Phil Coleman Presentation

Dec 9, 20110 likes603 views

The document discusses NoSQL databases and Cassandra in particular. It explains that NoSQL databases are not relational, use eventual consistency instead of ACID properties, and are better suited to modern data and web-scale applications. Cassandra is an open source NoSQL database based on Amazon's Dynamo and Google's Bigtable. It uses a column-oriented data model and is highly scalable, fault-tolerant and distributed across commodity servers.

NoSQL Or: How I Learned to Stopped Worrying and Love Cassandra

NoSQL != No SQL N ot O nly SQL Mostly Same Functionality Same Purpose No Longer Relational

ACID vs WHAM ACID A tomicity C onsistency I solation D urability Issues Dated Not Necessary

ACID vs WHAM WHAM W eb-scale H igh Traffic A daptive Schema M ulti-Use Benefits Better Suited for the current Data Ecosystem

No Family Drama Removes Existing Slowdowns Relations Consistency Between Related Data Joins More Easily Distributed Faster Queries

Cassandra - History 2007 - Initial Developed by Facebook Manage User Inbox Searching 2008 - Released as Open Source 2008 2009 - Picked up by Apache Present - Cassandra 1.0

Big Table + Dynamo Basic Design Principle Big Table Column Families Adaptable Similarities with SQL Dynamo Decentralized Distributive Nature Easily Scalable Durable

Building the Pyramid Columns 3 Values Name Value Time Stamp Primitive Types Similar Role to Columns in RDBMs

Example Column 1 Name: City Value: Houston Column 1 Name: Attire Value: Casual

Building the Pyramid Super Columns 2 Values Name Collection of Columns Columns can be sorted by name.

Example Super Column 1 Name: Hours Value: Column 1 Name: Mon-Thu Value: 10 am �C 10 pm Value: Column 2 Name: Fri-Sat Value: 10 am �C 11 pm Value: Column 3 Name: Sun Value: 10 am �C 9 pm

Building the Pyramid Rows A Collection of Columns Identified by A Unique Key Columns not necessarily related Similar Role to Rows in RDBMs

Example Row 1 Key: nikonikogreekcafe Column 1: City Column 2: Attire

Building the Pyramid Column Family A Collection of Rows Either Columns or Super Columns Query on Only One Column Family Similar Role to Tables in RDBMs

Example Value: Column 1 Name: Hours.Mon-Thu Value: 10 am �C 10 pm Value: Column 2 Name: Hours.Fri-Sat Value: 10 am �C 11 pm Value: Column 3 Name: Hours.Sun Value: 10 am �C 9 pm

Example Column Family: Name: Location Row 1: Niko Niko's Row 2: Goode Co. Row 3: Datafiniti

Building the Pyramid Keyspace A Collection of Column Families Global Settings Sorting Replication Factor Similar Role to Databases in RDBMs

Advantages Horizontally Scalable Decentralized Approach Eventually Consistent Auto-bootstrapping Distributed Computing Distributed Storage

Advantages Real Time Responses Read and Writes Removes Slower Functions Joins/Relations Consistency Does not need to Sort Able to return the first matches.

Advantages Developed for programmers Good API Support In most major languages Object-based Interaction model Few Function Calls Greater Control

Advantages No Single Point of Failure Redundancy across multiple nodes Decentralized Hinted Hand Offs Other Nodes will handle writes Update failed nodes when back online.

Disadvantages No Relational Model No Internal Joins Less Consistency Faster Queries

Disadvantages No Sorting at Query Time Less Flexibility on Data Returned No Ranking Able to Return First Results it Finds

Disadvantages No SQL Uses Proprietary Query Language (CQL) Less Familiar

Potential Uses Key Elements Large Amounts of Data Data Parameters Shift or Grow Frequently Real Time Responses Data is Not Reliant on Relations

Potential Uses Inbox Management Key/Value Store Social Network Management Data Warehouse

The document discusses NoSQL databases and their advantages over SQL databases. It describes the main NoSQL database models - key-value, document, columnar, and graph - and provides examples of implementations for each. The document also compares some popular NoSQL databases like MongoDB, Cassandra, Redis and Elasticsearch based on factors like data model, consistency, availability, scalability and querying capabilities. Finally, it discusses solutions for working with geospatial data in NoSQL databases.

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No sqlShruti_gtbit

This document provides an overview of NoSQL databases, including: - NoSQL databases are non-relational and do not require fixed schemas like SQL databases. - They are useful for large, unstructured datasets and provide high scalability and availability. - Cassandra is a popular open-source NoSQL database that uses a column-oriented data model and eventual consistency. - Hector is a Java client that provides an API for Cassandra and handles connection pooling. - NoSQL databases sacrifice features like joins and ACID transactions in exchange for scalability and high availability.

