Table of Contents
  • Easy-to-use, no-code platform: Use the drag-and-drop editor to quickly and easily create a data pipeline.
  • Cost reduction: Automate the data ingestion process, reducing the need for manual intervention and extra data engineers.
  • ELT capabilities: Extract data from source systems, load it into a data warehouse, and then transform it into a format ready for analysis.
  • Reverse ETL functionality: Reverse the process of ETL by transforming data from a data warehouse into a format that can be used by source systems.
  • Data warehouse insights: Access insights into the data stored in a data warehouse.
  • Data observability: Monitor and analyze data in real-time, with up to three free alerts.
  • Fast Change Data Capture (CDC): Capture data changes quickly and accurately.
  • Enhanced data quality: Ensure your data is accurate and up-to-date.
  • More accurate data transformation: Automate your data transformation processes to ensure data is transformed accurately.

Data ingestion is an important component of any successful data initiative. It refers to the process of collecting data from multiple sources and loading it into another system.

Businesses most commonly use a subtype of data ingestion called ETL (extract, transform, load), which allows the data to be transformed before it's loaded.

This extra step provides many benefits. Most importantly, it allows organizations to automatically match and correlate data from a variety of different sources.

In this guide, we'll take a look at the top 11 data ingestion tools for 2024, covering their features, use cases, and what makes each one unique.

Here are five key takeaways from this guide about data ingestion tools:

  • Data ingestion tools import data from various sources to one target location. This location is often a data warehouse.
  • ETL (extract, transform, load) is a subtype of data ingestion. Through this process, data is extracted and cleaned up before being loaded in a warehouse.
  • Various data ingestion tools can complete the ETL process automatically. These tools include features such as pre-built integrations and even reverse ETL capabilities.
  • Some of the most popular ETL tools include Integrate.io, Airbyte, Matillion, Talend, and Wavefront.
  • Integrate.io is a no-code data pipeline platform that simplifies the ETL process.
  1. Integrate.io
  2. Airbyte
  3. Amazon Kinesis
  4. Matillion
  5. Apache NiFi
  6. Apache Kafka
  7. Talend
  8. Dropbase
  9. Wavefront
  10. Apache Flume
  11. Precisely Connect

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1. Integrate.io

Rating: 4.3/5.0 (G2)

Integrate.io is a cloud-based data pipeline platform that enables businesses to connect multiple data sources to extract, transform, and load data to a data warehouse or other destinations.

The platform features a user-friendly, drag-and-drop workflow builder, a powerful data transformation engine, and over 130 built-in connectors to various databases, applications, and API ingestion.

Integrate.io features straightforward pricing with no hidden fees. You'll pay a flat fee per year, depending on how many connectors you use. The Starter Plan starts at $15,000 per year.

What Makes Integrate.io Stand Out?

Integrate.io provides a unified platform for data ingestion and manipulation. It’s packed with powerful features that can help you quickly generate a single source of truth covering all your data.

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2. Airbyte

Rating: 4.3/5.0 (G2)

Airbyte is an open-source data integration platform that enables businesses to create ELT data pipelines. One of the main advantages of Airbyte is that it allows data engineers to set up log-based incremental replication, ensuring that data is always up-to-date.

What Makes Airbyte Stand Out?

Businesses of all sizes can use Airbyte free of charge, as the platform is an open-source alternative to cloud-based data pipelines. But this can also be detrimental for some organizations that do not have the necessary resources to hire data engineers and programmers.

Even so, Airbyte provides a wide range of features that help businesses unify their data:

  • 300+ out-of-the-box connectors: Experience faster setup time with built-in, editable connectors.
  • Quick support: Gain an average response time of fewer than 10 minutes.
  • Build custom connectors: Use Airbyte’s CDK to quickly create new connectors in any programming language.
  • CDC replications: Easily schedule incremental and log-based replications.
  • Cloud hosting: Airbyte also provides cloud hosting and management services.

If you don’t want to deploy your own instance of Airbyte, you can opt for a paid plan with pricing starting at $2.50 per credit. Writing in database and warehouse destinations is free, but all other operations have a credit cost:

  • Read API source: 6 credits per million rows
  • Read database, warehouse, and file sources: 4 credits per GB
  • Read custom source: 6 credits per million rows

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3. Amazon Kinesis

Rating: 4.2/5.0 (G2)

Amazon Kinesis is a fully managed, cloud-based service from Amazon Web Services that enables real-time processing of streaming data on a massive scale. It's designed to capture, store, and process streaming data from various sources, including websites, applications, sensors, and IoT devices. 

