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What are real time
applications?
• real-time data feeds, video and audio streams,
Machine-to-Machine-to-Browser communications, and
more
Why Nodejs?
• non-blocking, event-driven I/O to remain lightweight
and efficient in the face of data-intensive real-time
applications that run across distributed devices.
• fast, scalable network applications, as it is capable of
handling a huge number of simultaneous connections
with high throughput
Mongo vs
Elasticsearch
• heavy computation could choke up Node’s single
thread and cause problems for all clients
• let elastic search do the computation and analytics.
Why elasticsearch
• distributed full-text search function with schema-free
JSON documents - fuzzy logic
• If you need more than 5 indexes on MongoDB,
consider using ElasticSearch because this search
engine will give you faster results. For MongoDB, it is
difficult and time-consuming to deal with large
indexes.
Analyse documents -
Kibana
• Flexible analytics and visualization platform
• Real-time summary and charting of streaming data
• Instant sharing and embedding of dashboards
Growing acceptance
of elastic search
• Scalability - shard reallocation on adding new nodes
leading to better performance
• Easy to horizontally scale with almost 0 downtime
• Elastic now provides open source monitoring tools for
measuring cluster health.

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Horizontal Scalable Real Time Web Applications

  • 1. What are real time applications? • real-time data feeds, video and audio streams, Machine-to-Machine-to-Browser communications, and more
  • 2. Why Nodejs? • non-blocking, event-driven I/O to remain lightweight and efficient in the face of data-intensive real-time applications that run across distributed devices. • fast, scalable network applications, as it is capable of handling a huge number of simultaneous connections with high throughput
  • 3. Mongo vs Elasticsearch • heavy computation could choke up Node’s single thread and cause problems for all clients • let elastic search do the computation and analytics.
  • 4. Why elasticsearch • distributed full-text search function with schema-free JSON documents - fuzzy logic • If you need more than 5 indexes on MongoDB, consider using ElasticSearch because this search engine will give you faster results. For MongoDB, it is difficult and time-consuming to deal with large indexes.
  • 5. Analyse documents - Kibana • Flexible analytics and visualization platform • Real-time summary and charting of streaming data • Instant sharing and embedding of dashboards
  • 6. Growing acceptance of elastic search • Scalability - shard reallocation on adding new nodes leading to better performance • Easy to horizontally scale with almost 0 downtime • Elastic now provides open source monitoring tools for measuring cluster health.