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Showing posts with the label data engineer career path

HBASE Vs. RDBMS Top Differences You can Unlock Now

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HBASE in the Big data context has a lot of benefits over RDBMS. The listed differences below make you understandable why HBASE is popular in Hadoop (or Bigdata) platform. Let us check one by one quickly. HBASE Vs. RDBMS Differences Random Accessing HBase handles a large amount of data that is store in a distributed manner in the column-oriented format while RDBMS is systematic storage of a database that cannot support a random manner for accessing the database. Database Rules RDBMS strictly follow Codd's 12 rules with fixed schemas and row-oriented manner of database and also follow ACID properties. HBase follows BASE properties and implement complex queries. Secondary indexes, complex inner and outer joins, count, sum, sort, group, and data of page and table can easily be accessible by RDBMS. Storage From small to medium storage application there is the use of RDBMS that provide the solution with MySQL and PostgreSQL whose size increase with concurrency and performance.  Codd'

5 Essential IT Skills for Data Engineers

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Data engineers need the following skills. These skills help you get nice job in any analytics company. Photo Credit: Srini Five Top Skills Need Skill-1 Experience working with big data tools such as MapReduce, Pig, Spark, Kafka and NoSQL data stores such as MongoDB, Cassandra, HBase, etc. Skill-2 Expertise in multi-structured data modeling, reporting on NoSQL & structured database technologies such as HBase and Cassandra, SQL. Skill-3 Experience with languages such as Python, Perl, Ruby, Java, Scala, R etc. Skill-4 Strong data & visual presentation skills and ability to explain insights using tools like tableau, D3 charts or other tools. Skill-5 Basic knowledge and experience of statistical analysis tools such as R.