NoSQL Tutorial: Types of NoSQL Databases & Example
โก Chytrรฉ shrnutรญ
NoSQL is a non-relational database management system that does not require a fixed schema, avoids joins, and scales easily. This resource explains what NoSQL is, why it exists, its history, features, the four database types, the CAP theorem, eventual consistency, and its advantages and disadvantages.

Co je NoSQL?
NoSQL databรกze is a non-relational data management system that does not require a fixed schema. It avoids joins, and is easy to scale. The major purpose of using a NoSQL database is for distributed data stores with humongous data storage needs. NoSQL is used for big data and real-time web apps. For example, companies like Twitter, Facebook, and Google shromaลพฤujรญ terabajty uลพivatelskรฝch dat kaลพdรฝ den.
NoSQL databรกze stands for โNot Only SQLโ or โNot SQLโ. Though a better term would be โNoRELโ, NoSQL caught on. Carl Strozzi introduced the NoSQL concept in 1998.
Traditional RDBMS uses SQL syntax to store and retrieve data for further insights. Instead, a NoSQL database system encompasses a wide range of database technologies that can store structured, semi-structured, unstructured, and polymorphic data. Let us understand about NoSQL with a diagram in this NoSQL database tutorial:
Proฤ NoSQL?
Koncept NoSQL databรกzรญ se stal populรกrnรญm u internetovรฝch gigantลฏ, jako je Google, Facebook, Amazonatd., kteลรญ se zabรฝvajรญ obrovskรฝmi objemy dat. Pลi pouลพitรญ RDBMS pro velkรฉ objemy dat se doba odezvy systรฉmu zpomalรญ.
Abychom tento problรฉm vyลeลกili, mohli bychom โrozลกรญลitโ naลกe systรฉmy upgradem naลกeho stรกvajรญcรญho hardwaru. Tento proces je drahรฝ.
The alternative for this issue is to distribute the database load on multiple hosts whenever the load increases. This method is known as โscaling outโ.
NoSQL database is non-relational, so it scales out better than relational databases, as they are designed with web applications in mind.
Struฤnรก historie NoSQL databรกzรญ
- 1998 โ Carlo Strozzi uses the term NoSQL for his lightweight, open-source relational database.
- 2000 โ Graph database Neo4j is launched.
- 2004 - Google BigTable is launched.
- 2005 - CouchDB je vypuลกtฤn.
- 2007 โ The research paper on Amazon Dynamo is released.
- 2008 โ Facebook open sources the Cassandra projekt.
- 2009 โ The term NoSQL was reintroduced.
Vlastnosti NoSQL
Nerelaฤnรญ
- NoSQL databรกze nikdy nedodrลพujรญ relaฤnรญ model.
- Never provide tables with flat fixed-column records.
- Work with self-contained aggregates or BLOBs.
- Do not require object-relational mapping and data normalization.
- No complex features like query languages, query planners, referential integrity joins, or ACID.
Bez schรฉmatu
- NoSQL databases are either schema-free or have relaxed schemas.
- Do not require any sort of definition of the schema of the data.
- Offer heterogeneous structures of data in the same domain.

Jednoduchรฉ API
- Offers easy-to-use interfaces for storage and querying data.
- APIs allow low-level data manipulation and selection methods.
- Text-based protocols mostly used with HTTP REST with JSON.
- Mostly used no standard-based NoSQL query language.
- Web-enabled databases running as internet-facing services.
Distribuovรกno
- Multiple NoSQL databases can be executed in a distributed fashion.
- Offers auto-scaling and fail-over capabilities.
- Often the ACID concept can be sacrificed for scalability and throughput.
- Mostly no synchronous replication between distributed nodes; asynchronous multi-master replication, peer-to-peer, HDFS replication.
- Only providing eventual consistency.
- Shared-nothing architecture. This enables less coordination and higher distribution.
Typy NoSQL databรกzรญ
NoSQL databรกze are mainly categorized into four types: Key-value pair, Column-oriented, Graph-based, and Document-oriented. Every category has its unique attributes and limitations. None of the above-specified databases is better at solving all the problems. Users should select the database based on their product needs.
Typy NoSQL databรกzรญ:
- Na zรกkladฤ pรกru klรญฤโhodnota
- Sloupcovฤ orientovanรฝ graf
- Na zรกkladฤ grafลฏ
- Orientace na dokumenty
Na zรกkladฤ pรกru klรญฤovรฝch hodnot
Data is stored in key/value pairs. It is designed in such a way to handle lots of data and heavy load. Key-value pair storage databases store data as a hash table where each key is unique, and the value can be a JSON, BLOB (Binary Large Objects), string, etc.
Napลรญklad pรกr klรญฤ-hodnota mลฏลพe obsahovat klรญฤ jako โWebovรก strรกnkaโ spojenรฝ s hodnotou jako โGuru99. "
It is one of the most basic NoSQL database examples. This kind of NoSQL database is used as a collection, dictionaries, associative arrays, etc. Key-value stores help the developer to store schema-less data. They work best for shopping obsah koลกรญku.
Redis, Dynamo, and Riak are some NoSQL examples of key-value store databases. They are all based on AmazonPapรญr Dynamo.
Na zรกkladฤ sloupcลฏ
Column-oriented databases work on columns and are based on the BigTable paper by Google. Every column is treated separately. Values of single-column databases are stored contiguously.
