data Lake Storage from a functionality perspective is a much easier solution to work with. It's implementation from Amazon EMR went smooth, and continued usage is definitely better. However, Amazon EMR was significantly cheaper overall between the high transaction fees and cost of storage due to growth. The two both have their advantages and disadvantages, but the functionality of Azure Data Lake Storage outweighed it's cost
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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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Microsoft
  • Instead of having separate pools of storage for data we are now operating on a single layer platform which has cut down on time spent on maintaining those separate pools.
  • We have had more of an ROI with the scalability as we are able to control costs of storage when need be.
  • We are able to operate in a more streamlined approach as we are able to stay within the Azure suite of products and integrate seamlessly with the rest of the applications in our cloud-based infrastructure
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ScreenShots