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Redpanda VS Apache Spark

Compare Redpanda VS Apache Spark and see what are their differences

Redpanda logo Redpanda

Redpanda is a powerful, yet simple, and cost-efficient streaming data platform that is compatible with Kafka® APIs while eliminating Kafka complexity.

Apache Spark logo Apache Spark

Apache Spark is an engine for big data processing, with built-in modules for streaming, SQL, machine learning and graph processing.
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  • Apache Spark Landing page
    Landing page //
    2021-12-31

Redpanda videos

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Apache Spark videos

Weekly Apache Spark live Code Review -- look at StringIndexer multi-col (Scala) & Python testing

More videos:

  • Review - What's New in Apache Spark 3.0.0
  • Review - Apache Spark for Data Engineering and Analysis - Overview

Category Popularity

0-100% (relative to Redpanda and Apache Spark)
Developer Tools
100 100%
0% 0
Databases
0 0%
100% 100
Queueing, Messaging And Background Processing
Big Data
0 0%
100% 100

User comments

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Reviews

These are some of the external sources and on-site user reviews we've used to compare Redpanda and Apache Spark

Redpanda Reviews

Best message queue for cloud-native apps
Redpanda message queue allows multiple producers to write messages to a single topic, and multiple consumers to read messages from that topic in parallel. Messages can be buffered in memory for fast delivery and persist to disk for durability. Redpanda also provides a number of features, such as replication, partitioning, and compression, to help manage large amounts of data.
Source: docs.vanus.ai

Apache Spark Reviews

15 data science tools to consider using in 2021
Apache Spark is an open source data processing and analytics engine that can handle large amounts of data -- upward of several petabytes, according to proponents. Spark's ability to rapidly process data has fueled significant growth in the use of the platform since it was created in 2009, helping to make the Spark project one of the largest open source communities among big...
Top 15 Kafka Alternatives Popular In 2021
Apache Spark is a well-known, general-purpose, open-source analytics engine for large-scale, core data processing. It is known for its high-performance quality for data processing – batch and streaming with the help of its DAG scheduler, query optimizer, and engine. Data streams are processed in real-time and hence it is quite fast and efficient. Its machine learning...
5 Best-Performing Tools that Build Real-Time Data Pipeline
Apache Spark is an open-source and flexible in-memory framework which serves as an alternative to map-reduce for handling batch, real-time analytics and data processing workloads. It provides native bindings for the Java, Scala, Python, and R programming languages, and supports SQL, streaming data, machine learning and graph processing. From its beginning in the AMPLab at...

Social recommendations and mentions

Based on our record, Apache Spark seems to be a lot more popular than Redpanda. While we know about 58 links to Apache Spark, we've tracked only 1 mention of Redpanda. 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.

Redpanda mentions (1)

  • Choosing Between a Streaming Database and a Stream Processing Framework in Python
    Stream-processing platforms such as Apache Kafka, Apache Pulsar, or Redpanda are specifically engineered to foster event-driven communication in a distributed system and they can be a great choice for developing loosely coupled applications. Stream processing platforms analyze data in motion, offering near-zero latency advantages. For example, consider an alert system for monitoring factory equipment. If a... - Source: dev.to / 4 months ago

Apache Spark mentions (58)

  • How I've implemented the Medallion architecture using Apache Spark and Apache Hdoop
    In this project, I'm exploring the Medallion Architecture which is a data design pattern that organizes data into different layers based on structure and/or quality. I'm creating a fictional scenario where a large enterprise that has several branches across the country. Each branch receives purchase orders from an app and deliver the goods to their customers. The enterprise wants to identify the branch that... - Source: dev.to / about 20 hours ago
  • Shades of Open Source - Understanding The Many Meanings of "Open"
    In contrast, Databricks maintains internal forks of Spark, Delta Lake, and Unity Catalog, using the same names for both the open-source versions and the features specific to the Databricks platform. While they do provide separate documentation, online discussions often reflect confusion about how to use features in the open-source versions that only exist on the Databricks platform. This creates a "muddying of the... - Source: dev.to / 3 days ago
  • Groovy 🎷 Cheat Sheet - 01 Say "Hello" from Groovy
    Recently I had to revisit the "JVM languages universe" again. Yes, language(s), plural! Java isn't the only language that uses the JVM. I previously used Scala, which is a JVM language, to use Apache Spark for Data Engineering workloads, but this is for another post 😉. - Source: dev.to / 4 months ago
  • 🦿🛴Smarcity garbage reporting automation w/ ollama
    Consume data into third party software (then let Open Search or Apache Spark or Apache Pinot) for analysis/datascience, GIS systems (so you can put reports on a map) or any ticket management system. - Source: dev.to / 5 months ago
  • Go concurrency simplified. Part 4: Post office as a data pipeline
    Also, this knowledge applies to learning more about data engineering, as this field of software engineering relies heavily on the event-driven approach via tools like Spark, Flink, Kafka, etc. - Source: dev.to / 6 months ago
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What are some alternatives?

When comparing Redpanda and Apache Spark, you can also consider the following products

Apache Pulsar - Apache Pulsar is an open-source, distributed messaging and streaming platform built for the cloud.

Apache Flink - Flink is a streaming dataflow engine that provides data distribution, communication, and fault tolerance for distributed computations.

NATS - NATS.io is an open source messaging system for cloud native applications, IoT messaging, Edge, and microservices architectures.

Apache Airflow - Airflow is a platform to programmaticaly author, schedule and monitor data pipelines.

Apache Kafka - Apache Kafka is an open-source message broker project developed by the Apache Software Foundation written in Scala.

Hadoop - Open-source software for reliable, scalable, distributed computing