In context of Big Data we know that it deals with large amount of data and its execution. So in nutshell we can say that Big data is something which deals with the large amount of data and as amount of data is so large then broadly there are three categories which are defined on the basis of how data is organized which are namely as Structured, Semi Structured and Unstructured Data.
Now the basis of level of organizing the data we can find out some more differences between all these three types of data which are as follow.
Following are the important differences between Structure and Union.
|Sr. No.||Key||Structured Data||Semi Structured Data||Unstructured Data|
|1||Level of organizing||Structured Data as name suggest this type of data is well organized and hence level of organizing is highest in this type of data.||On other hand in case of Semi Structured Data the data is organized up to some extent only and rest is non organized hence the level of organizing is less than that of Structured Data and higher than that of Unstructured Data.||In last the data is fully non organized in case of Unstructured Data and hence level of organizing is lowest in case of Unstructured Data.|
|2||Means of Data Organization||Structured Data is get organized by the means of Relational Database.||While in case of Semi Structured Data is partially organized by the means of XML/RDF.||On other hand in case of Unstructured Data data is based on simple character and binary data.|
|3||Transaction Management||In Structured Data management and concurrency of data is present and hence mostly preferred in multitasking process.||In Semi Structured Data transaction is not by default but is get adapted from DBMS but data concurrency is not present.||While in Unstructured Data no transaction management and no concurrency are present.|
|4||Versioning||As mentioned in definition Structured Data supports in Relational Database so versioning is done over tuples, rows and table as well.||On other hand in case of Semi Structured Data versioning is done only where tuples or graph is possible as partial database is supported in case of Semi Structured Data.||Versioning in case of Unstructured Data is possible only as on whole data as no support of database at all.|
|5||Flexible and Scalable||As Structured Data is based on relational database so it becomes schema dependent and less flexible as well as less scalable.||While in case Semi Structured Data data is more flexible than Structured Data but less flexible and scalable as compare to Unstructured Data.||As there is no dependency on any database so Unstructured Data is more flexible and scalable as compare to Structured and Semi Structured Data.|
|6||Performance||In Structure Data we can perform structured query which allow complex joining and thus performance is highest as compare to that of Semi Structured and Unstructured Data.||On other hand in case of Semi Structured Data only queries over anonymous nodes are possible so its performance is lower than Structured Data but more than that of Unstructured Data||While in case of Unstructured Data only textual query are possible so performance is lower than both Structured and Semi Structured Data.|