Skip to main content

5 Different Bigdata Storage Patterns

Data is now more than just plain text, it can exist in various persistence-storage mechanisms, with Hadoop distributed file system (HDFS) being one of them. The way data is ingested or the sources from which data is ingested affects the way data is stored. On the other hand, how the data is pushed further into the downstream systems or accessed by the data access layer decides how the data is to be stored.

The need to store huge volumes of data has forced databases to follow new rules of data relationships and integrity that are different from those of relational database management systems (RDBMS). RDBMS follow the ACID rules of atomicity, consistency, isolation and durability. These rules make the database reliable to any user of the database. However, searching huge volumes of big data and retrieving data from them would take large amounts of time if all the ACID rules were enforced.
NoSQL Databases
NoSQL Databases

A typical scenario is when we search for a certain topic using Google. The search returns innumerable pages of data; however, only one page is visible or basically available (BA). The rest of the data is in a soft state (S) and is still being assembled by Google, though the user is not aware of it. By the time the user looks at the data on the first page, the rest of the data becomes eventually consistent (E). This phenomenon—basically available soft state and eventually consistent—is the rule followed by the big data databases, which are generally NoSQL databases following BASE properties.

Database theory suggests that any distributed NoSQL big database can satisfy only two properties predominantly and will have to relax standards on the third. The three properties are consistency, availability, and partition tolerance (CAP). This is the CAP theorem.

  • Polyglot pattern: Multiple types of storage mechanisms—like RDBMS, file storage, CMS, OODBMS, NoSQL and HDFS—co-exist in an enterprise to solve the big data problem.
  • The aforementioned paradigms of ACID, BASE, and CAP give rise to new big data storage patterns like below:
  • Façade pattern: HDFS serves as the intermittent Façade for the traditional DW systems.
  • Lean pattern: HBase is indexed using only one column-family and only one column and unique row-key.
  • NoSQL pattern: Traditional RDBMS systems are replaced by NoSQL alternatives to facilitate faster access and querying of big data.

Comments

Popular posts from this blog

Top 20 ultimate ETL Questions really good for interviews

How to print/display the first line of a file?  there are many ways to do this. However the easiest way to display the first line of a file is using the [head] command.  $> head -1 file. Txt no prize in guessing that if you specify [head -2] then it would print first 2 records of the file.  another way can be by using [sed] command. [sed] is a very powerful text editor which can be used for various text manipulation purposes like this.  $> sed '2,$ d' file. Txt how does the above command work?  The 'd' parameter basically tells [sed] to delete all the records from display from line 2 to last line of the file (last line is represented by $ symbol). Of course it does not actually delete those lines from the file, it just does not display those lines in standard output screen. So you only see the remaining line which is the 1st line.  how to print/display the last line of a file?  the easiest way is to use the [tail] command.  $> tail -1 file. Txt if you want to do it using…

The unique helpful SAN architecture simplified one

Storage Area Networks (SANs)

A SAN is connected behind the servers. SANs provide block-level access to shared data storage. Block level access refers to the specific blocks of data on a storage device as opposed to file level access. One file will contain several blocks. 

SANs provide high availability and robust business continuity for critical data environments. SANs are typically switched fabric architectures using Fibre Channel (FC) for connectivity. The term switched fabric refers to each storage unit being connected to each server via multiple SAN switches also called SAN directors which provide redundancy within the paths to the storage units. This provides additional paths for communications and eliminates one central switch as a single point of failure.Ethernet has many advantages similar to Fibre Channel for supporting SANs. Some of these include high speed, support of a switched fabric topology, widespread interoperability, and a large set of management tools. In a storage ne…

Four Tableau products a quick review and explanation

I want to share you what are the Products most popular.

Total four products. Read the details below.

Tableau desktop-(Business analytics anyone can use) - Tableau  Desktop  is  based  on  breakthrough technology  from  Stanford  University  that  lets  you drag & drop to analyze data. You can connect to  data in a few clicks, then visualize and create interactive dashboards with a few more.

We’ve done years of research to build a system that supports people’s natural  ability  to  think visually. Shift fluidly between views, following your natural train of thought. You’re not stuck in wizards or bogged down writing scripts. You just create beautiful, rich data visualizations.  It's so easy to use that any Excel user can learn it. Get more results for less effort. And it’s 10 –100x faster than existing solutions.

Tableau server
Tableau  Server  is  a  business  intelligence  application  that  provides  browser-based  analytics anyone can use. It’s a rapid-fire alternative to th…