What Makes Amazon Kinesis Stand Out?

Kinesis can process terabytes of data per hour from hundreds of thousands of data sources, but its biggest advantage is that it can seamlessly integrate with other AWS services.

Its capabilities can be broken down into four components:

  • Kinesis Video Streams: Stream video from connected devices to AWS for various processing purposes.
  • Kinesis Data Streams: Access a scalable real-time data streaming service that can capture gigabytes of data per second from hundreds of thousands of sources.
  • Kinesis Data Firehose: Capture, transform, and load data streams into AWS data stores.
  • Kinesis Data Analytics: Process data streams in real-time with SQL or Apache Flink.

A great thing about Kinesis is that it can be scaled up or down depending on your needs. This also means its pricing varies greatly but can't go lower than $20 per month.

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4. Matillion

Rating: 4.4/5.0 (G2)

Matillion is a cloud-based data integration and transformation platform that helps organizations move, transform, and analyze data in the cloud.

You can use the platform to create a complete data pipeline by leveraging its range of features, including data ingestion, data transformation, data orchestration, and data visualization. 

What Makes Matillion Stand Out?

Matillion can be quickly deployed and scaled up or down as needed, making it a flexible solution for businesses both in terms of pricing and implementation time. 

Organizations rely on Matillion because of its advanced capabilities:

  • Automate repetitive tasks: Eliminate the need for manual coding and reduce the time and effort required to move data from source to destination.
  • Advanced security: The built-in encryption and authentication features ensure your data is safe and secure throughout the ingestion process.
  • Hundreds of pre-built connectors: Ingest data from a variety of sources, including databases, files, and APIs, into a single platform.

Matillion offers a free plan which gives you access to up to a million rows a month. However, if you need to move more data, you'll want to upgrade. The Basic plan costs $2.00 per credit and includes unlimited users, volume, and sources. The other plans move up from there.

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5. Apache NiFi

Rating: 4.2/5.0 (G2)

Apache NiFi is a powerful and scalable data routing, transformation, and system mediation logic platform. It was designed to automate the flow of data between software systems.

What Makes Apache NiFi Stand Out?

Apache NiFi’s data ingestion engine works without a schema, meaning each NiFi processor is responsible for interpreting the content of the data it receives. You can use Apache NiFi as an individual tool or in a cluster configuration with its built-in clustering system.

Here are some more features that make NiFi a great data ingestion tool:

  • Visual command and control: Gain real-time visual establishment of data flows.
  • Flow templates: Pre-built components help you get started with NiFi in no time.
  • Advanced security: The encrypted protocols ensure data is safely exchanged between systems at every point of the data flow.
  • Flexible scaling model: Scale up and down depending on your hardware resources.

Apache NiFi is an open-source platform, which means its free to use.

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6. Apache Kafka

Rating: 4.5/5.0 (G2)

Apache Kafka is an open-source stream-processing software widely used for its advanced ETL capabilities. With it, businesses can build data pipelines by integrating data from multiple sources in real-time.

What Makes Apache Kafka Stand Out?

Apache Kafka is renowned for its high-performance throughput, which allows it to handle thousands of messages per second. But this platform has more to offer than that:

  • Scalability: Elastically expand or contract storage and processing as needed.
  • Permanent storage: Store streams of data in a distributed, durable, fault-tolerant cluster.
  • Out-of-the-box connect interface: Integrates with hundreds of event sources and event sinks.
  • Large ecosystem of open-source tools: Enhance your data ingestion process with a vast array of community-driven open-source tools.

Just like Apache NiFi, Apache Kafka is also an open-source tool that's free to use.

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7. Talend

Rating: 4.0/5.0 (G2)

Talend is an end-to-end data ingestion and management tool that combines data integration, integrity, and governance in a single, low-code platform. It’s extremely flexible and can be deployed on-premises or in the cloud.

What Makes Talend Stand Out?

Talend provides a comprehensive solution for managing data by combining rapid data ingestion, transformation, and mapping with automated quality checks.

