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Minio vs Apache Spark: What are the differences?

Developers describe Minio as "AWS S3 open source alternative written in Go". Minio is an object storage server compatible with Amazon S3 and licensed under Apache 2.0 License. On the other hand, Apache Spark is detailed as "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.

Minio can be classified as a tool in the "Cloud Storage" category, while Apache Spark is grouped under "Big Data Tools".

Minio and Apache Spark are both open source tools. Apache Spark with 22.3K GitHub stars and 19.3K forks on GitHub appears to be more popular than Minio with 16.7K GitHub stars and 1.56K GitHub forks.

Uber Technologies, 9GAG, and Hootsuite are some of the popular companies that use Apache Spark, whereas Minio is used by AgFlow, codebeat, and Minio. Apache Spark has a broader approval, being mentioned in 263 company stacks & 111 developers stacks; compared to Minio, which is listed in 19 company stacks and 12 developer stacks.

Advice on Minio and Apache Spark
Nilesh Akhade
Technical Architect at Self Employed · | 5 upvotes · 217.5K 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
Elasticsearch

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 · 120.6K views
Recommends
Apache 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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Decisions about Minio and Apache Spark

Minio is a free and open source object storage system. It can be self-hosted and is S3 compatible. During the early stage it would save cost and allow us to move to a different object storage when we scale up. It is also fast and easy to set up. This is very useful during development since it can be run on localhost.

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Pros of Minio
Pros of Apache Spark
  • 7
    Store and Serve Resumes & Job Description PDF, Backups
  • 5
    S3 Compatible
  • 4
    Simple
  • 4
    Open Source
  • 3
    Encryption and Tamper-Proof
  • 2
    Pluggable Storage Backend
  • 2
    Scalable
  • 2
    Lambda Compute
  • 2
    Private Cloud Storage
  • 2
    Data Protection
  • 2
    Highly Available
  • 1
    Performance
  • 58
    Open-source
  • 48
    Fast and Flexible
  • 7
    One platform for every big data problem
  • 6
    Easy to install and to use
  • 6
    Great for distributed SQL like applications
  • 3
    Works well for most Datascience usecases
  • 2
    Machine learning libratimery, Streaming in real
  • 2
    In memory Computation
  • 0
    Interactive Query

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Cons of Minio
Cons of Apache Spark
  • 1
    Deletion of huge buckets is not possible
  • 3
    Speed

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What is Minio?

Minio is an object storage server compatible with Amazon S3 and licensed under Apache 2.0 License

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.

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What companies use Minio?
What companies use Apache Spark?
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What tools integrate with Apache Spark?

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What are some alternatives to Minio and Apache Spark?
ceph
In computing,It is a free-software storage platform, implements object storage on a single distributed computer cluster, and provides interfaces for object-, block- and file-level storage.
FreeNAS
It is the simplest way to create a centralized and easily accessible place for your data. Use it with ZFS to protect, store, backup, all of your data. It is used everywhere, for the home, small business, and the enterprise.
Swift
Writing code is interactive and fun, the syntax is concise yet expressive, and apps run lightning-fast. Swift is ready for your next iOS and OS X project — or for addition into your current app — because Swift code works side-by-side with Objective-C.
Rook
It is an open source cloud-native storage orchestrator for Kubernetes, providing the platform, framework, and support for a diverse set of storage solutions to natively integrate with cloud-native environments.
Amazon S3
Amazon Simple Storage Service provides a fully redundant data storage infrastructure for storing and retrieving any amount of data, at any time, from anywhere on the web
See all alternatives