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Using
Elastic Search
as a complementary datastore
The
Problems
to SQL or to NoSQL ?
Relational is good for:
Storing complex structures
Document-based is good for:
Storing tons of similar object
Scaling
to Store or to Compute ?
Storing is good for:
data safety
speed (cache only : redis...)
Computing is good for:
save disk space
speed (complex relations)
What do we
need then ?
A little bit of both !
Introducing ElasticSearch
A datastore
An index with a powerful set of API
A REST service
A very scalable product
Used by the best companies out there (StackOverflow, Facebook, Goldman Sachs, NASA...)
What is Elasticsearch ?
Features
Aggregated search
Concept of relevance
Partial/fuzzy matching
Still a lot more to learn !!!
As a complementary datastore
As a search engine
As a suggestion engine
How can we use it ?
Schemas speaks better
It's really powerful
Conclusion
We can use it to complement a RDB
Easy to set up
Scales very well
Blazingly fast
Using Elasticsearch as a complementary datastore
By Louis Lafont
Made with Slides.com
Using Elasticsearch as a complementary datastore
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Louis Lafont
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Louis Lafont