Get Advice Icon

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

Amazon Kinesis
Amazon Kinesis

308
147
+ 1
0
Apache Spark
Apache Spark

1K
802
+ 1
98
Add tool

Amazon Kinesis vs Apache Spark: What are the differences?

What is Amazon Kinesis? Store and process terabytes of data each hour from hundreds of thousands of sources. 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.

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.

Amazon Kinesis and Apache Spark are primarily classified as "Real-time Data Processing" and "Big Data" tools respectively.

Some of the features offered by Amazon Kinesis are:

  • Real-time Processing- Amazon Kinesis enables you to collect and analyze information in real-time, allowing you to answer questions about the current state of your data, from inventory levels to stock trade frequencies, rather than having to wait for an out-of-date report.
  • Easy to use- You can create a new stream, set the throughput requirements, and start streaming data quickly and easily. Amazon Kinesis automatically provisions and manages the storage required to reliably and durably collect your data stream.
  • High throughput. Elastic.- Amazon Kinesis seamlessly scales to match the data throughput rate and volume of your data, from megabytes to terabytes per hour. Amazon Kinesis will scale up or down based on your needs.

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

  • Run programs up to 100x faster than Hadoop MapReduce in memory, or 10x faster on disk
  • Write applications quickly in Java, Scala or Python
  • Combine SQL, streaming, and complex analytics

Apache Spark is an open source tool with 22.5K GitHub stars and 19.4K GitHub forks. Here's a link to Apache Spark's open source repository on GitHub.

According to the StackShare community, Apache Spark has a broader approval, being mentioned in 266 company stacks & 112 developers stacks; compared to Amazon Kinesis, which is listed in 132 company stacks and 25 developer stacks.

- No public GitHub repository available -

What is 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.

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.
Get Advice Icon

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

Why do developers choose Amazon Kinesis?
Why do developers choose Apache Spark?
    Be the first to leave a pro

    Sign up to add, upvote and see more prosMake informed product decisions

      Be the first to leave a con
      What companies use Amazon Kinesis?
      What companies use Apache Spark?

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

      What tools integrate with Amazon Kinesis?
      What tools integrate with Apache Spark?

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

      What are some alternatives to Amazon Kinesis and Apache Spark?
      Kafka
      Kafka is a distributed, partitioned, replicated commit log service. It provides the functionality of a messaging system, but with a unique design.
      Amazon SQS
      Transmit any volume of data, at any level of throughput, without losing messages or requiring other services to be always available. With SQS, you can offload the administrative burden of operating and scaling a highly available messaging cluster, while paying a low price for only what you use.
      Firehose.io
      Firehose is both a Rack application and JavaScript library that makes building real-time web applications possible.
      Amazon Kinesis Firehose
      Amazon Kinesis Firehose is the easiest way to load streaming data into AWS. It can capture and automatically load streaming data into Amazon S3 and Amazon Redshift, enabling near real-time analytics with existing business intelligence tools and dashboards you’re already using today.
      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.
      See all alternatives
      Decisions about Amazon Kinesis and Apache Spark
      No stack decisions found
      Interest over time
      Reviews of Amazon Kinesis and Apache Spark
      No reviews found
      How developers use Amazon Kinesis and Apache Spark
      Avatar of Wei Chen
      Wei Chen uses Apache SparkApache Spark

      Spark is good at parallel data processing management. We wrote a neat program to handle the TBs data we get everyday.

      Avatar of Ralic Lo
      Ralic Lo uses Apache SparkApache Spark

      Used Spark Dataframe API on Spark-R for big data analysis.

      Avatar of Kalibrr
      Kalibrr uses Apache SparkApache Spark

      We use Apache Spark in computing our recommendations.

      Avatar of BrainFinance
      BrainFinance uses Apache SparkApache Spark

      As a part of big data machine learning stack (SMACK).

      Avatar of Dotmetrics
      Dotmetrics uses Apache SparkApache Spark

      Big data analytics and nightly transformation jobs.

      Avatar of Luca Bianchi
      Luca Bianchi uses Amazon KinesisAmazon Kinesis

      Fast data stream maanagement hiding complexity

      Avatar of KASA FIK s.r.o.
      KASA FIK s.r.o. uses Amazon KinesisAmazon Kinesis

      Event streaming

      How much does Amazon Kinesis cost?
      How much does Apache Spark cost?
      Pricing unavailable
      News about Apache Spark
      More news