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TIBCO Spotfire VS Spark Streaming

Compare TIBCO Spotfire VS Spark Streaming and see what are their differences

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TIBCO Spotfire logo TIBCO Spotfire

TIBCO Spotfire is a Business Intelligence (BI) solution that provides users with executive dashboards, data visualization, data analytics and KPIs push to mobile devices.

Spark Streaming logo Spark Streaming

Spark Streaming makes it easy to build scalable and fault-tolerant streaming applications.
  • TIBCO Spotfire Landing page
    Landing page //
    2022-12-12
  • Spark Streaming Landing page
    Landing page //
    2022-01-10

TIBCO Spotfire videos

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Inside TIBCO Spotfire

More videos:

  • Review - TIBCO Spotfire® Overview

Spark Streaming videos

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Spark Streaming Vs Kafka Streams || Which is The Best for Stream Processing?

More videos:

  • Tutorial - Spark Streaming Vs Structured Streaming Comparison | Big Data Hadoop Tutorial

Category Popularity

0-100% (relative to TIBCO Spotfire and Spark Streaming)

TIBCO Spotfire

Spark Streaming

Data Dashboard
100 100%
Data Dashboard
0% 0
Stream Processing
0 0%
Stream Processing
100% 100
Business Intelligence
100 100%
Business Intelligence
0% 0
Data Management
0 0%
Data Management
100% 100

User comments

Share your experience with using TIBCO Spotfire and Spark Streaming. For example, how are they different and which one is better?
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Social recommendations and mentions

Based on our record, Spark Streaming seems to be more popular. It has been mentiond 3 times since March 2021. We are tracking product recommendations and mentions on various public social media platforms and blogs. They can help you identify which product is more popular and what people think of it.

TIBCO Spotfire mentions (0)

We have not tracked any mentions of TIBCO Spotfire yet. Tracking of TIBCO Spotfire recommendations started around Mar 2021.

Spark Streaming mentions (3)

  • Choosing Between a Streaming Database and a Stream Processing Framework in Python
    Other stream processing engines (such as Flink and Spark Streaming) provide SQL interfaces too, but the key difference is a streaming database has its storage. Stream processing engines require a dedicated database to store input and output data. On the other hand, streaming databases utilize cloud-native storage to maintain materialized views and states, allowing data replication and independent storage scaling. - Source: dev.to / 3 months ago
  • Machine Learning Pipelines with Spark: Introductory Guide (Part 1)
    Spark Streaming: The component for real-time data processing and analytics. - Source: dev.to / over 1 year ago
  • Spark for beginners - and you
    Is a big data framework and currently one of the most popular tools for big data analytics. It contains libraries for data analysis, machine learning, graph analysis and streaming live data. In general Spark is faster than Hadoop, as it does not write intermediate results to disk. It is not a data storage system. We can use Spark on top of HDFS or read data from other sources like Amazon S3. It is the designed... - Source: dev.to / over 2 years ago

What are some alternatives?

When comparing TIBCO Spotfire and Spark Streaming, you can also consider the following products

Looker - Looker makes it easy for analysts to create and curate custom data experiences—so everyone in the business can explore the data that matters to them, in the context that makes it truly meaningful.

Confluent - Confluent offers a real-time data platform built around Apache Kafka.

Qlik - Qlik offers an Active Intelligence platform, delivering end-to-end, real-time data integration and analytics cloud solutions to close the gaps between data, insights, and action.

Amazon Kinesis - Amazon Kinesis services make it easy to work with real-time streaming data in the AWS cloud.

Domo - Domo: business intelligence, data visualization, dashboards and reporting all together. Simplify your big data and improve your business with Domo's agile and mobile-ready platform.

Google Cloud Dataflow - Google Cloud Dataflow is a fully-managed cloud service and programming model for batch and streaming big data processing.

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