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Cloudera Enterprise vs Apache Flink: What are the differences?

What is Cloudera Enterprise? Enterprise Platform for Big Data. Cloudera Enterprise includes CDH, the world’s most popular open source Hadoop-based platform, as well as advanced system management and data management tools plus dedicated support and community advocacy from our world-class team of Hadoop developers and experts.

What is Apache Flink? Fast and reliable large-scale data processing engine. 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.

Cloudera Enterprise can be classified as a tool in the "Big Data as a Service" category, while Apache Flink is grouped under "Big Data Tools".

Some of the features offered by Cloudera Enterprise are:

  • Unified – one integrated system, bringing diverse users and application workloads to one pool of data on common infrastructure
  • no data movement required
  • Secure – perimeter security, authentication, granular authorization, and data protection

On the other hand, Apache Flink provides the following key features:

  • Hybrid batch/streaming runtime that supports batch processing and data streaming programs.
  • Custom memory management to guarantee efficient, adaptive, and highly robust switching between in-memory and data processing out-of-core algorithms.
  • Flexible and expressive windowing semantics for data stream programs

Apache Flink is an open source tool with 9.11K GitHub stars and 4.86K GitHub forks. Here's a link to Apache Flink's open source repository on GitHub.

Zalando, sovrn Holdings, and BetterCloud are some of the popular companies that use Apache Flink, whereas Cloudera Enterprise is used by Hammer Lab, JPush, and Jobrapido. Apache Flink has a broader approval, being mentioned in 20 company stacks & 21 developers stacks; compared to Cloudera Enterprise, which is listed in 4 company stacks and 7 developer stacks.

Advice on Cloudera Enterprise and Apache Flink
Nilesh Akhade
Technical Architect at Self Employed · | 5 upvotes · 255.1K views

We have a Kafka topic having events of type A and type B. We need to perform an inner join on both type of events using some common field (primary-key). The joined events to be inserted in Elasticsearch.

In usual cases, type A and type B events (with same key) observed to be close upto 15 minutes. But in some cases they may be far from each other, lets say 6 hours. Sometimes event of either of the types never come.

In all cases, we should be able to find joined events instantly after they are joined and not-joined events within 15 minutes.

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Replies (2)
Recommends
ElasticsearchElasticsearch

The first solution that came to me is to use upsert to update ElasticSearch:

  1. Use the primary-key as ES document id
  2. Upsert the records to ES as soon as you receive them. As you are using upsert, the 2nd record of the same primary-key will not overwrite the 1st one, but will be merged with it.

Cons: The load on ES will be higher, due to upsert.

To use Flink:

  1. Create a KeyedDataStream by the primary-key
  2. In the ProcessFunction, save the first record in a State. At the same time, create a Timer for 15 minutes in the future
  3. When the 2nd record comes, read the 1st record from the State, merge those two, and send out the result, and clear the State and the Timer if it has not fired
  4. When the Timer fires, read the 1st record from the State and send out as the output record.
  5. Have a 2nd Timer of 6 hours (or more) if you are not using Windowing to clean up the State

Pro: if you have already having Flink ingesting this stream. Otherwise, I would just go with the 1st solution.

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Akshaya Rawat
Senior Specialist Platform at Publicis Sapient · | 3 upvotes · 152.6K views
Recommends
Apache SparkApache Spark

Please refer "Structured Streaming" feature of Spark. Refer "Stream - Stream Join" at https://spark.apache.org/docs/latest/structured-streaming-programming-guide.html#stream-stream-joins . In short you need to specify "Define watermark delays on both inputs" and "Define a constraint on time across the two inputs"

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Pros of Cloudera Enterprise
Pros of Apache Flink
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    • 15
      Unified batch and stream processing
    • 8
      Easy to use streaming apis
    • 8
      Out-of-the box connector to kinesis,s3,hdfs
    • 3
      Open Source
    • 1
      Low latency

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    - No public GitHub repository available -

    What is Cloudera Enterprise?

    Cloudera Enterprise includes CDH, the world’s most popular open source Hadoop-based platform, as well as advanced system management and data management tools plus dedicated support and community advocacy from our world-class team of Hadoop developers and experts.

    What is 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.

    Need advice about which tool to choose?Ask the StackShare community!

    What companies use Cloudera Enterprise?
    What companies use Apache Flink?
    See which teams inside your own company are using Cloudera Enterprise or Apache Flink.
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    What tools integrate with Cloudera Enterprise?
    What tools integrate with Apache Flink?

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    What are some alternatives to Cloudera Enterprise and Apache Flink?
    Amazon Redshift
    It is optimized for data sets ranging from a few hundred gigabytes to a petabyte or more and costs less than $1,000 per terabyte per year, a tenth the cost of most traditional data warehousing solutions.
    Google BigQuery
    Run super-fast, SQL-like queries against terabytes of data in seconds, using the processing power of Google's infrastructure. Load data with ease. Bulk load your data using Google Cloud Storage or stream it in. Easy access. Access BigQuery by using a browser tool, a command-line tool, or by making calls to the BigQuery REST API with client libraries such as Java, PHP or Python.
    Snowflake
    Snowflake eliminates the administration and management demands of traditional data warehouses and big data platforms. Snowflake is a true data warehouse as a service running on Amazon Web Services (AWS)—no infrastructure to manage and no knobs to turn.
    Amazon EMR
    It is used in a variety of applications, including log analysis, data warehousing, machine learning, financial analysis, scientific simulation, and bioinformatics.
    Stitch
    Stitch is a simple, powerful ETL service built for software developers. Stitch evolved out of RJMetrics, a widely used business intelligence platform. When RJMetrics was acquired by Magento in 2016, Stitch was launched as its own company.
    See all alternatives