6 Best ELT Tools to Streamline Data Operations In 2024

July 19, 2024

Data drives your organization's success, as it helps you analyze market trends, reduce costs, and maximize profits. However, the key task is integrating this data from various platforms for enhanced analysis and visualization. There are different data integration solutions that you can employ for migrating data, but the ELT approach is one of the most popular and modern solutions that allows you to store raw data as soon as it is generated. 

In this article, you will understand the ELT data integration process and the top six ELT tools you can employ for streamlined data operations in 2024.

What is ELT?

ELT is a popular data integration process that stands for Extract, Load, Transform. It allows you to move data from one place to another effortlessly. The process starts with collecting data from diverse sources in its original format. You then need to replicate the collected data into destinations like data warehouses or data lakes. Once the data is loaded, you can perform the transformation to make your dataset analytics-ready.

Usage of ELT Method

Here are a few major uses of employing the ELT method to fulfill your data integration needs:

  • The ELT approach offers flexibility since the transformation is performed after the data is loaded into the destination. This allows you to add extracted data of any format to your target system without complexity.
  • The ELT data pipelines leverage modern cloud data warehouses for storage purposes, which can be efficient for large datasets. Since the raw data is directly loaded, you have untransformed data at your disposal. This enables you to perform data analytics according to your needs without reaching out to the source for the original data.
  • One of the major benefits of using the ELT method is faster initial data loading compared to ETL. This makes it cost-effective, as you do not have to spend time and resources on an additional system for data transformation.

Top 6 ELT Tools

Here’s a comprehensive list of the top six ELT tools that you can employ to streamline your data integration process:

Airbyte

Airbyte

Introduced in 2020, Airbyte is a robust data integration platform. It uses a modern ELT approach to extract data from diverse sources, such as SaaS applications, flat files, and databases, and load it into a centralized repository. Airbyte provides a rich library of 350+ pre-built connectors to automate the creation of data pipelines. If you can't find a connector of your choice, you can always build custom connectors using CDK or request a new one by contacting Airbyte’s team. To help you adapt to modern integration practices, Airbyte supports data sources that manage unstructured, semi-structured, and structured data types.

Some of the unique features of Airbyte

  • Airbyte allows you to employ the Change Data Capture feature to identify changes made in the source dataset and replicate them in the destination. This enables you to keep track of your data, thus ensuring data integrity and consistency.
  • With Airbyte, you can design and manage your data pipelines efficiently using UI, API, PyAirbyte, and Terraform Provider. While the User Interface doesn’t require programming skills, the other three let you utilize programming skills to create custom data pipelines.
  • To protect your data from external threats, Airbyte offers various security measures such as authentication mechanisms, encryption, access controls, and audit logging. In addition to these features, it also complies with security certifications like ISO 27001 and SOC 2 Type 2.
  • You can integrate Airbyte with dbt to leverage transformation capabilities. With dbt, you can perform simple to complex transformations. This enables you to clean and enhance raw data and convert it into a format suitable for analysis and reporting.

Matillion

Matillion

Launched in 2011, Matillion is a cloud-based platform that provides streamlined data integration processes such as ETL, ELT, and Reverse ETL. It empowers you to collect data from multiple sources and load them into your preferred destination system for seamless data analytics. In addition to these features, it also offers an intuitive interface with powerful push-down ETL/ELT functionality. This technology allows you to utilize your data warehouse potential to process complex joins over millions of rows within seconds.

Some of the unique features of Matillion

  • With Matillion, you can access a catalog of 150+ pre-built connectors to integrate data from various sources into a target system effortlessly. You can also build custom connectors if your required connector is unavailable in their list.
  • Matillion is a dynamic platform that allows you to perform basic to advanced transformations. The basic ones include functions such as filtering, mapping, and aggregation, while the complex ones leverage SQL and Python scripts to create functions.
  • It is equipped with data replication features, enabling you to eliminate redundant data by keeping it in sync. You can easily copy the changes in your data source and replicate them in your destination file.

Skyvia

Skyvia

Skyvia is a cloud-based data integration platform introduced in 2014 to facilitate effective data management. It allows you to implement different integration solutions, such as ETL, to extract data from multiple sources and load it into a centralized repository. Due to these capabilities, it is capable of managing complex operations like data splitting, conversions, and lookups. In addition to its integration features, Skyvia ensures data integrity across all platforms by enabling you to track changes in your source file and copy them into the destination.

Some of the unique features of Skyvia

  • Skyvia provides access to more than 160 pre-built connectors for migrating data across multiple platforms. But if you are unable to find a connector of your choice, you can always request a new one by reaching out to Skyvia’s platform.
  • It offers a powerful backup and restore feature for cloud applications to keep your data secure. You can perform manual or scheduled backups and ensure that data is not lost during the replication process.
  • With Skyvia, you can create a synchronization package that enables you to perform bi-directional data synchronization between relational databases and cloud applications. It also allows you to synchronize data with different structures, maintain all data relations, and provide strong mapping settings for configuring the entire process.

