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Presentation - Business - Data [2:54]
- (JSP EJB Oracle)
- (React.js Node.js Cassandra)
Strengths [12:43]
- Rich front-end framework (scale, UX)
- Hip, scalable middle tier
- Basically infinitely scalable data tier
Weaknesses [14:57]
Overall Rating [15:32]
- Scalability 4
- Hipness 2
- Difficulty 3
- Flexibility 5
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When Sharding Attacks [19:53]
Strengths [23:38]
- Client isolation is easy(data and deployment)
- Known, simple technologies
Weaknesses [24:56]
- Complexity
- No comprehensive view of data (ETL)
- Oversized shards
Overall Rating [28:00]
- Scalability 3
- Hipness 1
- Difficulty 4
- Flexibility 3
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http://softwareengineeringdaily.com/2016/08/19/apache-beam-with-frances-perry
Messaging [34:42]
Kafka [35:09]
Strengths [38:20]
- Optimizes subsystems based on operational requirements
- Good at unbounded data
Weaknesses [39:09]
- Complex to operate and maintain
- No, seriously
Overall Rating
- Scalability 5
- Hipness 1
- Difficulty 5
- Flexibility 2
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Streaming [40:04]
- Integration is a first-class concern
- Life is dynamic; databases are static
- Tables are streams and streams are tables
- Keep your services close, your computation closer
Integration [41:55]
Database Abstraction [45:25]
Storing Data in Messages [46:26]
- Retention policy? Don’t be so hasty
- Whole-hearted I/O performance
- O(1) writes
- Partitioning, replication
- Elastic scale
First-class events [47:07]
Streams API for kafka [48:05]
- Core Kafka since 0.10 (May, 2016)
- Filters, aggregations, joins
- Doesn’t require a separate cluster!
- Keep stream computation near your code
Overall Rating
- Scalability 5
- Hipness 5
- Difficulty 4
- Flexibility 5
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