Top 5 ETL Tools to Consider in 2023
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There’s a rising demand for ETL tools, which are a part of the rapidly growing data integration market.
As the humans of data become increasingly diverse, the requirements from ETL tools continue to evolve. Data engineers now expect ETL tools to automate pipelines, enable data orchestration, and speed up analytics.
This article covers five such ETL tools that go beyond data transformation to support automated integration workflows and data orchestration.
Table of contents
- 5 Popular ETL tools
- Talend Data Fabric
- Informatica PowerCenter
- How to evaluate ETL tools
- FAQs about ETL tools
- ETL tools: Related reads
- Related deep dives on popular data tools
5 Popular ETL tools
Here are the five most popular ETL tools in 2023:
- Talend Data Fabric
- Informatica PowerCenter
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1. Talend Data Fabric
The Talend Data Fabric offers a complete suite of cloud-based data management tools that handle data collection, transformation, analytics, and governance. You can set up an ETL architecture that supports data from various sources and formats. Since Talend generates native Java code, you to run it anywhere — on any platform that supports Java.
What are the main capabilities of Talend?
- Talend lets you connect to data in public and private clouds as well as hybrid environments. Moreover, they have partnered up with leading cloud service providers, data warehouses, and analytics platforms — AWS, Microsoft Azure, GCP, Snowflake, and Databricks.
- You can use 1000+ connectors and components to connect any data source with any data environment with a drag-and-drop interface. You can also reuse ETL pipelines to speed up data integration.
- You can ensure data quality by spotting and fixing issues as data moves through your systems.
- Talend assigns a Talend Trust Score to check data health throughout the lifecycle of an asset.
2. Informatica PowerCenter
Informatica PowerCenter is a metadata-driven data integration platform for cloud environments. With Informatica PowerCenter, you can extract data from its source, transform it as per your requirements, and load it into a target data warehouse.
The platform continuously evaluates the performance of your processing engines and workload to find the right integration method for each use case.
Informatica PowerCenter can connect and fetch data from multiple sources and offers various levels of services — Standard, Advanced, and Premium. Each edition offers support to more data types, sources, and projects. For instance, the Premium edition supports the transformation of semi-structured and unstructured data too.
What are the main capabilities of Informatica PowerCenter?
- Informatica PowerCenter provides real-time integration of data from multiple data sources using out-of-the-box connectors.
- You can use graphical and code-less tools with pre-built transformations to set up ETL pipelines automatically and make them reusable.
- The tool also supports non-relational data sets such as XML, JSON, PDFs, and sensor data.
- You can process ETL jobs from anywhere — cloud-hosted and managed environments.
Fivetran helps you build automated pipelines to centralize data from different sources. It provides ready-to-use connectors that automatically adapt as schemas without requiring any configuration and maintenance.
Fivetran promises a 5-minute setup and zero infrastructure maintenance and guarantees a 99.9% platform uptime. Unlike traditional ETL tools, Fivetran is built for analysts and business users and empowers them to perform data discovery and exploration without any IT support.
Fivetran offers a free 14-day trial.
What are the main capabilities of Fivetran?
- Fivetran supports setting up zero-configuration, fully automated data pipelines that replicate all of your data in minutes.
- It reduces the load on data engineers to create and deploy pipelines manually with automated connectors and prebuilt data models.
- Fivetran enables end-to-end ETL transparency by full-scale visualization of the data synchronization process between Amazon Redshift, Snowflake, or Google BigQuery data warehouses and BI tools.
Stitch Data Loader is a Talend product for cloud-based ETL and is part of the Talend Data Fabric. It’s used for data migration from 130+ sources into central data warehouses for further analysis.
Stitch provides data detection, extraction, and loading to a central data warehouse with continuous synchronization. Stitch allows data replication without requiring any modifications to the code.
You can sign up for a free 14-day trial and take Stitch for a test drive.
What are the main capabilities of Stitch?
- Data replication: Stitch allows data replication features for quick access to data without requiring clients to handle any modifications.
- Improved analytics: Stitch automates data pipeline management, allowing data engineers to focus on retrieving better insights from the data.
- Scalability: Stitch provides scalable services with ready-to-use and self-managing connectors.
- Advanced security: Stitch holds enhanced security features and connectivity options to provide its clients with reliable data pipelines.
Xplenty, now identified as Integrate.io, is a low-code, cloud-based ETL tool to quickly design and run ETL pipelines.
Xplenty provides a coding-free data integration solution to build ETL pipelines without IT support. The platform is SOC2 compliant and uses advanced security features such as FLE, hashing, 2FA, and masking for data security and privacy.
What are the main capabilities of Xplenty?
- The platform supports 100+ native data sources and destinations — Salesforce, AWS, Snowflake, Netsuite, and more.
- The automated ETL pipelines are scalable, reliable, and reusable.
- Xplenty provides a simple drag-and-drop interface for users to set up transformations without requiring them to know its technicalities.
- However, if you wish to code, you can leverage advanced APIs, X-console, and webhooks to customize and extend the Xplenty platform.
- You can schedule tasks as and when required.
- You can track the progress of any job using visual dashboards.
How to evaluate ETL tools?
In data warehousing, ETL tools allow data engineers to break down data bottlenecks and simplify data analysis. Since organizations operate at different scales, their requirements from ETL tools can vary.
Here are some factors to consider when evaluating ETL tools:
Simplification of data handling: How much do you wish to simplify the data integration process?
Different ETL tools automate these processes to various extents, from low-coding to no-coding.
Security: Which security features are crucial for your data governance program?
ETL tools provide different security features to mitigate security risks and you should pick a solution that adheres to your data privacy policies.
Data cleansing and manipulation support: Which data cleansing features do you need?
Also, do you require support to manipulate data so that it gets organized in a central repository in a standard format?
Metadata support: Do you require metadata storage and maintenance?
Besides these, you should also consider your budget and available engineering resources when comparing various ETL tools.
FAQs about ETL tools
What are ETL tools?
ETL tools are data integration tools that allow automated and secure extraction, transformation, and data loading between systems.
Also, check out ETL vs. ELT.
Why are ETL tools used?
Organizations use ETL tools to simplify their data integration processes and focus on data analytics.
How many ETL tools are there?
There is a vast variety of ETL tools in the market divided into enterprise-grade tools, open-source tools, custom tools, and cloud-based tools.
What is ETL orchestration?
ETL orchestration refers to building and maintaining big data pipelines.
What is the future of ETL?
ETL is on its way to going beyond data integration to incorporate data administration, data quality, and data security to form a complete data management system.
ETL tools: Related reads
- ETL vs. ELT: Which data integration process is ideal?
- Data transformation: What, how, and why it’s needed
- Data ingestion vs. data integration: How are they different?
- The future of the modern data stack in 2023
- The building blocks of a modern data platform
- Data Orchestration vs ETL: 7 Core Differences Explained
Related deep dives on popular data tools
- 7 popular open-source ETL tools
- 9 best data discovery tools
- 5 popular open-source data catalog tools to consider in 2023
- 7 popular open-source data governance tools to consider in 2023
- 12 popular observability tools in 2023
- 10 popular transformation tools in 2023
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