The fundamentals
of NoSQL databases
(2 days)

Discover the world of NoSQL: challenges & solutions

Nb. days
Min. participants
Max. participants
Toulouse, Paris, etc.
1900€ HT
The fundamentals <br/> of NoSQL databases <br/> (2 days)
With the emergence of Big Data and real-time web applications, the power and agility of NoSQL databases have made them a standard for managing vast amounts of data.
These databases do not follow the relational model, allow data to be stored without necessarily having defined a schema (schema-less), and are based on a distributed architecture that allows auto-scaling and fail-over.
There are different types of NoSQL databases and it is important to understand their particularities to choose the right database for each use case.
At the end of this training, you will know the different families of NoSQL databases, their architectures, their technical characteristics and the main solutions on the market. You will be able to evaluate the advantages and disadvantages of each data model.


  • Understanding the differences between SQL DBMS and NoSQL DBMS
  • Evaluate the inherent advantages and disadvantages of NoSQL technologies
  • Analyze the main solutions of the NoSQL world for each data model
  • Identify the fields of application of NoSQL DBMS in operational and analytical applications
  • Understanding the different architectures
Alexia Audevart
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Teaching method

  • Seminar with many demonstrations.
  • A daily evaluation of the acquisition of the knowledge of the day before is carried out.
  • A synthesis is proposed at the end of the training.
  • An evaluation will be proposed to the trainee at the end of the course.
  • A course support will be given to each participant including slides on the theory and exercises.
  • A sign-in sheet for each half-day of attendance is provided at the end of the course as well as a certificate of completion if the trainee has attended the entire session.
  • A follow-up and an exchange with the participants will take place a few days after the training.


  • General knowledge of information systems and databases is desirable.


  • Technical Project Manager
  • DBA
  • Architects and Developers


This training does not require a formal assessment of learning


Introduction to NoSQL

  • The history of the NoSQL movement.
  • The different DBMS management approaches over time: hierarchical, relational, objects, XML, NoSQL.
  • The five “Vs” of big data: Volume, Variety, Velocity, Veracity, Validity.
  • Unstructured data: web activity, document exchange, social networks, open data, IoT.
  • The big players behind the NoSQL movement and big data analytics: Google and Amazon.
  • Summary view of the different types of NoSQL engines from a data model perspective.
  • NoSQL, big data and cloud architectures: common and divergent architectural principles.
  • Distribution modes: with master and decentralized.
  • Distributed transactions, failover, savepoints, request parallelization, load balancing.
  • The positioning of NoSQL within analytical big data: from the era of the transaction to the era of interaction.

Relational and NoSQL

  • Relational databases: their strengths and limitations.
  • Strong data structuring (explicit schema) versus soft structure (implicit schema) and Agile modelling.
  • From ACID qualities to BASE qualities.
  • CAP theorem (consistency, availability, partitioning tolerance).
  • The different levels of consistency.
  • The SQL language, the performance of joins. Key access in NoSQL.
  • The Evolution to Distributed: Vertical and Horizontal Scalability.
  • Understanding NoSQL through the aggregate model and data centrality.

The worlds of NoSQL

  • World of NoSQL through its technical choices and different free NoSQL databases (from less structured to more structured).
  • Distributed architecture: principles, shared-nothing.
  • Availability and deferred consistency: gossip, timestamps, majority rule, the Merkle tree.
  • Patterns and models. How to model and work effectively in NoSQL.
  • Key-value and in-memory oriented databases: Redis, Riak, Aerospike.
  • Document-oriented databases: the JSON format. Couchbase Server, MongoDB.
  • Distributed column-oriented databases for operational big data: Hbase, Cassandra, ScyllaDB...
  • Graph-oriented engines: Neo4j, OrientDB...
  • JSON search engines: Elasticsearch, SOLR.
  • Time series databases: InfluxDB, KDB, Prometheus.

Choose and set up

  • What are the uses of NoSQL databases?
  • How to approach migration?
  • How to develop efficiently with NoSQL databases?
  • Which monitoring tools and how to choose them?
  • What is the administrative complexity and learning curve?
  • Use cases in existing companies.
  • Manage interactions with relational databases.
  • Implement NoSQL strategies with relational engines. The PostgreSQL example and its extensions.
  • Implementing NoSQL in public clouds. Database-as-a-service practices and offerings.

NoSQL and Big Data

  • Big data analytics: the Hadoop ecosystem.
  • Storage and processing. The different forms of storage in HDFS: SequenceFile, Apache Parquet.
  • Functions and uses: search engines, commercial suggestion tools, intrusion detectors...
  • Different types of processing: MapReduce, directed acyclic graph, flow, machine learning, distributed graphs...
  • The integrated tool: Apache Spark.
  • Connection with operational engines: ETL, Apache Sqoop.