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Learn MorePros of Amazon Athena
Pros of Apache Kylin
Pros of Apache Spark
Pros of Amazon Athena
- Use SQL to analyze CSV files16
- Glue crawlers gives easy Data catalogue8
- Cheap7
- Query all my data without running servers 24x76
- No data base servers yay4
- Easy integration with QuickSight3
- Query and analyse CSV,parquet,json files in sql2
- Also glue and athena use same data catalog2
- No configuration required1
- Ad hoc checks on data made easy0
Pros of Apache Kylin
- Star schema and snowflake schema support7
- Seamless BI integration5
- OLAP on Hadoop4
- Easy install3
- Sub-second latency on extreme large dataset3
- ANSI-SQL2
Pros of Apache Spark
- Open-source61
- Fast and Flexible48
- One platform for every big data problem8
- Great for distributed SQL like applications8
- Easy to install and to use6
- Works well for most Datascience usecases3
- Interactive Query2
- Machine learning libratimery, Streaming in real2
- In memory Computation2
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Cons of Amazon Athena
Cons of Apache Kylin
Cons of Apache Spark
Cons of Amazon Athena
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Cons of Apache Kylin
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Cons of Apache Spark
- Speed4
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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 Kylin?
Apache Kylin™ is an open source Distributed Analytics Engine designed to provide SQL interface and multi-dimensional analysis (OLAP) on Hadoop/Spark supporting extremely large datasets, originally contributed from eBay Inc.
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 Amazon Athena?
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What tools integrate with Amazon Athena?
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What are some alternatives to Amazon Athena, Apache Kylin, 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.