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

Amazon Athena

387
615
+ 1
46
Cassandra

3.2K
3.1K
+ 1
492
Add tool

Amazon Athena vs Cassandra: What are the differences?

What is Amazon Athena? Query S3 Using SQL. 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 Cassandra? A partitioned row store. Rows are organized into tables with a required primary key. 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.

Amazon Athena can be classified as a tool in the "Big Data Tools" category, while Cassandra is grouped under "Databases".

"Use SQL to analyze CSV files" is the top reason why over 9 developers like Amazon Athena, while over 96 developers mention "Distributed" as the leading cause for choosing Cassandra.

Cassandra is an open source tool with 5.23K GitHub stars and 2.33K GitHub forks. Here's a link to Cassandra's open source repository on GitHub.

According to the StackShare community, Cassandra has a broader approval, being mentioned in 337 company stacks & 231 developers stacks; compared to Amazon Athena, which is listed in 47 company stacks and 17 developer stacks.

Advice on Amazon Athena and Cassandra

Hi all,

Currently, we need to ingest the data from Amazon S3 to DB either Amazon Athena or Amazon Redshift. But the problem with the data is, it is in .PSV (pipe separated values) format and the size is also above 200 GB. The query performance of the timeout in Athena/Redshift is not up to the mark, too slow while compared to Google BigQuery. How would I optimize the performance and query result time? Can anyone please help me out?

See more
Replies (4)

you can use aws glue service to convert you pipe format data to parquet format , and thus you can achieve data compression . Now you should choose Redshift to copy your data as it is very huge. To manage your data, you should partition your data in S3 bucket and also divide your data across the redshift cluster

See more
Carlos Acedo
Data Technologies Manager at SDG Group Iberia · | 4 upvotes · 87.8K views
Recommends
Amazon RedshiftAmazon Redshift

First of all you should make your choice upon Redshift or Athena based on your use case since they are two very diferent services - Redshift is an enterprise-grade MPP Data Warehouse while Athena is a SQL layer on top of S3 with limited performance. If performance is a key factor, users are going to execute unpredictable queries and direct and managing costs are not a problem I'd definitely go for Redshift. If performance is not so critical and queries will be predictable somewhat I'd go for Athena.

Once you select the technology you'll need to optimize your data in order to get the queries executed as fast as possible. In both cases you may need to adapt the data model to fit your queries better. In the case you go for Athena you'd also proabably need to change your file format to Parquet or Avro and review your partition strategy depending on your most frequent type of query. If you choose Redshift you'll need to ingest the data from your files into it and maybe carry out some tuning tasks for performance gain.

I'll recommend Redshift for now since it can address a wider range of use cases, but we could give you better advice if you described your use case in depth.

See more
Alexis Blandin
Recommends
Amazon AthenaAmazon Athena

It depend of the nature of your data (structured or not?) and of course your queries (ad-hoc or predictible?). For example you can look at partitioning and columnar format to maximize MPP capabilities for both Athena and Redshift

See more
Recommends

you can change your PSV fomat data to parquet file format with AWS GLUE and then your query performance will be improved

See more
Vinay Mehta
Needs advice
on
ScyllaScylla
and
CassandraCassandra

The problem I have is - we need to process & change(update/insert) 55M Data every 2 min and this updated data to be available for Rest API for Filtering / Selection. Response time for Rest API should be less than 1 sec.

The most important factors for me are processing and storing time of 2 min. There need to be 2 views of Data One is for Selection & 2. Changed data.

See more
Replies (4)
Pankaj Soni
Chief Technical Officer at Software Joint · | 2 upvotes · 57.4K views
Recommends
CassandraCassandra

i love syclla for pet projects however it's license which is based on server model is an issue. thus i recommend cassandra

See more
Recommends
ScyllaScylla

Scylla can handle 1M/s events with a simple data model quite easily. The api to query is CQL, we have REST api but that's for control/monitoring

See more
Alex Peake
Recommends
CassandraCassandra

Cassandra is quite capable of the task, in a highly available way, given appropriate scaling of the system. Remember that updates are only inserts, and that efficient retrieval is only by key (which can be a complex key). Talking of keys, make sure that the keys are well distributed.

See more
Recommends
ScyllaScylla

By 55M do you mean 55 million entity changes per 2 minutes? It is relatively high, means almost 460k per second. If I had to choose between Scylla or Cassandra, I would opt for Scylla as it is promising better performance for simple operations. However, maybe it would be worth to consider yet another alternative technology. Take into consideration required consistency, reliability and high availability and you may realize that there are more suitable once. Rest API should not be the main driver, because you can always develop the API yourself, if not supported by given technology.

See more
Get Advice from developers at your company using Private StackShare. Sign up for Private StackShare.
Learn More
Pros of Amazon Athena
Pros of Cassandra
  • 15
    Use SQL to analyze CSV files
  • 8
    Glue crawlers gives easy Data catalogue
  • 6
    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
  • 114
    Distributed
  • 95
    High performance
  • 80
    High availability
  • 74
    Easy scalability
  • 52
    Replication
  • 26
    Multi datacenter deployments
  • 26
    Reliable
  • 8
    OLTP
  • 7
    Open source
  • 7
    Schema optional
  • 2
    Workload separation (via MDC)
  • 1
    Fast

Sign up to add or upvote prosMake informed product decisions

Cons of Amazon Athena
Cons of Cassandra
    Be the first to leave a con
    • 2
      Reliability of replication
    • 1
      Updates

    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 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.

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

    What companies use Amazon Athena?
    What companies use Cassandra?
    See which teams inside your own company are using Amazon Athena or Cassandra.
    Sign up for Private StackShareLearn More

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

    What tools integrate with Amazon Athena?
    What tools integrate with Cassandra?

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

    Blog Posts

    Aug 28 2019 at 3:10AM

    Segment

    PythonJavaAmazon S3+16
    5
    2149
    Jul 2 2019 at 9:34PM

    Segment

    Google AnalyticsAmazon S3New Relic+25
    10
    5899
    GitHubPythonReact+42
    47
    39408
    GitHubPythonNode.js+26
    28
    15316
    What are some alternatives to Amazon Athena and Cassandra?
    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.
    Spectrum
    The community platform for the future.
    Amazon Quicksight
    Amazon QuickSight is a fast, cloud-powered business analytics service that makes it easy to build visualizations, perform ad-hoc analysis, and quickly get business insights from your data.
    See all alternatives