No SQL
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This document discusses NoSQL databases and compares them to SQL databases. It defines NoSQL as non-relational data storage systems that are schema-free and relax ACID properties. NoSQL is useful for massive data stores with frequent schema changes, as seen with social media sites. The CAP theorem states that only two of consistency, availability, and partition tolerance can be achieved at once. NoSQL databases favor availability and partition tolerance over consistency. The document compares database types and performance, and provides examples of querying and updating documents in MongoDB.
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NoSQL plays a vital role in an enterprise application which needs to access and analyze a massive set of data that is being made available on multiple virtual servers (remote based) in the cloud infrastructure and mainly when the data set is not structured. Hence, the NoSQL database is designed to overcome the Performance, Scalability, Data Modelling and Distribution limitations that are seen in the Relational Databases.
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Azure Cosmos DB is a globally distributed, massively scalable, multi-model database service. It supports document, key-value, graph, and column-family data models. Cosmos DB provides turnkey global distribution, elastic scale of storage and throughput, guaranteed low latency at the 99th percentile, comprehensive SLAs, and five consistency models. It is designed for data growth and puts data where users are located.
Introduction to NoSQL
The document summarizes a meetup about NoSQL databases hosted by AWS in Sydney in 2012. It includes an agenda with presentations on Introduction to NoSQL and using EMR and DynamoDB. NoSQL is introduced as a class of databases that don't use SQL as the primary query language and are focused on scalability, availability and handling large volumes of data in real-time. Common NoSQL databases mentioned include DynamoDB, BigTable and document databases.
Apache Cassandra
This document provides an introduction to Apache Cassandra, a NoSQL distributed database. It discusses Cassandra's history and development by Facebook, key features including distributed architecture, data replication, fault tolerance, and linear scalability. It also compares relational and NoSQL databases, and lists some major companies that use Cassandra like Netflix, Apple, and eBay.
SQL and NoSQL in SQL Server
This document discusses SQL and NoSQL approaches to scaling databases. It describes how social networks and other large-scale websites use techniques like sharding and messaging to partition data across many databases. It also discusses how SQL Server is adopting NoSQL paradigms like flexible schemas and federated sharding to provide scalability. The document aims to educate about scaling databases and how SQL Server is evolving to support both SQL and NoSQL approaches.
Introduction of Redis as NoSQL Database
Redis is an open source, advanced key-value data store,Often referred to as a data structure server since keys can contain strings, hashes, lists, sets and sorted sets
NoSQL
This document provides an overview and comparison of relational and NoSQL databases. Relational databases use SQL and have strict schemas while NoSQL databases are schema-less and include document, key-value, wide-column, and graph models. NoSQL databases provide unlimited horizontal scaling, very fast performance that does not deteriorate with growth, and flexible queries using map-reduce. Popular NoSQL databases include MongoDB, Cassandra, HBase, and Redis.
Big data stores
This document discusses several NoSQL databases including key-value, column-family, graph, and document databases. It provides information on Cassandra, DynamoDB, Riak, Redis, CouchDB, Azure Table Storage, BerkeleyDB, HBase, BigTable, HyperTable, Neo4j, and MongoDB, summarizing their architectures, features, uses cases, and advantages.
No sq lv2
NoSQL databases are non-relational data storage systems that are designed for large volumes of data across many servers. They are schema-less, support document or key-value data models, and are distributed, open source, and designed for scalability. Common types include key-value stores, document databases, column-family stores, and graph databases. NoSQL databases sacrifice consistency guarantees and transactions for horizontal scalability and high availability.
Deep dive to ElasticSearch - معرفی ابزار جستجوی الاستیکی
در این اسلاید به مباحث زیر می پردازیم:
مقدمات پایگاه داده های غیر اس.کیو.ال، مبانی جستجوگرها
سپس معرفی ابزار جستجوی الاستیکی، کاربردها، معماری کلی، مقایسه با ابزارهای مشابه
افزودن تحلیلگر متن و در نهایت لینک آن با دات نت
ا
No sql
This document provides an overview of NoSQL databases and Cassandra in particular. It discusses that NoSQL databases were developed to address the inability of relational databases to scale horizontally to large datasets and distributed architectures. Cassandra is an open source, column-oriented NoSQL database that provides high availability and eventual consistency without ACID transactions through its implementation of the CAP theorem and Dynamo paper concepts. The document outlines Cassandra's data model, APIs, and Hector client library and provides code examples for common operations.
SQL or NoSQL, is this the question? - George Grammatikos
This document provides an overview and comparison of SQL and NoSQL databases. It lists the most popular databases according to a Stack Overflow survey, including SQL databases like Azure SQL and NoSQL databases like Azure Cosmos DB. It then defines RDBMS and NoSQL databases and provides examples of relational and non-relational data models. The document compares features of SQL and NoSQL databases such as scalability, performance, data modeling flexibility and pricing. It also includes live demo instructions for provisioning Azure SQL and Cosmos DB databases.
