Best ETL Tools:
One of the hallmarks of the Information Age is that data
exists everywhere. Whether it's estimated delivery dates of your packages or
analytics on the amount of screen time you spend on your phones, you access
data every day to inform your decisions and set goals.
Organizations leverage data in the same way but on a larger
scale. They have data on customers, employees, products, and services that all
must be standardized and shared across various teams and systems. This
information may even be made available for external partners and vendors.
To achieve this highly scaled information sharing and avoid
data silos, organizations turn to the extract, transform, and load (ETL)
practice for formatting, passing, and storing data between systems. With the
large volumes of data organizations are handling between all their business
processes, ETL tools can standardize and scale their data pipelines.
What are ETL Tools?
ETL tools are software designed to support ETL processes:
extracting data from disparate sources, scrubbing data for consistency and
quality, and consolidating this information into data warehouses. If
implemented correctly, ETL tools simplify data management strategies and
improve data quality by providing a standardized approach to intake, sharing,
and storage.
ETL tools support data-driven organizations and platforms.
For example, customer-relationship management (CRM) platforms' central
advantage is that all business activities are conducted through the same
interface. This allows CRM data to be easily shared between teams to provide a
more holistic view of business performance and progress toward goals.
Next, let's examine the four types of ETL tools available.
Types of ETL Tools
1. Enterprise Software ETL Tools
Enterprise software ETL tools are developed and supported by
commercial organizations. These solutions tend to be the most robust and mature
in the marketplace since these companies were the first to champion ETL tools.
This includes offering graphical user interfaces (GUIs) for architecting ETL
pipelines, support for most relational and non-relational databases, and
extensive documentation and user groups.
Though they offer more functionality, enterprise software
ETL tools will typically have a larger price tag and require more employee
training and integration services to onboard due to their complexity.
2. Open-Source ETL Tools
With the rise of the open-source movement, it’s no surprise that open-source ETL tools have entered the marketplace. Many ETL tools today are free and offer GUIs for designing data-sharing processes and monitoring the flow of information. A distinct advantage of open-source solutions is that organizations can access the source code to study the tool's infrastructure and extend capabilities.
However, open-source ETL tools can vary in upkeep,
documentation, ease of use, and functionality since they are not usually
supported by commercial organizations.
3. Cloud-Based ETL Tools
Following the widespread adoption of cloud and
integration-platform-as-a-service technologies, cloud service providers (CSPs)
now offer ETL tools built on their infrastructure.
A specific advantage of cloud-based ETL tools is efficiency.
Cloud technology provides high latency, availability, and elasticity so that
computing resources scale to meet the data processing demands at that time. If
the organization also stores its data using the same CSP, then the pipeline is
further optimized because all processes take place within a shared
infrastructure.
A drawback of cloud-based ETL tools is that they only work
within the CSP's environment. They do not support data stored in other clouds or
on-premise data centers without first being shifted onto the provider's cloud
storage.
4. Custom ETL Tools
Companies with development resources may produce proprietary
ETL tools using general programming languages. The key advantage of this
approach is the flexibility to build a solution customized to the
organization's priorities and workflows. Popular languages for building ETL
tools include SQL, Python, and Java.
The largest drawback of this approach is the internal
resources required to build out a custom ETL tool, including testing,
maintenance, and updates. An additional consideration is the training and
documentation to onboard new users and developers who will all be new to the
platform.
Now that you understand what ETL tools are and the categories
of tools available, let's examine how to evaluate these solutions for the ideal
fit for your organizations' data practices and use cases.
How to Evaluate ETL Tools
Every organization has a unique business model and culture,
and the data that a company collects and values will reflect this. However,
there are common criteria that you can measure ETL tools against that will be
relevant to each organization, which are outlined below.
Use case: Use case is a critical consideration for ETL
tools. If your organization is small or your data analysis requirements are
minor, then you may not need as robust of a solution as large organizations
with complex datasets.
Budget: Monetary cost is another important factor when
evaluating ETL software. Open-source tools are typically free to use but may
not offer as many capabilities or support as enterprise-grade tools. Another
consideration is the resources required to hire and retain developers if the
software is code intensive.
Capabilities: The best ETL tools can be customized to meet
the data needs of different teams and business processes. Automated features
like de-duplication are one-way ETL tools can enforce data quality and reduce
the labor required to analyze datasets. In addition, data integrations
streamline sharing between platforms.
Data sources: ETL tools should be able to meet data
"where it lives," whether it is on-premise or in the cloud. ETL
connectors are the components of an ETL tool that establish connections to data
sources. Organizations may also have complex data structures or unstructured
data, all in different formats. An ideal solution will be able to extract
information from all sources and store it in standardized formats.
Technical literacy: The data and code fluency of developers
and end users is a key consideration. For example, if the tool requires manual
coding, then ideally the development team can use the languages it's built on.
However, if the user does not understand how to construct complex queries, then
a tool that automates this process will be ideal.
Next, let’s examine individual tools to power your ETL
pipelines and group them by the types discussed above.
ETL Tools
- Integrate.io
- IBM DataStage
- Oracle Data Integrator
- Fivetran
- SAS Data Management
- Talend Open Studio
- Pentaho Data Integration
- Singer
- Hadoop
- Dataddo
- AWS Glue
- Azure Data Factory
- Google Cloud Dataflow
- Stitch
- Informatica PowerCenter
1. Integrate.io
Price: Free 14-day trial & flexible paid plans available
Type: Cloud
Integrate.io is a leading low-code data integration platform
with a robust offering (ETL, ELT, API Generation, Observability, Data Warehouse
Insights) and hundreds of connectors to build and manage automated, secure
pipelines in minutes. Get constantly refreshed data to help deliver actionable,
data-backed insights to do things like lower your CAC, increase your ROAS, and
drive go-to-market success.
