NoSQL ट्यूटोरियल: NoSQL डेटाबेस के प्रकार और उदाहरण

NoSQL क्या है?

नोएसक्यूएल डाटाबेस 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 गूगल collect terabytes of user data every single day.

NoSQL डेटाबेस stands for “Not Only SQL” or “Not SQL”. Though a better term would be “NoREL”, 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:

नोएसक्यूएल क्यों?

NoSQL डेटाबेस की अवधारणा गूगल, फेसबुक जैसी इंटरनेट दिग्गज कंपनियों के बीच लोकप्रिय हो गई। Amazon, आदि जो बहुत बड़ी मात्रा में डेटा से निपटते हैं। जब आप बहुत बड़ी मात्रा में डेटा के लिए RDBMS का उपयोग करते हैं तो सिस्टम प्रतिक्रिया समय धीमा हो जाता है।

इस समस्या को हल करने के लिए, हम अपने मौजूदा हार्डवेयर को अपग्रेड करके अपने सिस्टम को “स्केल अप” कर सकते हैं। यह प्रक्रिया महंगी है।

The alternative for this issue is to distribute the database load on multiple hosts whenever the load increases. This method is known as “scaling out”.

NoSQL database is non-relational, so it scales out better than relational databases, as they are designed with web applications in mind.

NoSQL डेटाबेस का संक्षिप्त इतिहास

• 1998 – Carlo Strozzi uses the term NoSQL for his lightweight, open-source relational database.
• 2000 – Graph database Neo4j is launched.
• 2004 – गूगल BigTable is launched.
• 2005 - CouchDB लॉन्च किया गया है।
• 2007 – The research paper on Amazon Dynamo is released.
• 2008 – Facebook open sources the Cassandra परियोजना.
• 2009 – The term NoSQL was reintroduced.

NoSQL की विशेषताएं

गैर संबंधपरक

• NoSQL डेटाबेस कभी भी इसका पालन नहीं करते हैं संबंधपरक मॉडल.
• 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.

स्कीमा से मुक्त

• 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.

सरल एपीआई

• 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.

वितरित

• 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.

NoSQL डेटाबेस के प्रकार

NoSQL डेटाबेस 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.

NoSQL डेटाबेस के प्रकार:

• कुंजी-मूल्य जोड़ी आधारित
• स्तंभ-उन्मुख ग्राफ
• ग्राफ़ आधारित
• दस्तावेज़ उन्मुख

कुंजी मूल्य जोड़ी आधारित

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.

उदाहरण के लिए, एक कुंजी-मान युग्म में "वेबसाइट" जैसी कुंजी हो सकती है जो " जैसे मान से जुड़ी हो।Guru99 "।

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 कार्ट में मौजूद सामान।

Redis, Dynamo, and Riak are some NoSQL examples of key-value store databases. They are all based on Amazon'डायनमो पेपर.

स्तंभ के आधार पर

Column-oriented databases work on columns and are based on the BigTable paper by गूगल. 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, व्यापारिक सूचना, CRM, and library card catalogs.

एचबेस, Cassandra, and Hypertable are NoSQL query examples of column-based databases.

दस्तावेज़ उन्मुख

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 सिंपलडीबी, CouchDB, MongoDB, Riak, and Lotus Notes are popular document-oriented डीबीएमएस सिस्टम.

ग्राफ आधारित

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, अनंत ग्राफ, OrientDB, and FlockDB are some popular graph-based databases.

NoSQL के लिए क्वेरी मैकेनिज्म उपकरण

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.

CAP प्रमेय क्या है?

CAP theorem is also called Brewer’s theorem. It states that it is impossible for a distributed data store to offer more than two out of three guarantees:

1. कंसिस्टेंसी (Consistency)
2. उपलब्धता
3. विभाजन सहिष्णुता

संगति: किसी ऑपरेशन के निष्पादन के बाद भी डेटा एक जैसा बना रहना चाहिए। इसका मतलब है कि एक बार डेटा लिखे जाने के बाद, भविष्य में किसी भी रीड रिक्वेस्ट में वह डेटा शामिल होना चाहिए। उदाहरण के लिए, ऑर्डर स्टेटस अपडेट करने के बाद, सभी क्लाइंट को एक ही डेटा देखने में सक्षम होना चाहिए।

उपलब्धता: डेटाबेस हमेशा उपलब्ध और प्रतिक्रियाशील होना चाहिए। इसमें कोई डाउनटाइम नहीं होना चाहिए।

विभाजन सहिष्णुता: विभाजन सहनशीलता का अर्थ है कि सर्वरों के बीच संचार स्थिर न होने पर भी सिस्टम को काम करना जारी रखना चाहिए। उदाहरण के लिए, सर्वरों को कई समूहों में विभाजित किया जा सकता है जो एक दूसरे के साथ संचार नहीं कर सकते हैं। यहां, यदि डेटाबेस का हिस्सा अनुपलब्ध है, तो अन्य भाग हमेशा अप्रभावित रहते हैं।

अंततः संगति

The term “eventual consistency” 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.

आधार: Bसमान रूप से Aअनुपलब्ध, Sअक्सर राज्य, Eवेंटुअल स्थिरता

• 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.

नोएसक्यूएल के लाभ

• 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.
• यह तेज़ प्रदर्शन और क्षैतिज मापनीयता प्रदान करता है।
• 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.
• यह ऑनलाइन आवेदनों के लिए प्राथमिक डेटा स्रोत के रूप में काम कर सकता है।
• 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.

NoSQL के नुकसान

• No standardization rules.
• Limited query capabilities.
• आरडीबीएमएस databases and tools are comparatively mature.
• यह किसी भी पारंपरिक डाटाबेस क्षमता की पेशकश नहीं करता है, जैसे एक साथ कई लेनदेन किए जाने पर स्थिरता।
• 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.

अक्सर पूछे जाने वाले प्रश्न