One of its biggest strengths is its ability to connect to virtually any data source while ensuring the highest levels of data accuracy.

Here are more features that make Talend stand out from other data ingestion tools:

  • 1,000+ connectors and components: Quickly ingest data from virtually any source.
  • Drag-and-drop interface: Develop and deploy reusable data pipelines without code.
  • Data observability capabilities: Discover, highlight, and fix issues as data moves through your systems.
  • Data flexibility: Access data behind secure firewalls, locked in data centers, or in secure cloud environments.

As for pricing, Talend offers a wide range of plans to fit your specific needs, including Stitch, Data Management Platform, Big Data Platform, and Data Fabric. For accurate pricing, you must contact Talend's sales team.

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8. Dropbase

Rating: 0 ratings (G2)

Dropbase is a cloud-based platform that can extract, transform, and load data from CSV files and spreadsheets into live databases.

What Makes Dropbase Stand Out?

Dropbase helps you import and manage all your spreadsheet data in a fully-featured SQL database. This process is done in three simple steps:

  1. Select the production table you want to stage, specify the primary key, and add validation checks to the columns you need.
  2. Edit the data using a simple, spreadsheet-like UI. You can invite other team members to make edits, insert rows, or import more data as needed.
  3. Resolve any conflicts between staging and production, then sync the changes.

The best part is that you don’t need to set up or host your own database, as Dropbase manages this out-of-the-box. 

Dropbase features pay-as-you-grow or usage-based pricing. Other plans exist for larger organizations, such as the Pro plan and the Enterprise plan. For a custom quote, you'll need to contact sales.

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9. Tanzu Observability by Wavefront

Rating: 4.1/5.0 (G2)

Tanzu Observability by Wavefront is a high-performance streaming analytics service that enables users to ingest, store, visualize, and monitor all forms of metric data. 

What Makes Wavefront Stand Out?

Wavefront is capable of scaling to very high query loads and data ingestion rates, reaching millions of data points per second. Some other important features of this platform include:

  • Advanced charts and dashboards: Use filters and functions to see exactly what you’re interested in.
  • Create custom alerts: Detect problems early with advanced custom alerts and notifications.
  • Simple query language: The Wavefront query language (WQL) allows you to extract exactly the information you need.

Tanzu Observability pricing depends on your VMware plan, if applicable. For more detailed pricing information, you must contact VMware's sales team.

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10. Apache Flume

Rating: 3.9/5.0 (G2)

Flume is a powerful system that facilitates the process of gathering, combining, and transferring large amounts of log data.

What Makes Apache Flume Stand Out?

Apache Flume has a flexible architecture based on streaming data flows. Its tunable reliability mechanisms make it a robust and fault-tolerant solution even when working with incredibly large amounts of data.

Flume has multiple failover and recovery mechanisms and an extensible data model that allows for online analytics applications.

Just like the other Apache tools in this list, Flume is open-source and free to use.

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11. Precisely Connect

Rating: 0 ratings (G2)

Connect is a platform that enables users to migrate their data from the mainframe to the cloud. It provides batch and real-time data ingestion for analytics, machine learning, and data migration. 

What Makes Precisely Connect Stand Out?

Connect can save you hundreds of hours of development time and speed up the implementation of ETL processes by up to ten times through its self-tuning engine.

You can also use Connect to replicate changes to application data as they occur across various architectures and topologies, ensuring your databases are always in-sync.

Currently, Precisely doesn't disclose its pricing for the Connect tool. For more information, you'll need to reach out to Precisely's sales team.

What You Should Know Before Choosing a Data Ingestion Tool

Choosing the right data ingestion tool can be tedious, especially since so many options are available today. In the following section, we’ll answer some of the most frequently asked questions about data ingestion tools to help you make an informed decision.

What Is an Example of Data Ingestion?

An example of data ingestion is the process of extracting data from various IoT devices and placing it into a database or analytics platform for further analysis.

What Is a Data Ingestion Framework?

A data ingestion framework is a set of tools and processes used to collect, transform, and load data from multiple sources into a data warehouse or other data storage system. 

What Other Tools Are Important for Data-Driven Decision-Making?

Data ingestion is simply the first step when developing a data pipeline. That’s why companies rely on various tools to achieve a single source of truth. Some of these other tools include: