Apache Flume vs Apache Spark

Apache Flume
Apache Flume

29
44
+ 1
0
Apache Spark
Apache Spark

1.6K
1.7K
+ 1
112
Add tool

Apache Flume vs Apache Spark: What are the differences?

What is Apache Flume? A service for collecting, aggregating, and moving large amounts of log data. It is a distributed, reliable, and available service for efficiently collecting, aggregating, and moving large amounts of log data. It has a simple and flexible architecture based on streaming data flows. It is robust and fault tolerant with tunable reliability mechanisms and many failover and recovery mechanisms. It uses a simple extensible data model that allows for online analytic application.

What is Apache Spark? Fast and general engine for large-scale data processing. Spark is a fast and general processing engine compatible with Hadoop data. It can run in Hadoop clusters through YARN or Spark's standalone mode, and it can process data in HDFS, HBase, Cassandra, Hive, and any Hadoop InputFormat. It is designed to perform both batch processing (similar to MapReduce) and new workloads like streaming, interactive queries, and machine learning.

Apache Flume belongs to "Log Management" category of the tech stack, while Apache Spark can be primarily classified under "Big Data Tools".

Apache Spark is an open source tool with 22.9K GitHub stars and 19.7K GitHub forks. Here's a link to Apache Spark's open source repository on GitHub.

Pros of Apache Flume
Pros of Apache Spark
    Be the first to leave a pro

    Sign up to add or upvote prosMake informed product decisions

    Cons of Apache Flume
    Cons of Apache Spark
      Be the first to leave a con

      Sign up to add or upvote consMake informed product decisions

      No Stats
      - No public GitHub repository available -

      What is Apache Flume?

      It is a distributed, reliable, and available service for efficiently collecting, aggregating, and moving large amounts of log data. It has a simple and flexible architecture based on streaming data flows. It is robust and fault tolerant with tunable reliability mechanisms and many failover and recovery mechanisms. It uses a simple extensible data model that allows for online analytic application.

      What is Apache Spark?

      Spark is a fast and general processing engine compatible with Hadoop data. It can run in Hadoop clusters through YARN or Spark's standalone mode, and it can process data in HDFS, HBase, Cassandra, Hive, and any Hadoop InputFormat. It is designed to perform both batch processing (similar to MapReduce) and new workloads like streaming, interactive queries, and machine learning.
      What companies use Apache Flume?
      What companies use Apache Spark?

      Sign up to get full access to all the companiesMake informed product decisions

      What tools integrate with Apache Flume?
      What tools integrate with Apache Spark?
        No integrations found

        Sign up to get full access to all the tool integrationsMake informed product decisions

        What are some alternatives to Apache Flume and Apache Spark?
        Logstash
        Logstash is a tool for managing events and logs. You can use it to collect logs, parse them, and store them for later use (like, for searching). If you store them in Elasticsearch, you can view and analyze them with Kibana.
        Apache Storm
        Apache Storm is a free and open source distributed realtime computation system. Storm makes it easy to reliably process unbounded streams of data, doing for realtime processing what Hadoop did for batch processing. Storm has many use cases: realtime analytics, online machine learning, continuous computation, distributed RPC, ETL, and more. Storm is fast: a benchmark clocked it at over a million tuples processed per second per node. It is scalable, fault-tolerant, guarantees your data will be processed, and is easy to set up and operate.
        Kafka
        Kafka is a distributed, partitioned, replicated commit log service. It provides the functionality of a messaging system, but with a unique design.
        Apache Flink
        Apache Flink is an open source system for fast and versatile data analytics in clusters. Flink supports batch and streaming analytics, in one system. Analytical programs can be written in concise and elegant APIs in Java and Scala.
        Apache NiFi
        An easy to use, powerful, and reliable system to process and distribute data. It supports powerful and scalable directed graphs of data routing, transformation, and system mediation logic.
        See all alternatives
        Interest over time