Front Range PHP NoSQL DatabasesJon Meredith

NoSQL databases are non-relational databases designed for large volumes of data across many servers. They emerged to address scaling and reliability issues with relational databases. While different technologies, NoSQL databases are designed for distribution without a single point of failure and to sacrifice consistency for availability if needed. Examples include Dynamo, BigTable, Cassandra and CouchDB.

NO SQL Databases, Big Data and the cloudManu Cohen-Yashar

1) NoSQL databases were developed to address problems with scaling relational databases (RDBMS) and fitting certain types of data and use cases. 2) NoSQL databases are non-relational and come in different types including key-value, wide column, document, and graph databases. They are designed for high scale, simplicity, and distribution across clusters. 3) The cloud allows for massive data analysis by providing unlimited scalability through mounting large compute clusters to process vast amounts of diverse data from various sources.

No sq lv2Nusrat Sharmin

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.

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Next Generation Databases mostly addressing some of the points: being non-relational, distributed, open-source and horizontally scalable. The original intention has been modern web-scale databases. The movement began early 2009 and is growing rapidly. Often more characteristics apply such as: schema-free, easy replication support, simple API, eventually consistent / BASE (not ACID), a huge amount of data and more. So the misleading term "nosql" (the community now translates it mostly with "not only sql") should be seen as an alias to something like the definition above.

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No sqlMurat ?akal

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.

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Phil Coleman Presentation

1. NoSQL Or: How I Learned to Stopped Worrying and Love Cassandra

2. What is NoSql?

3. NoSQL != No SQL N ot O nly SQL Mostly Same Functionality Same Purpose No Longer Relational

4. ACID vs WHAM ACID A tomicity C onsistency I solation D urability Issues Dated Not Necessary

5. ACID vs WHAM WHAM W eb-scale H igh Traffic A daptive Schema M ulti-Use Benefits Better Suited for the current Data Ecosystem

6. No Family Drama Removes Existing Slowdowns Relations Consistency Between Related Data Joins More Easily Distributed Faster Queries

7. Implementations

8. Cassandra - History 2007 - Initial Developed by Facebook Manage User Inbox Searching 2008 - Released as Open Source 2008 2009 - Picked up by Apache Present - Cassandra 1.0

9. Big Table + Dynamo Basic Design Principle Big Table Column Families Adaptable Similarities with SQL Dynamo Decentralized Distributive Nature Easily Scalable Durable

10. Cassandra Pyramid

11. Example

12. Building the Pyramid Columns 3 Values Name Value Time Stamp Primitive Types Similar Role to Columns in RDBMs

13. Example Column 1 Name: City Value: Houston Column 1 Name: Attire Value: Casual

14. Building the Pyramid Super Columns 2 Values Name Collection of Columns Columns can be sorted by name.

15. Example Super Column 1 Name: Hours Value: Column 1 Name: Mon-Thu Value: 10 am �C 10 pm Value: Column 2 Name: Fri-Sat Value: 10 am �C 11 pm Value: Column 3 Name: Sun Value: 10 am �C 9 pm

16. Building the Pyramid Rows A Collection of Columns Identified by A Unique Key Columns not necessarily related Similar Role to Rows in RDBMs

17. Example Row 1 Key: nikonikogreekcafe Column 1: City Column 2: Attire

18. Building the Pyramid Column Family A Collection of Rows Either Columns or Super Columns Query on Only One Column Family Similar Role to Tables in RDBMs

19. Example Value: Column 1 Name: Hours.Mon-Thu Value: 10 am �C 10 pm Value: Column 2 Name: Hours.Fri-Sat Value: 10 am �C 11 pm Value: Column 3 Name: Hours.Sun Value: 10 am �C 9 pm

20. Example Column Family: Name: Location Row 1: Niko Niko's Row 2: Goode Co. Row 3: Datafiniti

21. Building the Pyramid Keyspace A Collection of Column Families Global Settings Sorting Replication Factor Similar Role to Databases in RDBMs

22. Advantages Horizontally Scalable Decentralized Approach Eventually Consistent Auto-bootstrapping Distributed Computing Distributed Storage

23. Advantages Real Time Responses Read and Writes Removes Slower Functions Joins/Relations Consistency Does not need to Sort Able to return the first matches.

24. Advantages Developed for programmers Good API Support In most major languages Object-based Interaction model Few Function Calls Greater Control

25. Advantages No Single Point of Failure Redundancy across multiple nodes Decentralized Hinted Hand Offs Other Nodes will handle writes Update failed nodes when back online.

26. Disadvantages No Relational Model No Internal Joins Less Consistency Faster Queries

27. Disadvantages No Sorting at Query Time Less Flexibility on Data Returned No Ranking Able to Return First Results it Finds

28. Disadvantages No SQL Uses Proprietary Query Language (CQL) Less Familiar

29. Potential Uses Key Elements Large Amounts of Data Data Parameters Shift or Grow Frequently Real Time Responses Data is Not Reliant on Relations

30. Potential Uses Inbox Management Key/Value Store Social Network Management Data Warehouse

31. Potential Uses Major Users

32. Questions?

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