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oracle 12 and sap hana tutorials skip to main skip to sidebar home posts rss comments rss edit oracle 12 and sap hana tutorials sap tutorials sunday may 12 2013 oracle vs sap hana basics sap hana is an in memory column oriented relational database management system developed and marketed by sap se 1 2 its primary function as a database server is to store and retrieve data as requested by the applications in addition it performs advanced analytics predictive analytics spatial data processing text analytics text search streaming analytics graph data processing and includes etl capabilities as well as an application server during the early development of sap hana in prague a number of technologies were developed or acquired by sap se these included trex search engine in memory column oriented search engine p time in memory oltp platform acquired by sap in 2005 and maxdb with its in memory livecache engine 3 4 the first major demonstration of the platform was in 2008 teams from sap se the hasso plattner institute and stanford university demonstrated an application architecture for real time analytics and aggregation former sap se executive vishal sikka mentioned this architecture as hasso s new architecture 5 before the name hana stabilized people referred to this product as new database 6 the software was previously called sap high performance analytic appliance 7 the first product shipped in late november 2010 4 8 by mid 2011 the technology had attracted interest but more experienced business customers considered it to be in early days 9 hana support for sap netweaver business warehouse was announced in september 2011 for availability by november 10 in 2012 sap promoted aspects of cloud computing 11 in october 2012 sap announced a platform as a service offering called the sap hana cloud platform 12 13 and a variant called sap hana one that used a smaller amount of memory 14 15 in may 2013 a managed private cloud offering called the hana enterprise cloud service was announced 16 17 in may 2013 business suite on hana became available enabling customers to run sap enterprise resource planning functions on the hana platform 18 19 s 4hana released in 2015 written specifically for the hana platform combines functionality for erp crm srm and others into a single hana system 20 s 4hana is intended to be a simplified business suite replacing earlier generation erp systems 21 while it is likely that sap will focus its innovations on s 4hana some customers using non hana systems have raised concerns of being locked into sap products since s 4hana requires an sap hana system to run customers running sap business suite applications on hardware not certified by sap would need to migrate to a sap certified hana database should they choose the features offered by s 4hana 22 rather than versioning the software utilizes service packs referred to as support package stacks sps for updates support package stacks are released every 6 months 23 in november 2016 sap announced sap hana 2 which offers enhancements to multiple areas such as database management and application management and includes two new cloud services text analysis and earth observation analysis 24 hana customers can upgrade to hana 2 from sps10 and above customers running sps9 and below must first upgrade to sps12 before upgrading to hana 2 sps01 25 overview edit the key distinctions between hana and previous generation sap systems are that it is a column oriented in memory database that combines olap and oltp operations into a single system thus in general sap hana is an oltap system 26 storing data in main memory rather than on disk provides faster data access and by extension faster querying and processing 27 while storing data in memory confers performance advantages it is a more costly form of data storage observing data access patterns up to 85 of data in an enterprise system may be infrequently accessed 27 therefore it can be cost effective to store frequently accessed or hot data in memory while the less frequently accessed warm data is stored on disk an approach sap have termed dynamic tiering 28 column oriented systems store all data for a single column in the same location rather than storing all data for a single row in the same location row oriented systems this can enable performance improvements for olap queries on large datasets and allows greater vertical compression of similar types of data in a single column if the read times for column stored data is fast enough consolidated views of the data can be performed on the fly removing the need for maintaining aggregate views and its associated data redundancy 29 although row oriented systems have traditionally been favored for oltp in memory storage opens techniques to develop hybrid systems suitable for both olap and oltp capabilities 30 removing the need to maintain separate systems for oltp and olap operations indexer components the index server performs session management authorization transaction management and command processing the database has both a row store and a columnar store users can create tables using either store but the columnar store has more capabilities and is most frequently used citation needed the index server also manages persistence between cached memory images of database objects log files and permanent storage files the xs engine allows web applications to be built 31 sap hana information modeling also known as sap hana data modeling is a part