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Apache Storm
Apache Storm

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Apache Impala
Apache Impala

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What is 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.

What is Apache Impala?

Impala is a modern, open source, MPP SQL query engine for Apache Hadoop. Impala is shipped by Cloudera, MapR, and Amazon. With Impala, you can query data, whether stored in HDFS or Apache HBase – including SELECT, JOIN, and aggregate functions – in real time.
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Why do developers choose Apache Storm?
Why do developers choose Apache Impala?

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      What tools integrate with Apache Storm?
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        What are some alternatives to Apache Storm and Apache Impala?
        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.
        Kafka
        Kafka is a distributed, partitioned, replicated commit log service. It provides the functionality of a messaging system, but with a unique design.
        Amazon Kinesis
        Amazon Kinesis can collect and process hundreds of gigabytes of data per second from hundreds of thousands of sources, allowing you to easily write applications that process information in real-time, from sources such as web site click-streams, marketing and financial information, manufacturing instrumentation and social media, and operational logs and metering data.
        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.
        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.
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        Decisions about Apache Storm and Apache Impala
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        How developers use Apache Storm and Apache Impala
        Avatar of Pinterest
        Pinterest uses Apache StormApache Storm

        In addition to batch processing, we also wanted to achieve real-time data processing. For example, to improve the success rate of experiments, we needed to figure out experiment group allocations in real-time once the experiment configuration was pushed out to production. We used Storm to tail Kafka and compute aggregated metrics in real-time to provide crucial stats.

        Avatar of Yelp
        Yelp uses Apache StormApache Storm

        Real-time analytics are much better than periodically run batch jobs, so recently we open sourced Pyleus which allows anyone to write Storm topologies using Python.

        Avatar of Blue Kangaroo
        Blue Kangaroo uses Apache StormApache Storm

        Real-time log processing for user profiling

        Avatar of JimmyCode
        JimmyCode uses Apache StormApache Storm

        Batch processing and as recommendation tool.

        Avatar of brenoinojosa
        brenoinojosa uses Apache StormApache Storm

        Tasks in parallel are run by Storm.

        How much does Apache Storm cost?
        How much does Apache Impala cost?
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