Best 13 Data Ingestion Open Source Tools in 2024

Extracting data from multiple sources in real time is still a challenging task for several firms. Data Ingestion Open Source Tools simplifies this process by automatically ingesting data from several sources and loading it directly to your desired destination.

Being Open Source, these solutions are an economical choice for businesses that not eliminate human errors but also allow your Engineering team focuses their efforts on core objectives rather than creating & fixing up pipelines. In this article, you will learn about the Top Data Ingestion Open Source Tools available and how they can assist you in simplifying your Data Integration process.    

What are Data Ingestion Tools?

With the growing demand for real-time data in business intelligence, organizations need solutions that seamlessly extract data from many sources and integrate them. However, manually creating and managing data ingestion pipelines is a time-consuming and resource-intensive task that may lead to inaccurate reports and potentially misleading analytics conclusions.

Data Ingestion Open Source tools eliminate the need for individually building pipelines and simplify this process by automatically extracting data from multiple sources and inserting it into the desired destination. Apart from being an economical solution, these Data Ingestion Open Source tools can also help you process, modify, and format your data to properly fit your target system schema.

Key Features of Data Ingestion Tools

Data Ingestion Tools offers the following salient features:

• Enhanced Performance: With little to no time & effort spent on setting up and maintaining pipelines, Data Ingestion Open-Source tools completely manages the whole process efficiently.
• Scalability: As a business grows, bo the number of data sources & the data volume increases at an exponential rate. Real-time Data Ingestion Tools ensure that they easily scale on-demand and can effectively handle fluctuating workloads.
• Free: Acting as an economical solution, Data Ingestion Open Source Tools allows you to customize the pipelines according to your business needs.  
• Data Transformation: You can also perform data formatting, data cleaning & data profiling operations using the Real-time data ingestion tools. Acting as a one-stop solution for data transformation processes, Real-time data ingestion tools help you save a lot of time in data analytics by proving analysis-ready data. 
• User Friendly: Most Real-time Data Ingestion Tools provide a user-friendly interface that allows any beginner to quickly get started with their first data ingestion pipeline. This also eliminates the need for expert technical knowledge, allowing data analysts to initiate a data ingestion pipeline by selecting the data source and the destination.
• Better Data Management: With minimal manual intervention during the data transfer process, Real-time Data Ingestion tools maintain data quality and reduce any inaccuracies or redundancies.

What are the benefits of leveraging Data Ingestion Tools for Businesses?

Building a scalable custom Data Ingestion platform requires you to assign a portion of engineering bandwidth that has to continuously monitor the pipeline. You also need to ensure that your solution is scalable. You have to invest heavily in buying and maintaining infrastructure as well. Lastly, you are also required to have comprehensive documentation and proper knowledge transfer to eliminate any dependencies. Though, you can eliminate all these obstacles by employing the Data Ingestion Open Source Tools and leveraging the following benefits:

• Data Ingestion Open Source tools establish a framework for businesses that allows them to collect, transfer, integrate, & process data from multiple sources.
• Without worrying about building & managing the ever-evolving data connector, Data Ingestion Open Source Tools provides a seamless data extraction process with complete support for several data transport protocols.
• Along with data collection, integration & processing, Data Ingestion Open Source tools also have data modification & formatting capabilities to facilitate analytics. You can either start the data ingestion process in batches(small chunks of data) or stream it in real-time.   
• By using Data Ingestion Open Source Tools, you can ingest data rapidly and deliver data to your targets at the lowest level of latency. It also allows you to scale the framework to handle large datasets and achieve fast in-memory transaction processing. 

Leveraging Hevo Data for Your Data Ingestion Needs

Hevo provides an Automated No-code Data Pipeline that assists you in ingesting data in real-time from 150+ data sources but also enriching the data and transforming it into an analysis-ready form without having to write a single line of code. Its fault-tolerant architecture ensures that the data is handled in a secure, consistent manner with zero data loss. Adding to its flexibility, Hevo provides several Data Ingestion Modes such as Change Tracking, Table, Binary Logging, Custom SQL, Oplog, etc. 

Hevo’s fault-tolerant architecture will enrich and transform your data securely and consistently and load it to your destination without any assistance from your side. You can entrust us with your data transfer process by both ETL and ELT processes to a data warehouse, Reverse ETL processes to CRMs, etc and enjoy a hassle-free experience.

