What users are saying about
128 Ratings
128 Ratings
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Score 8.8 out of 100
163 Ratings
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Score 8.1 out of 100

Likelihood to Recommend

Apache Spark

The software appears to run more efficiently than other big data tools, such as Hadoop. Given that, Apache Spark is well-suited for querying and trying to make sense of very, very large data sets. The software offers many advanced machine learning and econometrics tools, although these tools are used only partially because very large data sets require too much time when the data sets get too large. The software is not well-suited for projects that are not big data in size. The graphics and analytical output are subpar compared to other tools.
Thomas Young | TrustRadius Reviewer

Azure SQL Database

The most important positive for our organization is the ability to scale up or down at will. As a startup, we needed to quickly adapt to changing space and performance needs. It's also integral as we grow different branches of the business. Thus far, we haven't encountered much of anything with the tool that hasn't been a good fit for our business.
Anonymous | TrustRadius Reviewer

Feature Rating Comparison

Database-as-a-Service

Apache Spark
Azure SQL Database
9.0
Automatic software patching
Apache Spark
Azure SQL Database
8.9
Database scalability
Apache Spark
Azure SQL Database
9.2
Automated backups
Apache Spark
Azure SQL Database
8.9
Database security provisions
Apache Spark
Azure SQL Database
9.2
Monitoring and metrics
Apache Spark
Azure SQL Database
8.8
Automatic host deployment
Apache Spark
Azure SQL Database
8.9

Pros

Apache Spark

  • Rich APIs for data transformation making for very each to transform and prepare data in a distributed environment without worrying about memory issues
  • Faster in execution times compare to Hadoop and PIG Latin
  • Easy SQL interface to the same data set for people who are comfortable to explore data in a declarative manner
  • Interoperability between SQL and Scala / Python style of munging data
Nitin Pasumarthy | TrustRadius Reviewer

Azure SQL Database

  • Scalability is #1: if it used to be an almost no-win endeavour to try to modernize your server or migrate to other hardware, with Azure SQL Database it becomes a press of a button.
  • All the tools simply work after you are on Azure SQL Database.
  • The applications do not need changes in order to start using Azure SQL Database.
  • Hybrid Cloud scenarios will work.
  • Clustering and failover - already there.
  • You can start monitoring the use and extract performance insights in a new way in Azure.
Arthur Zubarev | TrustRadius Reviewer

Cons

Apache Spark

  • Memory management. Very weak on that.
  • PySpark not as robust as scala with spark.
  • spark master HA is needed. Not as HA as it should be.
  • Locality should not be a necessity, but does help improvement. But would prefer no locality
Anson Abraham | TrustRadius Reviewer

Azure SQL Database

  • A little slow on processing complex or large Views. We use a lot of Views to feed our BI system, and the processing time could see some improvement, IMHO.
  • Additional monitoring components would be nice too, automating some built in performance measurement tools would be a nice feature.
  • Price can always be improved as well. It’s not bad, but room for improvement.
Anonymous | TrustRadius Reviewer

Likelihood to Renew

Apache Spark

No score
No answers yet
No answers on this topic

Azure SQL Database

Azure SQL Database 8.0
Based on 1 answer
This is best solution as a DBA one could expect from a service provider and as a cloud service, it removes all your hassles.
Zimran Azim | TrustRadius Reviewer

Usability

Apache Spark

Apache Spark 8.7
Based on 3 answers
Apache integrates with multiple big data frameworks. It does not exert too much load on the disks. Moreover, it is easy to program and use. It reduces the headache of using different applications separately through its high-level APIs. Big data processing has never been as easy as it is with Apache Spark.
Partha Protim Pegu | TrustRadius Reviewer

Azure SQL Database

No score
No answers yet
No answers on this topic

Support Rating

Apache Spark

Apache Spark 8.3
Based on 6 answers
1. It integrates very well with scala or python.2. It's very easy to understand SQL interoperability.3. Apache is way faster than the other competitive technologies.4. The support from the Apache community is very huge for Spark.5. Execution times are faster as compared to others.6. There are a large number of forums available for Apache Spark.7. The code availability for Apache Spark is simpler and easy to gain access to.8. Many organizations use Apache Spark, so many solutions are available for existing applications.
Yogesh Mhasde | TrustRadius Reviewer

Azure SQL Database

Azure SQL Database 9.0
Based on 6 answers
We give the support a high rating simply because every time we've had issues or questions, representatives were in contact with us quickly. Without fail, our issues/questions were handled in a timely matter. That kind of response is integral when client data integrity and availability is in question. There is also a wealth of documentation for resolving issues on your own.
Anonymous | TrustRadius Reviewer

Alternatives Considered

Apache Spark

Spark in comparison to similar technologies ends up being a one stop shop. You can achieve so much with this one framework instead of having to stitch and weave multiple technologies from the Hadoop stack, all while getting incredibility performance, minimal boilerplate, and getting the ability to write your application in the language of your choosing.
Anonymous | TrustRadius Reviewer

Azure SQL Database

Comparing with Amazon Aurora: Azure SQL DB is 100% compatible with SQL Server and Aurora is compatible with MySQL and PostGreSQL. Because of if, SQL DB suits large enterprises with hundreds of databases better. Comparing with Oracle: the main issue is that Oracle will try to push all other services available in their product offering.
Anonymous | TrustRadius Reviewer

Return on Investment

Apache Spark

  • It has had a very positive impact, as it helps reduce the data processing time and thus helps us achieve our goals much faster.
  • Being easy to use, it allows us to adapt to the tool much faster than with others, which in turn allows us to access various data sources such as Hadoop, Apache Mesos, Kubernetes, independently or in the cloud. This makes it very useful.
  • It was very easy for me to use Apache Spark and learn it since I come from a background of Java and SQL, and it shares those basic principles and uses a very similar logic.
Carla Borges | TrustRadius Reviewer

Azure SQL Database

  • Our database costs have decreased over time by 20%.
  • Our engineer spends much less time managing API calls with some of the new features available.
  • Our engineer is planning on using the Power Query embedded feature to streamline some ETL processes.
Scott Kennedy | TrustRadius Reviewer

Pricing Details

Apache Spark

General

Free Trial
Free/Freemium Version
Premium Consulting/Integration Services
Entry-level set up fee?
No

Apache Spark Editions & Modules

Additional Pricing Details

Azure SQL Database

General

Free Trial
Free/Freemium Version
Premium Consulting/Integration Services
Entry-level set up fee?
No

Azure SQL Database Editions & Modules

Edition
2 vCORE$0.50441
6 vCORE$1.51311
10 vCORE$2.521
  1. Per Hour
Additional Pricing Details

Rating Summary

Likelihood to Recommend

Apache Spark
8.6
Azure SQL Database
9.2

Likelihood to Renew

Apache Spark
Azure SQL Database
8.0

Usability

Apache Spark
8.7
Azure SQL Database

Support Rating

Apache Spark
8.3
Azure SQL Database
9.0

Add comparison