"Imageflow is a visual tool that helps make it easier for business people to understand complex workflows."
"The built-in optimization recommendations halved the speed of queries and allowed us to reach decision points and deliver insights very quickly."
"It's great technology."
"I like the ability to use workspaces with other colleagues because you can work together even without seeing the other team's job."
"It can send out large data amounts."
"Ability to work collaboratively without having to worry about the infrastructure."
"Databricks is a scalable solution. It is the largest advantage of the solution."
"Databricks gives you the flexibility of using several programming languages independently or in combination to build models."
"The most valuable feature is real-time streaming."
"There are a lot of options in Spring Cloud. It's flexible in terms of how we can use it. It's a full infrastructure."
"There are no direct connectors — they are very limited."
"The integration of data could be a bit better."
"Would be helpful to have additional licensing options."
"Implementation of Databricks is still very code heavy."
"There should be better integration with other platforms."
"Instead of relying on a massive instance, the solution should offer micro partition levels. They're working on it, however, they need to implement it to help the solution run more effectively."
"Pricing is one of the things that could be improved."
"The solution could improve by providing better automation capabilities. For example, working together with more of a DevOps approach, such as continuous integration."
"The configurations could be better. Some configurations are a little bit time-consuming in terms of trying to understand using the Spring Cloud documentation."
"Some of the features, like the monitoring tools, are not very mature and are still evolving."
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.
Spring Cloud Data Flow is a toolkit for building data integration and real-time data processing pipelines.
Pipelines consist of Spring Boot apps, built using the Spring Cloud Stream or Spring Cloud Task microservice frameworks. This makes Spring Cloud Data Flow suitable for a range of data processing use cases, from import/export to event streaming and predictive analytics. Use Spring Cloud Data Flow to connect your Enterprise to the Internet of Anything—mobile devices, sensors, wearables, automobiles, and more.
Databricks is ranked 1st in Streaming Analytics with 22 reviews while Spring Cloud Data Flow is ranked 7th in Streaming Analytics with 2 reviews. Databricks is rated 7.8, while Spring Cloud Data Flow is rated 8.0. The top reviewer of Databricks writes "Has a good feature set but it needs samples and templates to help invite users to see results". On the other hand, the top reviewer of Spring Cloud Data Flow writes "Good logging mechanisms, a strong infrastructure and pretty scalable". Databricks is most compared with Microsoft Azure Machine Learning Studio, Amazon SageMaker, Azure Stream Analytics, Alteryx and Dataiku Data Science Studio, whereas Spring Cloud Data Flow is most compared with Apache Flink, TIBCO BusinessWorks, Mule Anypoint Platform and Cloudera DataFlow. See our Databricks vs. Spring Cloud Data Flow report.
See our list of best Streaming Analytics vendors.
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.