No sql - { If and Else }
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This document provides an overview of NoSQL databases, including: 1) NoSQL databases differ from relational databases by being schemaless and not using joins. They were created to address limitations of relational databases. 2) NoSQL databases can be categorized as key-value, column-oriented, document-based or graph-based. MongoDB is presented as an example document-based NoSQL database. 3) The CAP theorem states that a distributed system cannot simultaneously provide consistency, availability, and partition tolerance. Pros and cons of NoSQL databases are discussed.
No sql - { If and Else }
- 1. NoSqlFuture begins hereAuthor: Marjan NikolovskiDate: 2011-02-03
- 2. ContentNoSql as movementPros and ConsCategoriesMongo DB showcaseDiscussion
- 3. NoSql as movement“NoSQL is a term used to designate databases that differ from classic relational databases in some way”SchemalessNo “joins”
- 4. NoSql as movementSchemaless – means everything can be stored without order, type, structureNo “joins” – means normalization is not used to relate and retrieve the dataNoSql as movementInvented to cover what RDBMS could notFast write/read under heavy usage of a systemHighly distribution of dataBetter architecture of distributed systemsFun
- 5. Cap TheoremCAP Theorem !!!“It is impossible for a distributed computer system to simultaneously provide all three of the following guarantees: - Consistency (all nodes see the same data at the same time) - Availability (node failures do not prevent survivors from continuing to operate) - Partition Tolerance (the system continues to operate despite arbitrary message loss)According to the theorem, a distributed system can satisfy any two of these guarantees at the same time, but not all three”
- 6. Cap Theorem - 2
- 7. Pros and Cons - 2PROSComplex objectsHigh-Volume Low-Value dataReal-time analysisOnline games (MMRPG)Search enginesScalable horizontally(sharding)RedundancyFlexibilityFaster developmentGeospatialCONSTransactions and distributedtransactions
- 8. Business IntelligencePros and ConsWhat are we architecting ???What are our options ???Result …
- 9. CategoriesUnder NoSql four main categories exists:Key / ValueBigTableDocumentGraph
- 10. Categories – Key / ValueWe can see on this type as distributed hash tableUsed for caching layersQuerying is done by key onlyHighly distributiveProducts:MemcachedProject VoldemortAmazon Dynamo
- 11. Categories - BigTableBigTable are step forward from Key/Value storesThere is some order in these stores and querying can be done by more paramsMore like the RDBMS that we now with excluded foreign key concept and with support each row to have different columnsProducts:Apache CassandraApache HBase
- 12. Categories – DocumentDocuments stores are json/xml based stores for objectsHighly queryableProductsMongoDBRavenDBApache CouchDB
- 13. Categories – GraphGraph stores store data in vortex connected with zero or more vortexes.Data is held in hashtable in each nodeRich objects are not supportedProductsNeo4jAllegroGraphInfoGrid
- 14. Categories – size/complexity*Complexity = Sophistication of data modeling
- 15. Mongo DB showcase - 1What isDocument storeFast, scalable and availableJSon – used for data hydratationDynamicStores data structured as documents instead of row as seen in RDBMSUses Query, Insert, Update and Remove for data manipulationUsed for adding data at high rates without “choking” the system
- 16. Mongo DB showcase - 2Internals of CoreMap files in memory (virtual) Memory is allocated by namespaces Free space comes at the end of the structureEach document contains a header for traversal and position, body (document data) and paddingReplicationMaster/Slave and Replication sets architectureBoth require Master but Replication set vote for new master if the one dedicated for the job is unavailableCursorsResults can be of type cursor which can be iterated until cursor have 0 elements left
- 17. Mongo DB showcase - 3Documents inEach document can be of size max to 4mbEach document you insert into MongoDB will be assigned an id consisted of: This is a 12-byte value consisting of 4 parts: timestamp (4 bytes)machine identifier (3 bytes)process id (2 bytes)increment (3 bytes)in MongoDB, each document will contain not only the values, but the key names (~"column names" in relational db-speak) too. So if you have keys: “Username" and “Password", then those alone will add 16 bytes to each document.MongoDB automatically adds some padding to the documents to allow for documents to grow in size to try and reduce the need for documents to be moved around if they do grow
- 18. Mongo DB showcase - 4Map reduce andMap/Reduce is done via javascript
- 19. Mongo DB showcase - 5Simple usageOn win32 start mongod.exeStart mongo.exe test client for testing db.Workers.insert({ _workerId: “936DA01F-9ABD-4d9d-80C7-02AF85C822A8”, name: “XyZ”, department: “services”,subdepartment: “.NET”});db.Workers.find({ name: “XyZ” });
- 20. Mongo DB showcase - 6Performance analyses
- 21. Mongo DB showcase - 7So how can we use it in .NET ???
- 22. Mongo DB showcase - 8Get Mongodb-csharp driverhttp://github.com/samus/mongodb-csharp/commits/master/Let’s start
- 23. SuggestionsCheck: The high scalability blogApache CassandraRanvenDB, .Net implementation of document storemysql performance blogCAP theorem
- 24. Discussion
- 25. Sponsored by
Editor's Notes
- #9: Transaction avalable only for one row. No batching transactions avaliable.Needs middleware to handle transactions for multiple rows