They deliver high performance on aggregation queries like SUM, COUNT, AVG, MIN, etc., as the data is readily available in a column. Column-based NoSQL databases are widely used to manage data warehouses, business intelligence, CRM, and library card catalogs.
HBase, Cassandra, and Hypertable are NoSQL query examples of column-based databases.
Orientace na dokumenty
Document-Oriented NoSQL DB stores and retrieves data as a key-value pair, but the value part is stored as a document. The document is stored in JSON or XML formats. The value is understood by the DB and can be queried.
In this diagram on your left, you can see we have rows and columns, and on the right, we have a document database which has a similar structure to JSON. Now for the relational database, you have to know what columns you have, and so on. However, for a document database, you have a data store like a JSON object. You do not need to define it, which makes it flexible.
The document type is mostly used for CMS systems, blogging platforms, real-time analytics, and e-commerce applications. It should not be used for complex transactions which require multiple operations or queries against varying aggregate structures.
Amazon SimpleDB, CouchDB, MongoDB, Riak, and Lotus Notes are popular document-oriented DBMS systรฉmy.
Na zรกkladฤ grafu
A graph type database stores entities as well as the relations amongst those entities. The entity is stored as a node with the relationship as edges. An edge gives a relationship between nodes. Every node and edge has a unique identifier.
Compared to a relational database where tables are loosely connected, a graph database is multi-relational in nature. Traversing relationships is fast, as they are already captured in the DB, and there is no need to calculate them. Graph base databases are mostly used for social networks, logistics, and spatial data.
Neo4J, nekoneฤnรฝ graf, OrientDB, and FlockDB are some popular graph-based databases.
Nรกstroje Query Mechanism pro NoSQL
The most common data retrieval mechanism is the REST-based retrieval of a value based on its key/ID with a GET resource.
Document store databases offer more difficult queries, as they understand the value in a key-value pair. For example, CouchDB allows defining views with MapReduce.
Co je teorรฉm CAP?
CAP theorem is also called Brewerโs theorem. It states that it is impossible for a distributed data store to offer more than two out of three guarantees:
- Konzistence
- dostupnost
- Tolerance oddรญlลฏ
Konzistence: Data by mฤla zลฏstat konzistentnรญ i po provedenรญ operace. To znamenรก, ลพe jakmile jsou data zapsรกna, jakรฝkoli budoucรญ poลพadavek na ฤtenรญ by mฤl tato data obsahovat. Napลรญklad po aktualizaci stavu objednรกvky by vลกichni klienti mฤli vidฤt stejnรก data.
Dostupnost: Databรกze by mฤla bรฝt vลพdy dostupnรก a reagovat. Nemฤl by mรญt ลพรกdnรฉ prostoje.
Tolerance oddรญlลฏ: Tolerance oddรญlลฏ znamenรก, ลพe systรฉm by mฤl nadรกle fungovat, i kdyลพ komunikace mezi servery nenรญ stabilnรญ. Servery mohou bรฝt napลรญklad rozdฤleny do nฤkolika skupin, kterรฉ spolu nemusรญ komunikovat. Zde platรญ, ลพe pokud je ฤรกst databรกze nedostupnรก, ostatnรญ ฤรกsti nejsou vลพdy ovlivnฤny.
Pลรญpadnรก konzistence
The term โeventual consistencyโ means to have copies of data on multiple machines to get high availability and scalability. Thus, changes made to any data item on one machine have to be propagated to other replicas.
Data replication may not be instantaneous, as some copies will be updated immediately while others in due course of time. These copies may be mutually inconsistent, but in due course of time, they become consistent. Hence, the name eventual consistency.
BรZE: Basticky Ak dispozici, Sฤasto stรกt, Eventivnรญ konzistence
- Basically available means the DB is available all the time as per the CAP theorem.
- Soft state means even without an input, the system state may change.
- Eventual consistency means that the system will become consistent over time.
Vรฝhody NoSQL
- Can be used as a primary or analytic data source.
- Big data capability.
- No single point of failure.
- Easy replication.
- No need for a separate caching layer.
- Poskytuje rychlรฝ vรฝkon a horizontรกlnรญ ลกkรกlovatelnost.
- Can handle structured, semi-structured, and unstructured data with equal effect.
- Object-oriented programming which is easy to use and flexible.
- NoSQL databases do not need a dedicated high-performance server.
- Support key developer languages and platforms.
- Simpler to implement than using RDBMS.
- Mลฏลพe slouลพit jako primรกrnรญ zdroj dat pro online aplikace.
- Handles big data which manages data velocity, variety, volume, and complexity.
- Excels at distributed database and multi-data center operations.
- Eliminates the need for a specific caching layer to store data.
- Offers a flexible schema design which can easily be altered without downtime or service disruption.
Nevรฝhody NoSQL
- No standardization rules.
- Limited query capabilities.
- RDBMS databases and tools are comparatively mature.
- Nenabรญzรญ ลพรกdnรฉ tradiฤnรญ databรกzovรฉ funkce, jako je konzistence pลi provรกdฤnรญ vรญce transakcรญ souฤasnฤ.
- When the volume of data increases, it is difficult to maintain unique values as keys become difficult.
- Does not work as well with relational data.
- The learning curve is stiff for new developers.
- Open source options are not so popular for enterprises.






