4 Best Apache ETL Tools in 2023
Are you confused about which Apache ETL tools to use? There are a wide variety of Apache ETL tools available in the market today. Apache has been one of the most trustworthy and reliable providers of these tools that you can trust your data with.
Table of Contents
This article will walk you through the 4 best Apache ETL tools in the market. These 4 Apache ETL tools include Apache NiFi, Apache StreamSets, Apache Airflow, and Apache Kafka. Let’s dive deep into these Apache ETL tools.
Table of Contents
- What are Apache ETL Tools?
- 4 Best Apache ETL Tools
What are Apache ETL Tools?
It is critical to choose the best ETL tool for your company. ELT extracts data from a source, transforms it to meet requirements, and then puts the modified data into a database, data warehouse, or business intelligence platform. There are a large number of ETL tools in the market.
Apache is one of the popular Web Server Software. Apache is free open-source software developed and maintained by the Apache Software Foundation. It is installed on 67 percent of all webservers on the planet. Apache Software Foundation has developed numerous ETL tools as well that can benefit companies. This article will walk you through some of the popular Apache ETL tools that have gained significant market share and can definitely benefit any company to achieve its goals.
To know more about Apache ETL tools, visit this link.
4 Best Apache ETL Tools
Apache ETL tools have gained wide acceptance in the market worldwide. Few of the popular Apache ETL tools include:
Scale your Data Integration effortlessly with Hevo’s Fault-Tolerant No Code Data Pipeline
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.Get started for Free with Hevo
With Hevo, fuel your analytics by not just loading data into Warehouse but also enriching it with in-built no-code transformations. Its fault-tolerant architecture ensures that the data is handled in a secure, consistent manner with zero data loss.
Check out what makes Hevo amazing:
- Near Real-Time Replication: Get access to near real-time replication on All Plans. Near Real-time via pipeline prioritization for Database Sources. For SaaS Sources, near real-time replication depend on API call limits.
- In-built Transformations: Format your data on the fly with Hevo’s preload transformations using either the drag-and-drop interface or our nifty python interface. Generate analysis-ready data in your warehouse using Hevo’s Postload Transformation.
- Monitoring and Observability: Monitor pipeline health with intuitive dashboards that reveal every stat of pipeline and data flow. Bring real-time visibility into your ETL with Alerts and Activity Logs.
- Reliability at Scale: With Hevo, you get a world-class fault-tolerant architecture that scales with zero data loss and low latency.
- 24×7 Customer Support: With Hevo you get more than just a platform, you get a partner for your pipelines. Discover peace with round-the-clock “Live Chat” within the platform. What’s more, you get 24×7 support even during the 14-day free trial.
Hevo provides Transparent Pricing to bring complete visibility to your ETL spend.
Stay in control with spend alerts and configurable credit limits for unforeseen spikes in the data flow.Sign up here for a 14-Day Free Trial!
1) Apache Nifi
Apache NiFi is an open-source ETL tool and is free for use. It allows you to visually assemble programs from boxes and run them without writing code. So, it is ideal for anyone without a background in coding. It can work with numerous different sources, including RabbitMQ, JDBC query, Hadoop, MQTT, UDP socket, etc. You can use it to filter, adjust, join, split, enhance, and verify data.
Apache NiFi lets you create long-running jobs and is suitable to process both streaming data and periodic batches. Manually managed jobs are also a possibility. However, you may face a few difficulties while setting them up.
It is not limited to data in CSV format. You can easily process photos, videos, audio, and binary data. Another great feature it provides is being able to use different queue policies (FIFO, LIFO, and others). Data Provenance is a connected service that records almost everything in your dataflows. It’s very convenient because you can see how the data was saved or performed. The only drawback is that the function requires lots of disk space.
However, one of the biggest drawbacks is the absence of live monitoring and per-record statistics.
2) Apache StreamSets
Apache StreamSets is a very strong competitor for Apache NiFi, being a free tool as well. It’s difficult to identify the better Apache ETL tools between the two. The data that is put into StreamSets is automatically converted into exchangeable records. Unlike Apache Nifi, StreamSets does not show queues between processors. In order to be able to utilize different formats, Apache Nifi requires turning from one version of the processor to another whereas StreamSets avoids these manipulations. This lets you stop only one processor instead of the whole data flow to change the settings. Debugging in StreamSets is easier than in NiFi due to the real-time debugging tool. It also has a more user-friendly interface.
StreamSets checks each processor before you are able to run the data flow. StreamSets does not allow you to leave disconnected processors for fixing bugs in the future.
In StreamSets, each processor has individual per-record statistics with nice visualization for effective debugging.
3) Apache Airflow
Airflow is a modern platform used to design, create and track workflows is an open-source ETL software. It can be integrated with cloud services, including GCP, Azure, and AWS. It has a user-friendly interface for clear visualization. It can be scaled up easily due to its modular design. The code is written in Python, but you won’t have to worry about XML or drag-and-drop GUIs.
Airflow was developed to act as a perfectly flexible task scheduler. However, its functionality doesn’t end here. It is also used in training ML models, sending notifications, tracking systems, and powering functions within various APIs. Even though Apache Airflow is adequate for most of the day-to-day operations (running ETL jobs and ML pipelines, delivering data, and completing DB backups), it is not the best choice to perform stream jobs.
It enables you to perform tasks on DAGs due to its modern UI, full of visualization elements. You will be able to see the running pipelines, track progress, and also fix bugs. The workflows are constant and stable, making them easily manageable.
One of the major drawbacks of Airflow is that it can be challenging to run alone. It is beneficial to use different operators.
4) Apache Kafka
Apache Kafka is an open-source distributed event streaming platform used by many companies to develop high-performance data pipelines, perform streaming analytics and data integration.
It is a distributed streaming platform that lets you publish and subscribe to streams of records (similar to a message queue). It also provides support for fault-tolerant storing of streams of records and enables the processing of these streams as they occur.
Typically, Kafka is used to building real-time streaming data pipelines that can either move data between systems or applications or even transform or react to the streams of data. The underlying concept of this project includes running a cluster on one or more servers, strong streams of records in categories, and working with records, where each record includes a key, a value, and a timestamp.
Benefits of using Kafka include reliability due to its fault-tolerant architecture. Moreover, it can be scaled easily without any downtime. Kafka uses a distributed commit log which implies that messages persist on disk as fast as possible, hence it is durable.
Kafka is most suitable for stream processing, log aggregation, and monitoring operational data.
All the ETL tools provided by Apache are open source, thus, your choice would depend mainly on your use case. It is important to understand the type of data you will be handling, whether you will require stream or batch processing, etc. It is important to find answers to these questions before finding the right Apache ETL tools.
Hevo Data lets you directly transfer data from 150+ Data Sources like Apache Kafka, Kafka Confluent Cloud straight to your Data Warehouse, Business Intelligence tools, or any other desired destination in a fully automated and secure manner without having to write any code and will provide you with a hassle-free experience.
Want to take Hevo for a spin? Sign up for a 14-day free trial and experience the feature-rich Hevo suite firsthand.
Share your thoughts about understanding Apache ETL tools in the comments section below.