Apache Spark is an open-source, distributed cluster-computing framework designed for large-scale data processing, batch transformations, real-time Streaming Analytics, and machine learning workloads. The platform executes distributed memory-centric computations across heterogeneous storage layers using unified APIs in Python, Scala, Java, SQL, and R.
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Spotfire Streaming
Score5 out of 10
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The Spotfire Streaming (formerly TIBCO Streaming or StreamBase) platform is a high-performance system for rapidly building applications that analyze and act on real-time streaming data. Using Spotfire Streaming, users can rapidly build real-time systems and deploy them at a fraction of the cost and risk of other alternatives.
Big Data Analytics - Data Engineer in Information Technology at Telkomsel (Telecommunications, 1001-5000 employees)
Chose Spotfire Streaming
Great visual programming is very useful and easy to learn. There's no need for learning a specific programming language just need to know business needs and the logic required. We are already able to provide a solution in a timely manner.
A de minimis incentive was given to thank the reviewer for their time. The incentive was not used to bias or drive a particular response, nor was the incentive contingent on a positive endorsement. More Info
Well suited: To most of the local run of datasets and non-prod systems - scalability is not a problem at all. Including data from multiple types of data sources is an added advantage. MLlib is a decently nice built-in library that can be used for most of the ML tasks. Less appropriate: We had to work on a RecSys where the music dataset that we used was around 300+Gb in size. We faced memory-based issues. Few times we also got memory errors. Also the MLlib library does not have support for advanced analytics and deep-learning frameworks support. Understanding the internals of the working of Apache Spark for beginners is highly not possible.
A de minimis incentive was given to thank the reviewer for their time. The incentive was not used to bias or drive a particular response, nor was the incentive contingent on a positive endorsement. More Info
Taking data from various sources including files, databases, web services, applying some complex rules, transforming, aggregating and producing a result. This is what Spotfire Streaming does best. - If one needs connectivity to special services as secured databases or web services, building interactive web apps, those are probably tasks that shall be addressed with different tools.
A de minimis incentive was given to thank the reviewer for their time. The incentive was not used to bias or drive a particular response, nor was the incentive contingent on a positive endorsement. More Info
A de minimis incentive was given to thank the reviewer for their time. The incentive was not used to bias or drive a particular response, nor was the incentive contingent on a positive endorsement. More Info
A de minimis incentive was given to thank the reviewer for their time. The incentive was not used to bias or drive a particular response, nor was the incentive contingent on a positive endorsement. More Info
A de minimis incentive was given to thank the reviewer for their time. The incentive was not used to bias or drive a particular response, nor was the incentive contingent on a positive endorsement. More Info
If the team looking to use Apache Spark is not used to debug and tweak settings for jobs to ensure maximum optimizations, it can be frustrating. However, the documentation and the support of the community on the internet can help resolve most issues. Moreover, it is highly configurable and it integrates with different tools (eg: it can be used by dbt core), which increase the scenarios where it can be used
A de minimis incentive was given to thank the reviewer for their time. The incentive was not used to bias or drive a particular response, nor was the incentive contingent on a positive endorsement. More Info
The usability is good in terms that it gets well integrated with the Spotfire suite but the only few issues I have is the tough UI/UX (learning curve, if the project is huge) and unable to find many users and devs to help with the queries. At the end it is solely based on the documentation provided which is never enough
A de minimis incentive was given to thank the reviewer for their time. The incentive was not used to bias or drive a particular response, nor was the incentive contingent on a positive endorsement. More Info
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.
A de minimis incentive was given to thank the reviewer for their time. The incentive was not used to bias or drive a particular response, nor was the incentive contingent on a positive endorsement. More Info
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.
A de minimis incentive was given to thank the reviewer for their time. The incentive was not used to bias or drive a particular response, nor was the incentive contingent on a positive endorsement. More Info
We are using Dataflow (by Google).The development time in Spotfire Streaming is definitely shorter because its GUI based. Dataflow handles late arrivals after the window closes, not sure Spotfire Streaming can do that. Dataflow can run GCP as a managed service which is why we chose that tool for our new product.
A de minimis incentive was given to thank the reviewer for their time. The incentive was not used to bias or drive a particular response, nor was the incentive contingent on a positive endorsement. More Info
A de minimis incentive was given to thank the reviewer for their time. The incentive was not used to bias or drive a particular response, nor was the incentive contingent on a positive endorsement. More Info
While we haven't specifically integrated Spotfire Streaming into our product development, it has allowed us to see the benefits of real-time streaming data.
We have much more visibility into how our longer term roadmap will look and what we should focus on.
A de minimis incentive was given to thank the reviewer for their time. The incentive was not used to bias or drive a particular response, nor was the incentive contingent on a positive endorsement. More Info
