Table of Contents
- Working knowledge of SaaS applications.
- Working knowledge of Open-Source and Cloud Environments.
What is the ETL Process?
The ETL process consists of 3 steps:
- Extraction: Extraction is an essential part of the ETL process as it helps unify Structured and Unstructured data from a diverse set of data sources such as Databases, SaaS applications, files, CRMs, etc.
Extraction Tools simplify this process by allowing users to extract valuable information in a matter of a few clicks. All this is done without having to write any complex code.
- Transformation: Transformation is the process of converting the extracted data into a common format so that it can be better understood by a Data Warehouse or a BI (Business Intelligence) tool. Some transformation techniques include Sorting, Cleaning, Removing Redundant Information, and Verifying Data from data sources.
- Loading: Loading is the process of storing the transformed data into a destination, normally a Data Warehouse, and also supports analysis of the data using various BI tools to gain valuable insights and build reports and dashboards. The Loading stage is crucial as the customer data is visualized using different BI tools after this stage.
The given figure highlights the stages of the ETL process:
As the ability of businesses to collect data explodes, data teams have a crucial role to play in fueling data-driven decisions. Yet, they struggle to consolidate the scattered data in their warehouse to build a single source of truth. Broken pipelines, data quality issues, bugs and errors, and lack of control and visibility over the data flow make data integration a nightmare.
1000+ data teams rely on Hevo’s Data Pipeline Platform to integrate data from over 150+ sources in a matter of minutes. Billions of data events from sources as varied as SaaS apps, Databases, File Storage and Streaming sources can be replicated in near real-time with Hevo’s fault-tolerant architecture.
Check out what makes Hevo amazing:
- Reliability at Scale – With Hevo, you get a world-class fault-tolerant architecture that scales with zero data loss and low latency.
- Monitoring and Observability – Monitor pipeline health with intuitive dashboards that reveal every stat of the pipeline and data flow. Bring real-time visibility into your ELT with Alerts and Activity Logs.
- Auto-Schema Management – Correcting improper schema after the data is loaded into your warehouse is challenging. Hevo automatically maps source schema with the destination warehouse so that you don’t face the pain of schema errors.
- Transparent Pricing – Say goodbye to complex and hidden pricing models. Hevo’s Transparent Pricing brings complete visibility to your ELT spending. Choose a plan based on your business needs. Stay in control with spend alerts and configurable credit limits for unforeseen spikes in data flow.
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What is Node.js?
To learn more about Node.js, click this link.
Nextract is an ETL Tool built on Node.js Streams and is designed by Github contributor Chad Auld. It is suited for beginner and mid-level programmers.
The main goal of Nextract is to help developers make their work easier by using the flexible and asynchronous nature of the Node.js runtime environment as compared to other Java-based ETL Tools.
It can extract data from database queries and reflect the results onto tables. It works best with CSV and JSON files and by adding plug-ins, you can perform additional ETL operations like Sorting, Filtering, and Math.
The only limitation of Nextract is that it cannot work with Big Data as it runs on the resources of a single machine.
Datapumps supports ETL processes such as Data Transformation, Encapsulation, Error Handling & Debugging. One limitation of Datapumps is that they cannot perform the ETL processes on their own and can only pass data in a controlled manner.
To make it efficient you can add “mixins”. Mixins help import, export, and transfer your data. Currently, Datapumps support 10 types of mixins.
Empujar is a NodeJs Open Source ETL Tool that helps extract data and perform backup operations. It is developed by TaskRabbit and takes advantage of Node.js’s asynchronous behavior to run data operations in series or parallel.
It uses a Book, Chapter, and Page format to represent data. Top-level objects are known as Books and they contain sequential Chapters with Pages that can run in parallel up to a limit that you can set.
This tool integrates with different types of databases including MySQL, FTP, S3, Amazon Redshift, and many more.
Extraload is a lightweight ETL Tool for Node.js that moves data from files into databases and between databases. It was developed by Github contributor Alyaton Norgard.
This tool also houses API reference pages that explain how to write scripts and create drivers.
As these tools are work-in-progress tools many of them are not fully developed and are not compatible with multiple data sources. Some of the limitations of these tools include:
- Enterprise Application Connectivity: Companies are not able to connect a few of their applications with NodeJs Open Source ETL Tools due to compatibility reasons.
- Management & Error Handling Capabilities: Many Open-Source ETL Tools are not able to handle errors easily due to their lack of error-handling capabilities.
- Large Data Volumes & Small Batch Windows: Many NodeJs Open Source ETL Tools need to analyze large data volumes but can process the data in small batches only. This is because many of these tools are Command-Line Interfaces and need both the power of Node.js and the ETL tool to function effectively.
- Complex Transformation Requirements: Companies that have complex transformation needs cannot use NodeJs Open Source ETL Tools. This is because they often lack support for performing complex transformations.
- Lack of Customer Support Teams: As Open-Source ETL Tools are managed by communities and developers all around the world, they do not have specific customer support teams to handle issues.
- Poor Security Features: Being Open-Source causes these tools to have poor security infrastructure and become prone to many cyber attacks.
In case you want to integrate data into your desired Database/destination, then Hevo Data is the right choice for you! It will help simplify the ETL and management process of both the data sources and the data destinations.
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