Here are more reasons to try Hevo:

• Smooth Schema Management: Hevo takes away the tedious task of schema management & automatically detects the schema of incoming data and maps it to your schema in the desired Data Warehouse.
• Exceptional Data Transformations: Best-in-class & Native Support for Complex Data Transformation at fingertips. Code & No-code Flexibility is designed for everyone.
• Quick Setup: Hevo with its automated features, can be set up in minimal time. Moreover, with its simple and interactive UI, it is extremely easy for new customers to work on and perform operations.

Sign up here for a 14-Day Free Trial!

Best Data Ingestion Open Source Tools

1. Apache Kafka

Apache Kafka is one of the Popular Distributed Stream Real-time Data Ingestion Open Source Tools & Processing platforms. Providing an end-to-end solution to its users, Kafka can efficiently read & write streams of events in Real-time with constant import/export of your data from other data systems. 

Its reliability & durability allows you to store streams of data securely for as long as you want. With its Best-in-Class performance, Low latency, Fault Tolerance, and High Throughput, Kafka can handle & process thousands of messages per second in Real-time. 

Launched as an Open Source Messaging Queue System by LinkedIn in 2011, Kafka has now evolved into a Full-Fledged Event Streaming Platform.  Among other Real-time Data Ingestion Tools, it is an excellent choice for building Real-time Streaming Data Pipelines and Applications that adapt to the Data Streams. You can easily Install Kafka on Mac, Windows, or Linux OS. Adding to its Flexibility, Kafka works for both Online & Offline Message Consumption.

2. Apache Storm

Apache Storm is a distributed Data Ingestion Open Source framework based on Clojure and Java programming languages.  It provides a scalable & fault-tolerant platform, thereby ensuring reliable delivery. You get best-in-class performance with Storm as it can effectively handle 1 million tuples per second on each node. Apache Storm is applicable in several scenarios such as real-time analytics, online machine learning, continuous computation, distributed RPC, ETL, and more. 

3. Apache Nifi

Apache Nifi is one of the popular Data Ingestion Open Source Tools for distributing and processing data with support for data routing and transformation. It is an integration, automation tool to perform data ingestion at a faster pace. Compared to other Data Ingestion Open Source Tools, Apache Nifi uses a robust system that processes and distributes the data over several resources. You can work with Apache NiFi in both standalone mode and cluster mode. 

It allows you to get incoming messages, filters, and formats using several processors. Most of all, Apache Nifi is fault-tolerant, leverages automation, manages the flow of information between systems, and promotes data lineage, security, and scalability

4. Airbyte

AirByte is a Data Ingestion Open Source Tool built to assist organizations with quickly getting started with a data ingestion pipeline in a short period of time. It comes with access to over 120 data connectors with a CDK (Cloud Development Kit) that allows you to create your custom connectors.

In addition, Airbyte offers log-based incremental replication capabilities that allow users to keep their data up-to-date. To cater to all your data needs, Airbyte facilitates access to raw data (for engineers) and normalized data (for analysts). You can also execute custom data transformations using any of the selected dbt transformation models.

5. Apache Flume

Similar to Apache Kafka, Apache Flume is one of Apache’s Big Data Ingestion Open Source tools. It is primarily intended to bring data into the Hadoop distributed file system(HDFS). 

 By employing this tool, you can easily extract, combine, and load large amounts of streaming data from a vast sea of data sources into HDFS. Apache Flume is primarily used to load log data into Hadoop, but it also supports other frameworks such as Hbase and Solr. 

Apache Flume offers simplicity, robustness, and fault tolerance with its adjustable reliability mechanism. It also provides multiple failover and recovery capabilities.

6. Elastic Logstash

Elastic Logstash is an open-source data processing pipeline that allows you to extract data from multiple sources and transfer it to your desired target system. These data sources include logs, metrics, web applications, data stores, and various AWS services.

No matter the data format or complexity, Logstash can transform or parse your data on the fly. Compared to other Data Ingestion Open Source Tools, Elastic Logstash can derive structure from unstructured data with grok, decipher geo coordinates from IP addresses, anonymize or exclude sensitive fields, and ease overall processing.

7. Amazon Kinesis

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It is a cloud-based data ingestion software. It enables the capturing, storing, and processing of data in real-time through its Kinesis data stream. It is used in various applications such as IoT devices, sensors, web applications, etc. Amazon Kinesis can capture and run data on the scale of terabytes per hour from various sources. The information is then loaded to Amazon Warehouse Services which stores data with Kinesis Data Firehose. 

