Apache Hive vs. Azure Data Lake Storage

Overview
ProductRatingMost Used ByProduct SummaryStarting Price
Apache Hive
Score 8.2 out of 10
N/A
Apache Hive is database/data warehouse software that supports data querying and analysis of large datasets stored in the Hadoop distributed file system (HDFS) and other compatible systems, and is distributed under an open source license.N/A
Azure Data Lake Storage
Score 8.4 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 HiveAzure Data Lake Storage
Editions & Modules
No answers on this topic
No answers on this topic
Offerings
Pricing Offerings
Apache HiveAzure 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 HiveAzure Data Lake Storage
Considered Both Products
Apache Hive

No answer on this topic

Azure Data Lake Storage
Chose Azure Data Lake Storage
We have used both Hadoop and GCS buckets for our storage needs of very large healthcare data. In terms of comparison with the Hadoop distributed Files system, Azure Data Lake Storage always stands in a far better position due to easy integration with various latest and widely …
Top Pros
Top Cons
Best Alternatives
Apache HiveAzure Data Lake Storage
Small Businesses
Google BigQuery
Google BigQuery
Score 8.6 out of 10
Backblaze B2 Cloud Storage
Backblaze B2 Cloud Storage
Score 9.7 out of 10
Medium-sized Companies
Cloudera Enterprise Data Hub
Cloudera Enterprise Data Hub
Score 9.0 out of 10
Azure Blob Storage
Azure Blob Storage
Score 8.7 out of 10
Enterprises
Oracle Exadata
Oracle Exadata
Score 8.2 out of 10
Azure Blob Storage
Azure Blob Storage
Score 8.7 out of 10
All AlternativesView all alternativesView all alternatives
User Ratings
Apache HiveAzure Data Lake Storage
Likelihood to Recommend
8.0
(35 ratings)
8.1
(14 ratings)
Likelihood to Renew
10.0
(1 ratings)
-
(0 ratings)
Usability
8.5
(7 ratings)
-
(0 ratings)
Support Rating
7.0
(6 ratings)
-
(0 ratings)
User Testimonials
Apache HiveAzure Data Lake Storage
Likelihood to Recommend
Apache
Software work execution is on a large scale, it is good to use for new projects or organizational changes, data lineage mapping has always been dubious but this one has had good results. You can store and synchronize data from different departments, the storage process can be manual but it is best automated.
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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
  • Apache Hive allows use to write expressive solutions to complex problems thanks to its SQL-like syntax.
  • Relatively easy to set up and start using.
  • Very little ramp-up to start using the actual product, documentation is very thorough, there is an active community, and the code base is constantly being improved.
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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
  • Some queries, particularly complex joins, are still quite slow and can take hours
  • Previous jobs and queries are not stored sometimes
  • Switching to Impala can sometimes be time-consuming (i.e. the system hangs, or is slow to respond).
  • Sometimes, directories and tables don't load properly which causes confusion
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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
Since I do not know the second data warehouse solution that integrate with HDFS as well as Hive.
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Microsoft
No answers on this topic
Usability
Apache
Hive is a very good big data analysis and ad-hoc query platform, which supports scaling also. The BI processes can be easily integrated with Hadoop via the Hive. It can deal with a much larger data set that traditional RDBMS can not. It is a "must-have" component of the big data domain.
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Microsoft
No answers on this topic
Support Rating
Apache
Apache Hive is a FOSS project and its open source. We need not definitely comment on anything about the support of open source and its developer community. But, it has got tremendous developer support, awesome documentation. I would justify the fact that much support can be gathered from the community backup.
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Microsoft
No answers on this topic
Alternatives Considered
Apache
Besides Hive, I have used Google BigQuery, which is costly but have very high computation speed. Amazon Redshift is the another product, I used in my recent organisation. Both Redshift and BigQuery are managed solution whereas Hive needs to be managed
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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
  • Apache hive is secured and scalable solution that helps in increasing the overall organization productivity.
  • Apache hive can handle and process large amount of data in a sufficient time manner.
  • It simplifies writing SQL queries, hence helping the organization as most companies use SQL for all query jobs.
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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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