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Amazon Redshift Spectrum vs Splunk: What are the differences?
Developers describe Amazon Redshift Spectrum as "Exabyte-Scale In-Place Queries of S3 Data". 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. On the other hand, Splunk is detailed as "Search, monitor, analyze and visualize machine data". It provides the leading platform for Operational Intelligence. Customers use it to search, monitor, analyze and visualize machine data.
Amazon Redshift Spectrum and Splunk belong to "Big Data Tools" category of the tech stack.
Nubank, Yelp, and Intuit are some of the popular companies that use Splunk, whereas Amazon Redshift Spectrum is used by Yelp, VSCO, and Onefootball. Splunk has a broader approval, being mentioned in 67 company stacks & 170 developers stacks; compared to Amazon Redshift Spectrum, which is listed in 11 company stacks and 45 developer stacks.
Pros of Amazon Redshift Spectrum
- Good Performance1
- Great Documentation1
- Economical1
Pros of Splunk
- API for searching logs, running reports3
- Alert system based on custom query results3
- Dashboarding on any log contents2
- Custom log parsing as well as automatic parsing2
- Ability to style search results into reports2
- Query engine supports joining, aggregation, stats, etc2
- Splunk language supports string, date manip, math, etc2
- Rich GUI for searching live logs2
- Query any log as key-value pairs1
- Granular scheduling and time window support1
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Cons of Amazon Redshift Spectrum
Cons of Splunk
- Splunk query language rich so lots to learn1
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What is Amazon Redshift Spectrum?
What is Splunk?
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What companies use Splunk?
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What tools integrate with Amazon Redshift Spectrum?
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