This document provides an introduction to NoSQL databases. It discusses that NoSQL is a non-relational approach to data storage that does not rely on fixed schemas and provides better scalability than traditional relational databases. Specific NoSQL examples mentioned include document databases like CouchDB and MongoDB, as well as key-value stores like Redis and Cassandra. The document outlines some of the characteristics and usage of these NoSQL solutions.

1. An introduction to
NoSQL
Radu Potop

2. NoSQL
● umbrella term
●
non-relational data storage
● no fixed table schemas
● a fresh take on the database
technology

3. Relational databases have issues in
handling big volumes of data
Some companies and their
databases:
●
Digg.com - 3 TB for green badges
● Facebook - 50 TB for inbox search
●
eBay - 2 P(eta)B in total

4. Issues
●
horizontal scalability
● server performance
●
rigid schemas
● distribution across servers

5. Characteristics of NoSQL
● no ACID guarantees (Atomicity,
Consistency, Isolation, Durability)
● highly distributed
● scalable
●
better performance - they don't
have to handle relations

6. NoSQL databases examples:
● Google Bigtable (used intensively
by almost everything made by
Google)
●
Amazon Dynamo (used by Amazon
S3)
● Facebook Cassandra
●
Apache HBase
● LinkedIn Voldemort

7. Some types of databases:
●
Document Oriented databases
● JSON format, XML databases
● examples: CouchDB, BaseX
● Key - Value pairs databases
●
values can be more than strings
(set of strings)
●
examples: Redis, Cassandra

8. CouchDB
● created by the Apache
Foundation
●
written in Erlang
● open source
●
document oriented database
● stores data as JSON documents
collection

9. ● queried via REST API
●
JavaScript is the default language
● also supported:
PHP, Ruby, Python and Erlang
● built-in replication features
● used by Ubuntu One

10. JSON document
{
"_id" : "fc5e038d38a570",
"_rev" : "D546012",
"to" : "email@example",
"subject" : "helloWorld",
"body" : "some text"
}

11. Operations with these documents
●
HTTP requests:
● GET (select), POST (create), PUT
(update), DELETE (delete).
●
HTTP AUTH
● Aplications: curl, Futon
●
JavaScript
● any application that knows HTTP
requests

12. Futon interface

13. Redis
●
key - value database
● written in C
●
open source
● networked
● in-memory
●
persistent database
● similar to memcached
●
data is non-volatile

14. ● atomic operations
●
very high performance
~100.000 operations/second
by 50 parallel clients
● all data is kept in memory -
blazing fast
●
periodic synchronization to hard-
drive
●
powerful replication

15. ●
bindings for a lot of languages:
PHP, Ruby, Python, C, Java, etc.
SET foo bar
GET foo => bar
SET - insert
GET - select

16. Key - value based databases
became very popular lately
Other key-value databases:
● Facebook's Cassandra (now also
used by Digg)
● GM.T
●
MemcacheDB (a persistence
enabled variant of memcached)
●
LinkedIn Voldemort

17. Conclusion
● relational databases are not the
holy grail of data storage
●
scalability issues determined
large corporations to look to other
solutions
● don't believe the FUD and give
them a try

18. Thank you