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ETL and Big data - both of them play vital roles while processing and analysing data. Although ETL and big data deal with the data for processing and analysis, they significantly differ in the methods and the types of data used.
A key difference is the type of data each approach was designed to deal with. The ETL process comes rather handy mostly for structured, well-defined data that needs to be extracted from a variety of sources whereas Big Data come quite handily used in unstructured, semi-structured and rapidly changing datasets.
The ways in which ETL and big data platforms rely on different technologies and architectures to function under the hood with big data. ETL often uses relational databases like RDBMS and data warehousing technologies, big data solutions mostly depend on distributed computing frameworks such as Hadoop and Spark and NoSQL databases. Click here if you want to learn more about ETL.
There is no silver bullet — ETL versus big data. That would depend on all the organisation specific and data specific scenarios.
ETL: ETL converts data from a source to an output structure.
Big Data: Big Data deals with unstructured, semi-structured and advance analytic datasets like Text documents, Images,Sensor logs etc.
ETL: ETL is designed to run in batch mode, which analyzes data in sets or batches, making it perfect for traditional data warehousing and business intelligence.
Big Data: Ideal for dealing with terabytes or petabytes of data and suitable for use cases such as processing data streams in real-time, or processing and analyzing large volumes of data efficiently.
ETL: Uses Relational Database Management Systems (RDBMS) and Data Warehousing Technologies.
Big Data: It is implemented with distributed computing frameworks, such as Hadoop, Spark, as well as NoSQL databases.
ETL: Usually works really well with structured data and medium-to-large volumes, but may not be fast processing large datasets.
Support for Big Data: Process large quantities of data in the terabytes to petabytes with high efficiency.
ETL: ETL follows a linear data pipeline with pre-defined batch-based transformations
Big Data: Here, it facilitates parallel processing with distributed systems which enables real-time data ingestion and transformation.
ETL: ETL may need extensive upfront investment in server-specific machines and databases.
Big Data: Big Data often utilises cloud computing and distributed storage (provide cheaper scaling for side application scale).
ETL: Harder to work with changing data in the inherent structure of the schema.
Big Data : More flexible which can handle ever new types of datasets and formats
The choice between ETL and big data isn’t a one-size-fits-all decision, as others suggest. It will depend on the uniqueness of an organisation or characteristics of data being processed by organisations.
There are organisations that have a more structured data, and focus on BI and reporting, which makes ETL the way to go. Here ELT-based plays its role, but in competitive market where data need to be high-quality, the consistency should not be compromised and reliably required by business partners can really get failure.
Organisations handling huge, complex, fast-changing sets of data might be more interested in big data while the opposite could be the case for small and medium ones. This way, big data could answer to the 3 Vs: Volume, Variety and Velocity of data.
In this data-driven world, more important than having the data is to be able to effectively manage and analyze complex, larger datasets if organisations want to have a competitive edge. To allow an organisation reach this ladder, two of the strongest actors they can rely on are ETL and big data but with each blossoming into its distinctive powers.
Organisations can completely maximise their data potential by leveraging the advantages of both ETL and Big data which enhances the decision making thereby achieving greater success. Start Your Free Trial for Trocco – Transform your Data into Actionable Insights with the power of ETL and Big Data Technologies in complete OneClick!
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