of hana application development modeling is the methodology to expose operational data to the end user reusable virtual objects named calculation views are used in the modelling process mvcc edit sap hana manages concurrency through the use of multiversion concurrency control mvcc which gives every transaction a snapshot of the database at a point in time when an mvcc database needs to update an item of data it will not overwrite the old data with new data but will instead mark the old data as obsolete and add the newer version 32 33 streaming and data virtualization edit data virtualization is available via a tool named smart data access 34 streaming data for example from internet of things devices is available via a tool named smart data streaming 35 dedicated streaming analytics predictive analytics can be employed against data ingested by smart data streaming 36 big data edit in a scale out environment hana can support volumes of up to a petabyte of data in memory while returning query results in under a second 37 in order to balance the tradeoff of the cost of large in memory systems notably the cost of ram versus solid state or disk based hard drives with performance hana has capabilities to manage data tiering i e offloading less frequently accessed data to disk based storage hana s data lifecycle management is a data administration feature that allows database administrators to define rules for when records in a table should be offloaded from memory to either a disk based column store on the same hana server i e warm data storage or to offload data from memory or disk to a separate hadoop server i e cold data storage 38 sap offers a separate but related product referred to as vora for tight integration of big data stored in hadoop with enterprise data in hana vora leverages some of the same concepts from hana namely in memory storage query pushdown and massive parallelization 39 analytics edit sap hana includes a number of analytic engines for various kinds of data processing the business function library includes a number of algorithms made available to address common business data processing algorithms such as asset depreciation rolling forecast and moving average 40 the predictive analytics library includes native algorithms for calculating common statistical measures in areas such as clustering classification and time series analysis 41 hana incorporates the open source statistical programming language r as a supported language within stored procedures 42 the column store database offers graph database capabilities the graph engine supports the cypher query language as well as a visual graph manipulation via a tool called graph viewer graph data structures are stored directly in relational tables in hana s column store 43 pre built algorithms in the graph engine include pattern matching neighborhood search single shortest path and strongly connected components use cases for the graph engine include things like supply chain traceability fraud detection and logistics and route planning 44 hana also includes a spatial database engine which supports spatial data types and sql extensions for crud operations on spatial data hana is certified by the open geospatial consortium 45 and integrates with esri s arcgis geographic information system 46 in addition to numerical and statistical algorithms hana can perform text analytics and enterprise text search hana s search capability is based on fuzzy fault tolerant search much like modern web based search engines results include a statistical measure for how relevant search results are and search criteria can include a threshold of accuracy for results 47 analyses available include identifying entities such as people dates places organizations requests problems and more such entity extraction can be catered to specific use cases such as voice of the customer customer s preferences and expectations enterprise i e mergers an acquisitions products organizations and public sector public persons events organizations 48 custom extraction and dictionaries can also be implemented posted by lauraiz 0 comments older posts subscribe to posts atom rss feed search for optional tutorials step 2 of 2 paste the code into the website place the below html code into your own website place the code where you would like to the click to chat text link to appear you can modify the text that is displayed by modifying the html code below manually need some extra help visit our integration help site for plugins information and more live chat software tutorials blog archive 2013 1 may 1 oracle vs sap hana basics 2012 10 january 10 2011 22 december 12 september 1 august 2 june 1 may 1 april 2 march 2 february 1 2010 301 november 1 october 1 september 5 august 4 july 16 june 69 may 67 april 78 march 31 february 7 january 22 2009 74 december 5 november 13 october 22 september 9 august 13 july 10 june 2 alexa traffic rank disclaimer this blog is a personal blog written and edited by me the compensation received may influence the advertising content topics or posts made in this blog that content advertising space or post may not always be identified as paid or sponsored content the owner s of this blog is compensated to provide opinion on products services websites and various other topics even though the owner s of this blog receives compensation for our posts or advertisements we always give our honest opinions findings beliefs or experiences on those topics or 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