When should I use Hadoop vs data warehouse?

If you have clean, consistent and high-quality data then you should go for Data Warehouse because Hadoop lacks data quality in some of its solutions. If you have Raw Unstructured Data, then you should go for Hadoop because Hadoop works well with unstructured/raw data but Data Warehouse works only with structured data.

Will Hadoop replace SQL?

Hadoop runs code across a cluster of computers and performs offline batch processing for huge data sets across the cluster of commodity servers. However, Hadoop is not a replacement for SQL rather their use depends on individual requirements.

Will big data replace data warehouse?

As evident from the important differences between big data and data warehouse, they are not the same and therefore not interchangeable. Therefore big data solution will not replace data warehouse.

What is Hadoop and how does it work?

Every machine in a cluster both stores and processes data. Hadoop stores the data to disks using HDFS. The software offers seamless scalability options. You can start with as low as one machine and then expand to thousands, adding any type of enterprise or commodity hardware. The Hadoop ecosystem is highly fault-tolerant.

Which open source big data processing framework should you use?

Two of the most popular big data processing frameworks in use today are open source – Apache Hadoop and Apache Spark. There is always a question about which framework to use, Hadoop, or Spark.

How many machines do you need for Hadoop?

You can start with as low as one machine and then expand to thousands, adding any type of enterprise or commodity hardware. The Hadoop ecosystem is highly fault-tolerant. Hadoop does not depend on hardware to achieve high availability. At its core, Hadoop is built to look for failures at the application layer.

What is HDFS file system in Hadoop?

HDFS – Hadoop Distributed File System. This is the file system that manages the storage of large sets of data across a Hadoop cluster. HDFS can handle both structured and unstructured data. The storage hardware can range from any consumer-grade HDDs to enterprise drives.