Stitch Data

Stitch Data

Stitch Data, an integral part of the Qlik Data Integration platform, is an open-source ELT tool designed for developing and managing data pipelines. It lets you quickly collect data from various sources, including databases, and load it into a centralized repository. Stitch also provides features like orchestration, scheduling, monitoring, and error handling that help you take full control and visibility over data as it moves from the source to the target system.

Some of the unique features of Stitch Data

  • To maintain data synchronization, it offers replication features that enable you to choose which source columns or tables to duplicate, establish replication schedules, and automate loading into the destination system.
  • With its pre-built connections to over 140 data sources, including databases, SaaS apps, and cloud platforms, Stitch facilitates data movement in a few minutes. Apart from built-in ones, if your preferred source isn't accessible, you can develop new ones by adhering to Singer's guidelines, an open-source framework for writing data movement scripts. 
  • Stitch Data has many security measures to protect data confidentiality and integrity. These safety features include IP address whitelisting, SSH tunnels, control access, and encryption based on SSL/TLS. 

Fivetran 

Fivetran

Fivetran, developed in 2012, is a cloud-based platform for integrating data. It assists with many integration tasks, including ELT, data migration, transformation, and governance. Due to its user-friendly interface, you can quickly connect various sources and destinations and leverage the flexibility to optimize your integration strategy to meet specific business goals. The platform manages complicated data pipelines by offering an automated mechanism for data extraction and loading, saving up IT resources for other uses.

Some of the unique features of Fivetran

  • With more than 500 connectors, Fivetran offers comprehensive support for all major databases, including DynamoDB and MySQL, as well as data warehouses like Redshift and Snowflake. Using these connectors, you can quickly load data into the target system after extracting it from various sources. 
  • Fivetran’s data transformation features allow you to prepare, organize, and analyze information while maintaining the data quality. It primarily enables you to perform transformations with the dbt Core and Quick Start data models. Both approaches facilitate complex transformations in the dataset using simple SQL queries. 
  • It provides various data replication techniques to provide effective, real-time data replication suited to different business workloads. Using a simple setup, you can employ the log-based CDC functionality to rapidly detect changes in your source data and replicate them into your desired destination.

Hevo Data

Hevo Data

Hevo Data is a powerful cloud-native integration service that provides end-to-end automated data pipelines. Its pre-built connectors library lets you collect data from 150+ sources, including SaaS applications or databases, and load them to over 15 destinations. This makes it easier to automate the integration process and employ the unified data for analytics and visualization. 

Some of the unique features of Hevo Data

  • Hevo Data leverages CDC functionality, which enables you to monitor and record changes in your source data files and replicate them to your preferred destination.
  • It mainly facilitates three transformations—in-flight, user-driven, and post-data. The in-flight process allows you to make minor changes, such as removing non-alphanumeric characters from a table, while the user-driven process lets you clean and filter the data. Both these processes are performed before loading the data into the destination. Finally, the post-data process involves data refining after loading.
  • With Hevo, you can safeguard your data from unauthorized access using features such as VPN, SSH, and Reverse SSH connections. It also adheres to best security practices, such as GDPR, HIPAA, and SOC 2, to maintain data confidentiality.

Final Word

Data integration is essential to your business activities as it empowers you to perform extensive data analysis by keeping them in one place. With the advent of cloud-based data lakes and warehouses, the ELT approach to moving and consolidating data has become quite popular. This article briefly discussed the top six ELT tools you can leverage to solve your data replication needs. Each tool is equipped with diverse features and is tailored to perform specific tasks based on your enterprise needs.

We suggest using Airbyte to move your data. It offers a rich library of pre-built and custom connectors to automate your data pipelines. Sign in on the Airbyte platform today to navigate through the different features it offers.

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Frequently Asked Questions

What is ETL?

ETL, an acronym for Extract, Transform, Load, is a vital data integration process. It involves extracting data from diverse sources, transforming it into a usable format, and loading it into a database, data warehouse or data lake. This process enables meaningful data analysis, enhancing business intelligence.

What is ?

What data can you extract from ?

How do I transfer data from ?

This can be done by building a data pipeline manually, usually a Python script (you can leverage a tool as Apache Airflow for this). This process can take more than a full week of development. Or it can be done in minutes on Airbyte in three easy steps: set it up as a source, choose a destination among 50 available off the shelf, and define which data you want to transfer and how frequently.

What are top ETL tools to extract data from ?

The most prominent ETL tools to extract data include: Airbyte, Fivetran, StitchData, Matillion, and Talend Data Integration. These ETL and ELT tools help in extracting data from various sources (APIs, databases, and more), transforming it efficiently, and loading it into a database, data warehouse or data lake, enhancing data management capabilities.

What is ELT?

ELT, standing for Extract, Load, Transform, is a modern take on the traditional ETL data integration process. In ELT, data is first extracted from various sources, loaded directly into a data warehouse, and then transformed. This approach enhances data processing speed, analytical flexibility and autonomy.

Difference between ETL and ELT?

ETL and ELT are critical data integration strategies with key differences. ETL (Extract, Transform, Load) transforms data before loading, ideal for structured data. In contrast, ELT (Extract, Load, Transform) loads data before transformation, perfect for processing large, diverse data sets in modern data warehouses. ELT is becoming the new standard as it offers a lot more flexibility and autonomy to data analysts.