A lot of things have been changing in the data processing industry. We have also been hearing the talks that the ETL is probably dead and Apache Kafka is becoming the future of data processing. There have been enough talks and statements that support the fact that Kafka can provide a flexible and uniform framework that supports modern requirements.
In this blog we will discuss how Kafka has taken over the entire data processing bandwidth and is shining bright as the future of data processing.
Old ETL architecture and recent trends
Data and data systems have changed dramatically over the past decade. The old world consisted of operational databases providing online transaction processing and online analytical processing. Data was typically batch-loaded into a master schema. This process is commonly referred to as ETL (Extraction-transform-load).
Recent trends are creating dramatic changes in the old world architecture:
- Single-server databases are replaced by a myriad of distributed data platforms.
- There are many types of data sources other than transactional data like logs, metrics etc.
- There is an increasing need for faster processing than daily batches.
Traditional approaches to data integration often look like a big mess. Lets now understand few drawbacks of ETL:
- There is a need for a global schema.
- Data cleansing and curation is a manually done process and often leads to errors.
- The operational cost of ETL is high and often slow and time-consuming.
- ETL tools were specifically designed to focus on connecting databases and data warehouses in a batch manner.
Enterprise Application Integration (EAI)
It was an early take on real-time ETL, and used for data integration. However, these technologies could often not scale to the desired magnitude. It creates a confusion: real-time but not scalable or scalable but batch.
Understanding the new requirements that the modern world for data integration has to offer:
- Capabilities of processing high volume data.
- The platform should be supportive of real-time data and should have event-centric thinking.
- Forward-compatible data architectures need to be enabled and also support the ability to add more applications.
Need for Apache Kafka
Apache Kafka was developed some seven years ago within LinkedIn. It is an open-source streaming platform and can operate as the central nervous system for an organization’s data in these ways:
- It works as the real-time scalable messaging bus for applications with no EAI.
- It serves as a source-of-truth pipeline
- As the building blocks of stream-processing microservices.
Apache Kafka processes 14 million messages a day and is being deployed by thousands of organizations, including fortune 500 companies like Cisco, Netflix, Paypal, Verizon and many more. Kafka is rapidly becoming the first choice for streaming data.
Kafka enables the building of streaming data pipelines- the extraction and Load through Kafka connects API. The connect API utilizes Kafka for scalability, it is built upon the fault-tolerant model of Kafka and offers a uniform method to monitor all the connectors. Stream processing and transformations are implemented with the help of Kafka stream API- The transform in ETL. Using Kafka as a streaming platform can eliminate the need of duplicate ETL components for each system.
The event-driven microservices vision being implemented by the Kafka stream API makes stream processing accessible for any use case.
Kafka stream API provides a DSL with operators like map, filter, and window aggregates. There is no micro-batching and it also uses a dataflow style windowing approach to handle the data that arrives late. It also supports fast stateful and fault-tolerant processing and also streams processing which is very useful when upgrading applications or migrating data.
Also, logs unify batch and stream processing. A log can be consumed by either batch windows or in real-time.
Ksolves Apache Kafka Services
Now you have understood why the ETL may be the thing of the past and Apache Kafka is the shiny new future of data processing. Let us tell you about why you need Ksolves. Being an Apache Kafka development company, we understand your requirements and are always ready with the best-suited solutions. Our Kafka developers are highly qualified and experienced to provide you the best data processing experience. If you are still confused on what to choose for your data processing needs, give us a call and let’s discuss in detail.