6269441.ppt
The document provides an introduction to NoSQL databases. It discusses the issues with scaling relational databases, defines what NoSQL is, and covers some of the major NoSQL databases including key-value, document, and column-based databases. It also discusses the CAP theorem and how NoSQL databases provide more flexibility and horizontal scaling compared to relational databases.
NO SQL: What, Why, How
This document provides an overview of NoSQL databases, including why they are used, common types, and how they work. The key points are:
1) SQL databases do not scale well for large amounts of distributed data, while NoSQL databases are designed for horizontal scaling across servers and partitions.
2) Common types of NoSQL databases include document, key-value, graph, and wide-column stores, each with different data models and query approaches.
3) NoSQL databases sacrifice consistency guarantees and complex queries for horizontal scalability and high availability. Eventual consistency is common, with different consistency models for different use cases.
NoSQL_Night
This document provides an overview of a NoSQL Night event presented by Clarence J M Tauro from Couchbase. The presentation introduces NoSQL databases and discusses some of their advantages over relational databases, including scalability, availability, and partition tolerance. It covers key concepts like the CAP theorem and BASE properties. The document also provides details about Couchbase, a popular document-oriented NoSQL database, including its architecture, data model using JSON documents, and basic operations. Finally, it advertises Couchbase training courses for getting started and administration.
A Seminar on NoSQL Databases.
Here is my seminar presentation on No-SQL Databases. it includes all the types of nosql databases, merits & demerits of nosql databases, examples of nosql databases etc.
For seminar report of NoSQL Databases please contact me: ndc@live.in
No sql (1)
This document provides an overview of NoSQL databases. It begins with an agenda that covers the history of NoSQL, what NoSQL is, the CAP theorem, types of NoSQL databases like key-value and schema-less models, advantages of NoSQL like scalability and flexibility, and what is given up like joins and ACID transactions. It then discusses Cassandra as an example NoSQL database and its use of the Dynamo model and Thrift API. Statistics are given showing Cassandra's improved performance over MySQL for Facebook's use case. The document was made by students for their class.
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No SQL
- 1. NOSQL : WHY, WHAT AND WHEN Not Only SQL
- 2. WHAT IS NOSQL? Stands for Not Only SQL Class of non-relational data storage systems Schema-free All NoSQL offerings relax one or more of the ACID properties
- 3. WHY NOSQL? Flexibility Scalability Massive data stores Availability Lower operational cost
- 4. WHO NEEDS IT? Explosion of social media sites (Facebook,Twitter) with large data needs Rise of cloud-based solutions such asAmazon S3 (simple storage solution) Just as moving to dynamically-typed languages (Ruby/ Groovy), a shift to dynamically-typed data with frequent schema changes
- 5. CAPTHEOREM “Of three properties of shared-data systems (Consistency, Availability and tolerance to network Partitions) only two can be achieved at any given moment in time.”
- 6. CAPTHEOREM • Consistency (all nodes see the same data at the same time)
- 7. CAPTHEOREM • Consistency (all nodes see the same data at the same time) • Availability (a guarantee that every request receives a response about whether it succeeded or failed)
- 8. CAPTHEOREM • Consistency (all nodes see the same data at the same time) • Availability (a guarantee that every request receives a response about whether it succeeded or failed) • Partition tolerance (the system continues to operate despite arbitrary partitioning due to network failures)
- 9. ACID PROPERTY Atomic: Everything in a transaction succeeds or the entire transaction is rolled back. Consistent: A transaction cannot leave the database in an inconsistent state. Isolated:Transactions cannot interfere with each other. Durable: Completed transactions persist, even when servers restart etc.
- 10. EVENTUAL CONSISTENCY (BASE) != STRONG CONSISTENCY Eventual consistency (normally asynchronous transactions) ACID provides strong consistency • Basically Available • Soft state • Eventual consistency
- 11. WHY NOT NOSQL DRBMS databases and tools are mature NoSQL implementations often “alpha” Data consistency , transactions
- 12. TYPES OF NOSQL DATABASES Column: Accumulo, Cassandra, Druid Document: MongoDB , Apache CouchDB , HyperDex Key-value: Oracle NoSQL , Dynamo , Riak , Redis Graph: Alegro , Neo4J , Stardog
- 13. RDBMSVS. NOSQL Strong consistency vs. Eventual consistency Big dataset vs. HUGE dataset Scaling is possible vs. Scaling is easy SQL vs. Map-Reduce Good availability vs.Very high availability
- 16. PERFORMANCE SQL SERVERVS. MONGO
- 17. FEATURES Standard DB stuff : Indexing , replication support Documents are stored in BSON (binary JSON) Any valid JSON can be easily imported and queried Schema-less = very flexible Easy to install Document-oriented = flexible
- 18. QUERYING
- 19. db.exnum.update({ number : { $gt : 18 } } $lt - < $lte - <= $gt - > $gte - >= $ne - !=
- 20. Find & Sort & Count
- 21. Update Find Remove Shema-less
- 23. Multi-update
- 24. In Mongo : db.exnum.update({ number : { $gt : 18 } } , { $set : { type : “A” } } , { multi : true}) In SQL : UPDATE exnum SET status = “A” WHERE number > 18