Expert Q&A on Database Management in the Times of Big Data

Any business establishment, big or small, works well now by data-based insights. Data and information act as the critical resources now regarding business administration, which helps you to understand the target audience, their preferences, and the target market trends. Big data is the new technology, which can change the fate your business irrespective of being small or big.

The role of big data

As per the experts at remoteDba.com, big data combines many processes and tools regarding managing a massive amount of data sets and processing them into tangible business insights. Big Data is born with the objective of understanding the customer philosophy, market trends, changing preferences, and upcoming patterns based on the vast database produced while people interact with various systems.

Big Data effectively incorporates analytics to figure out most valuable customers and to help businesses to offer their customers an individually satisfying experience through products and services. However, there are a lot of doubts people have about big data implementation, let’s discuss a few random questions here.

Big data Q&A

Q: How one should choose the best big data database technologies based on their environment?

As a whole, big data has many meanings, but when it comes to storage, it’s all about volume. You have first to decide the volume; however, the storage with big data can be more than the conventional relational storage. There are a large number of providers offering database technologies, which are advanced when compared to the conventional RDBMS approach, and column-oriented DB is an example.

There are also NoSQL technologies like HBase or Cassandra which are specifically created for big data. These DBs can support the clusters with hundreds of servers with terabytes or petabytes of storage volume.

Q: Is it hard to integrate the existing DB infrastructure to new big data compliant technologies?

It is true to the extent that the non-traditional databases may be a bit difficult to integrate. However, there are ways to do this task efficiently by considering your operational aspects. DevOps and SysOps in many of the organizations have experience in handling monolithic relational database. Handling distributed databases like HBase and Cassandra is another challenge.

However, these challenges are not insoluble but just needed to be planned accordingly. Open-source NoSQL databases are not instant replacements for the new-age relational database management systems, so it requires a bit of learning, operational compliances, and customized implementation.

Q: What are appropriate messaging systems available to work well with big data?

Even though there are some systems, the two major systems which are proven to be most successful are Kafka and RabbitMQ. Kafka is highly scalable and also features a distributed system which can accommodate well even if the queue is so massive to fit in the memory. RabbitMQ can scale horizontally with multiple queues fitting into the memory. NSQ is also another promising open source messaging system.

With the need for real-time data processing regarding big data, you need to be so careful regarding database adoption, planning, implementation, and monitoring to ensure the most streamlined analytical output for better business administration.

 

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