Compare Apache Spark Streaming vs. Databricks

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Apache Spark Streaming Logo
3,478 views|3,275 comparisons
Databricks Logo
27,869 views|23,272 comparisons
Top Review
Find out what your peers are saying about Apache Spark Streaming vs. Databricks and other solutions. Updated: September 2021.
535,919 professionals have used our research since 2012.
Quotes From Members

We asked business professionals to review the solutions they use. Here are some excerpts of what they said:

Pros
"The solution is better than average and some of the valuable features include efficiency and stability.""The solution is very stable and reliable."

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"We are completely satisfied with the ease of connecting to different sources of data or pocket files in the search""Automation with Databricks is very easy when using the API.""Databricks is based on a Spark cluster and it is fast. Performance-wise, it is great.""The most valuable aspect of the solution is its notebook. It's quite convenient to use, both terms of the research and the development and also the final deployment, I can just declare the spark jobs by the load tables. It's quite convenient.""I work in the data science field and I found Databricks to be very useful.""The time travel feature is the solution's most valuable aspect.""I haven't heard about any major stability issues. At this time I feel like it's stable.""Imageflow is a visual tool that helps make it easier for business people to understand complex workflows."

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Cons
"There could be an improvement in the area of the user configuration section, it should be less developer-focused and more business user-focused.""The solution itself could be easier to use."

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"The integration features could be more interesting, more involved.""Some of the error messages that we receive are too vague, saying things like "unknown exception", and these should be improved to make it easier for developers to debug problems.""It should have more compatible and more advanced visualization and machine learning libraries.""The solution could be improved by integrating it with data packets. Right now, the load tables provide a function, like team collaboration. Still, it's unclear as to if there's a function to create different branches and/or more branches. Our team had used data packets before, however, I feel it's difficult to integrate the current with the previous data packets.""It would be very helpful if Databricks could integrate with platforms in addition to Azure.""Databricks is an analytics platform. It should offer more data science. It should have more features for data scientists to work with.""Pricing is one of the things that could be improved.""The product needs samples and templates to help invite users to see results and understand what the product can do."

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Pricing and Cost Advice
Information Not Available
"Whenever we want to find the actual costing, we have to send an email to Databricks, so having the information available on the internet would be helpful.""I do not exactly know the costs, but one of our clients pays between $100 USD and $200 USD monthly.""Licensing on site I would counsel against, as on-site hardware issues tend to really delay and slow down delivery.""We find Databricks to be very expensive, although this improved when we found out how to shut it down at night.""The pricing depends on the usage itself.""I am based in South Africa, where it is expensive adapting to the cloud, and then there is the price for the tool itself.""The price is okay. It's competitive.""Databricks uses a price-per-use model, where you can use as much compute as you need."

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Questions from the Community
Top Answer: The solution is better than average and some of the valuable features include efficiency and stability.
Top Answer: There could be an improvement in the area of the user configuration section, it should be less developer-focused and more business user-focused. For example, it is still not plug and play and use as… more »
Top Answer: The primary use of the solution is to implement predictive maintenance qualities.
Top Answer: The initial setup is pretty easy.
Top Answer: I can't speak on pricing of the solution. It's not an aspect of the solution I deal with directly.
Top Answer: The product is quite ambitious. It's trying to become a centralized platform for all data ingestion, transformation, and analytics needs. It may encounter a stiff competition from best of breed… more »
Ranking
9th
out of 36 in Streaming Analytics
Views
3,478
Comparisons
3,275
Reviews
2
Average Words per Review
334
Rating
7.5
1st
out of 36 in Streaming Analytics
Views
27,869
Comparisons
23,272
Reviews
24
Average Words per Review
552
Rating
8.0
Comparisons
Also Known As
Spark Streaming
Databricks Unified Analytics, Databricks Unified Analytics Platform, Redash
Learn More
Overview

Spark Streaming makes it easy to build scalable fault-tolerant streaming applications.

Databricks creates a Unified Analytics Platform that accelerates innovation by unifying data science, engineering, and business. It utilizes Apache Spark to help clients with cloud-based big data processing. It puts Spark on “autopilot” to significantly reduce operational complexity and management cost. The Databricks I/O module (DBIO) improves the read and write performance of Apache Spark in the cloud. An increase in productivity is ensured through Databricks’ collaborative workplace.

Offer
Learn more about Apache Spark Streaming
Learn more about Databricks
Sample Customers
UC Berkeley AMPLab, Amazon, Alibaba Taobao, Kenshoo, eBay Inc.
Elsevier, MyFitnessPal, Sharethrough, Automatic Labs, Celtra, Radius Intelligence, Yesware
Top Industries
VISITORS READING REVIEWS
Computer Software Company29%
Comms Service Provider15%
Media Company10%
Financial Services Firm9%
REVIEWERS
Financial Services Firm20%
Computer Software Company20%
Energy/Utilities Company10%
Consumer Goods Company10%
VISITORS READING REVIEWS
Computer Software Company28%
Comms Service Provider15%
Financial Services Firm8%
Media Company6%
Company Size
No Data Available
REVIEWERS
Small Business13%
Midsize Enterprise21%
Large Enterprise67%
VISITORS READING REVIEWS
Small Business24%
Midsize Enterprise19%
Large Enterprise57%
Find out what your peers are saying about Apache Spark Streaming vs. Databricks and other solutions. Updated: September 2021.
535,919 professionals have used our research since 2012.

Apache Spark Streaming is ranked 9th in Streaming Analytics with 2 reviews while Databricks is ranked 1st in Streaming Analytics with 24 reviews. Apache Spark Streaming is rated 7.6, while Databricks is rated 8.0. The top reviewer of Apache Spark Streaming writes "Mature and stable with good scalability". On the other hand, the top reviewer of Databricks writes "Has a good feature set but it needs samples and templates to help invite users to see results". Apache Spark Streaming is most compared with Amazon Kinesis, Azure Stream Analytics, Spring Cloud Data Flow, Talend Data Streams and IBM Streams, whereas Databricks is most compared with Microsoft Azure Machine Learning Studio, Amazon SageMaker, Azure Stream Analytics, Alteryx and Dataiku Data Science Studio. See our Apache Spark Streaming vs. Databricks report.

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We monitor all Streaming Analytics reviews to prevent fraudulent reviews and keep review quality high. We do not post reviews by company employees or direct competitors. We validate each review for authenticity via cross-reference with LinkedIn, and personal follow-up with the reviewer when necessary.