Amazon Athena vs Apache Flink vs Apache Spark

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

Amazon Athena

385
635
+ 1
47
Apache Flink

417
660
+ 1
35
Apache Spark

2.5K
2.9K
+ 1
132
Get Advice from developers at your company using Private StackShare. Sign up for Private StackShare.
Learn More
Pros of Amazon Athena
Pros of Apache Flink
Pros of Apache Spark
  • 15
    Use SQL to analyze CSV files
  • 8
    Glue crawlers gives easy Data catalogue
  • 7
    Cheap
  • 5
    Query all my data without running servers 24x7
  • 4
    No data base servers yay
  • 3
    Easy integration with QuickSight
  • 2
    Query and analyse CSV,parquet,json files in sql
  • 2
    Also glue and athena use same data catalog
  • 1
    No configuration required
  • 0
    Ad hoc checks on data made easy
  • 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
  • 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

Sign up to add or upvote prosMake informed product decisions

Cons of Amazon Athena
Cons of Apache Flink
Cons of Apache Spark
    Be the first to leave a con
      Be the first to leave a con
      • 3
        Speed

      Sign up to add or upvote consMake informed product decisions

      - No public GitHub repository available -

      What is Amazon Athena?

      Amazon Athena is an interactive query service that makes it easy to analyze data in Amazon S3 using standard SQL. Athena is serverless, so there is no infrastructure to manage, and you pay only for the queries that you run.

      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.

      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.

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

      What companies use Amazon Athena?
      What companies use Apache Flink?
      What companies use Apache Spark?

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

      What tools integrate with Amazon Athena?
      What tools integrate with Apache Flink?
      What tools integrate with Apache Spark?

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

      Blog Posts

      What are some alternatives to Amazon Athena, Apache Flink, and Apache Spark?
      Presto
      Distributed SQL Query Engine for Big Data
      Amazon Redshift Spectrum
      With Redshift Spectrum, you can extend the analytic power of Amazon Redshift beyond data stored on local disks in your data warehouse to query vast amounts of unstructured data in your Amazon S3 “data lake” -- without having to load or transform any data.
      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.
      Cassandra
      Partitioning means that Cassandra can distribute your data across multiple machines in an application-transparent matter. Cassandra will automatically repartition as machines are added and removed from the cluster. Row store means that like relational databases, Cassandra organizes data by rows and columns. The Cassandra Query Language (CQL) is a close relative of SQL.
      Spectrum
      The community platform for the future.
      See all alternatives