8. Dropbase

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It is a platform that can ingest data from diverse sources, including CSV and Excel files. It has the ability to convert offline data into live databases. You can edit, delete, rearrange, or add data to your databases. To import data in the SQL database from the spreadsheet, you can follow the below steps:

• Select the table you want to ingest, define the primary key, and validation checks for the columns you require to export. 
• Now you can edit, add, and import data by using a spreadsheet-like interface. You can also collaborate with your team members to do so. 
• You can sync the changes you have made after resolving all the conflicts between staging and production. 

Using its data ingestion framework open source you can efficiently perform data ingestion and transformation. 

9. Integrate.io

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With a drag-and-drop interface, this data ingestion tool provides connectivity with nearly 100 connectors to enable data ingestion. It is a cloud-based, no-code, and fast data change capture tool. It automates data transformation, reducing the need for manual intervention. It is a data pipeline that allows users to maintain APIs directly on its platform, which can then be connected to systems and applications present already. It is one of the prominent data ingestion tools open source used to carry out the ETL process seamlessly. 

10. Matillion 

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It is one of the open source data ingestion tools that is useful for SMBs who wish to migrate data from current databases to cloud-based databases. An ETL tool with more than 70 connectors, Matillion helps you move, transform, and analyze data in real time. Along with data ingestion and transformation, it offers other features such as data orchestration and visualization. In addition to this, it also offers advanced security and automates the tasks that are repetitive thereby reducing the effort required for the data ingestion process. 

11. Amazon Kinesis

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It is a cloud-based data ingestion software. It enables the capturing, storing, and processing of data in real-time through its Kinesis data stream. It is used in various applications such as IoT devices, sensors, web applications, etc. Amazon Kinesis can capture and run data on the scale of terabytes per hour from various sources. The information is then loaded to Amazon Warehouse Services which stores data with Kinesis Data Firehose. 

12. Dropbase

Image Source

It is a platform that can ingest data from diverse sources, including CSV and Excel files. It has the ability to convert offline data into live databases. You can edit, delete, rearrange, or add data to your databases. To import data in the SQL database from the spreadsheet, you can follow the below steps:

• Select the table you want to ingest, define the primary key, and validation checks for the columns you require to export. 
• Now you can edit, add, and import data by using a spreadsheet-like interface. You can also collaborate with your team members to do so. 
• You can sync the changes you have made after resolving all the conflicts between staging and production. 

Using its data ingestion framework open source you can efficiently perform data ingestion and transformation. 

13. Integrate.io

Source: Integrate.io

With a drag-and-drop interface, this data ingestion tool provides connectivity with nearly 100 connectors to enable data ingestion. It is a cloud-based, no-code, and fast data change capture tool. It automates data transformation, reducing the need for manual intervention. It is a data pipeline that allows users to maintain APIs directly on its platform, which can then be connected to systems and applications present already. It is one of the prominent data ingestion tools open source used to carry out the ETL process seamlessly. 

Conclusion

In this article, you have learned about the Best Data Ingestion Tools. Manually creating pipelines and monitoring the ever-changing data connectors is a resource-intensive task and requires constant effort from your Engineering team. To remedy this, you can employ Data Ingestion Open Source Tools that automatically extract data from your sources and seamlessly transfer it to your target system. This in turn reduces any human errors caused during the manual process and provides accurate data for creating your business reports. 

Though, these also require some technical knowledge for customizing your pipelines and for performing the simplest of the data transformations. Hence, these create potential bottlenecks as the business teams have to still wait on the Engineering teams for providing the data. You can streamline this process by opting for a Beginner Friendly Cloud Based No-Code Data Integration Platform like Hevo Data! 

Visit our Website to Explore Hevo

Hevo Data, a No-code Data Pipeline can Ingest Data in Real-Time from a vast sea of 150+ sources to a Data Warehouse, BI Tool, or a Destination of your choice. It is a reliable, completely automated, and secure service that doesn’t require you to write any code!  

If you are using CRMs, Sales, HR, and Marketing applications and searching for a no-fuss alternative to Manual Data Integration, then Hevo can effortlessly automate this for you. Hevo, with its strong integration with 150+ sources and BI tools(Including 40+ Free Sources), allows you to not only export & load data but also transform & enrich your data & make it analysis-ready in a jiffy.

Want to take Hevo for a ride? Sign Up for a 14-day free trial and simplify your Data Integration process. Do check out the pricing details to understand which plan fulfills all your business needs.

Share your experience of learning about the best Data Ingestion Open Source Tools! Let us know in the comments section below!