Amazon Redshift Spectrum vs Stroom
Overview
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Detailed Comparison
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. | It is a data processing, storage and analysis platform. It is scalable - just add more CPUs / servers for greater throughput. It is suitable for processing high volume data such as system logs, to provide valuable insights into IT performance and usage. |
| - | Receive and store large volumes of data such as native format logs. Ingested data is always available in its raw form; Create sequences of XSL and text operations, in order to normalise or export data in any format. It is possible to enrich data using lookups and reference data; Easily add new data formats and debug the transformations if they don't work as expected; Create multiple indexes with different retention periods. These can be sharded across your cluster; Run queries against your indexes or statistics and view the results within custom visualisations; Record counts or values of items over time |
Statistics | |
GitHub Stars - | GitHub Stars 452 |
GitHub Forks - | GitHub Forks 62 |
Stacks 99 | Stacks 1 |
Followers 147 | Followers 3 |
Votes 3 | Votes 0 |
Pros & Cons | |
Pros
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Integrations | |
What are some alternatives to Amazon Redshift Spectrum, Stroom?
Papertrail
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Logmatic
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Loggly
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Apache Spark
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Logentries
Logentries makes machine-generated log data easily accessible to IT operations, development, and business analysis teams of all sizes. With the broadest platform support and an open API, Logentries brings the value of log-level data to any system, to any team member, and to a community of more than 25,000 worldwide users.
Logstash
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Graylog
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Presto
Distributed SQL Query Engine for Big Data
Amazon Athena
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Sematext
Sematext pulls together performance monitoring, logs, user experience and synthetic monitoring that tools organizations need to troubleshoot performance issues faster.