The platform is highly scalable with any data volume or use
case, while enabling you to easily aggregate data to warehouses, databases,
data stores, and operational systems.
2. IBM DataStage
Price: Free trial with paid plans available
Type: Enterprise
IBM DataStage is a data integration tool built around a
client-server design. From a Windows client, tasks are created and executed
against a central data repository on a server. The tool is designed to support
ETL and extract, load, and transform (ELT) models and supports data
integrations across multiple sources and applications while maintaining high
performance.
IBM DataStage is built for on-premise deployment and is also
available in a cloud-enabled version: DataStage for IBM Cloud Pak for Data.
3. Oracle Data Integrator
Price: Pricing available on request
Type: Enterprise
Oracle Data Integrator (ODI) is a platform designed to
build, manage, and maintain data integration workflows across organizations.
ODI supports the full spectrum of data integration requests from high-volume
batch loads to service-oriented architecture data services. It also supports
parallel task execution for faster data processing and offers built-in
integrations with Oracle Golden Gate and Oracle Warehouse Builder.
ODI and other Oracle solutions can be monitored through the
Oracle Enterprise Manager for greater visibility across the toolstack.
4. Fivetran
Price: 60$/month for Standard Select plan; 120$/month for
Starter plan; 180$/month for Standard plan; $240/month for Enterprise plan
Type: Enterprise
Fivetran aims to add convenience to your data management
process with its platform of handy tools. The easy-to-use software keeps up
with API updates and pulls the latest data from your database in minutes.
In addition to ETL tools, Fivetran offers data security
services, database replication, and 24/7 support. Fivetran prides itself on its
nearly perfect uptime, giving you access to its team of engineers at a moment's
notice.
5. SAS Data Management
Price: Pricing available on request
Type: Enterprise
SAS Data Management is a data integration platform built to
connect with data wherever it exists, including cloud, legacy systems, and data
lakes. These integrations provide a holistic view of the organization's
business processes. The tool optimizes workflows by reusing data management
rules and empowering non-IT stakeholders to pull and analyze information within
the platform.
SAS Data Management is also flexible and works in a variety
of computing environments and databases as well as integrating with third-party
data modeling tools to produce compelling visualizations.
6. Talend Open Studio
Price: Free
Type: Open Source
Talend Open Studio is an open-source tool designed to
rapidly build data pipelines. Data components can be connected to run jobs
through Open Studio's drag-and-drop GUI from Excel, Dropbox, Oracle,
Salesforce, Microsoft Dynamics, and other data sources. Talend Open Studio has
built-in connectors to pull information from diverse environments, including
relational database management systems, software-as-a-service platforms, and
packaged applications.
7. Pentaho Data Integration
Price: Pricing available on request
Type: Open Source
Pentaho Data Integration (PDI) manages data integration
processes, including capturing, cleansing, and storing data in a standardized
and consistent format. The tool also shares this information with end users for
analysis, and it supports data access for IoT technologies to facilitate machine
learning.
PDI also offers the Spoon desktop client for building
transformations, scheduling jobs, and manually initiating processing tasks when
needed.
8. Singer
Price: Free
Type: Open Source
Singer is an open-source scripting technology built to
enhance data transfer between an organization's applications and storage.
Singer defines the relationship between data extraction and data loading
scripts, allowing information to be pulled from any source and loaded to any
destination. The scripts use JSON so that they are accessible in any
programming language and also support rich data types and enforce data
structures through JSON Schema.
9. Hadoop
Price: Free
Type: Open Source
The Apache Hadoop software library is a framework designed
to support processing large data sets by distributing the computational load
across clusters of computers. The library is designed to detect and handle
failures at the application layer versus the hardware layer, providing high
availability while combining the computing power of multiple machines. Through
the Hadoop YARN module, the framework also supports job scheduling and cluster
resource administration.
10. Dataddo
Price: Free with paid plans available
Type: Cloud
Dataddo is a no-code, cloud-based ETL platform that enables
technical and non-technical users to flexibly integrate data. It offers a wide
range of connectors, fully customizable metrics, a central system for
simultaneous management of all data pipelines, and can be seamlessly
incorporated into existing technology architecture.
Users can deploy pipelines within minutes of account
creation and all API changes are managed by the Dataddo team, so pipelines
require no maintenance. New connectors can be added within 10 business days
upon request. The platform is GDPR, SOC2, and ISO 27001 compliant.
11. AWS Glue
Price: Free with paid plans available
Type: Cloud
AWS Glue is a cloud-based data integration service that
supports visual and code-based clients to support technical and non-technical
business users. The serverless platform offers multiple features to provide
additional functions, such as the AWS Glue Data Catalog for finding data across
the organization and the AWS Glue Studio for visually designing, executing, and
maintaining ETL pipelines.
AWS Glue also supports custom SQL queries for more hands-on data interactions.
12. Azure Data Factory
Price: Free trial with paid plans available
Type: Cloud
Azure Data Factory is a serverless data integration service
built on a pay-as-you-go model that scales to meet computing demands. The
service offers both no-code and code-based interfaces and can pull data from
more than 90 built-in connectors. In addition, Azure Data Factory integrates
with Azure Synapse Analytics to provide advanced data analysis and
visualization.
The platform also supports Git for version control and
continuous integration/continuous deployment workflows for DevOps teams.
13. Google Cloud Dataflow
Price: Free trial with paid plans available
Type: Cloud
Google Cloud Dataflow is a fully managed data processing
service built to optimize computing power and automate resource management. The
service is focused on reducing processing costs through flexible scheduling and
automatic resource scaling to ensure usage matches needs. In addition, Google
Cloud Dataflow offers AI capabilities to power predictive analysis and
real-time anomaly detection as the data is transformed.
14. Stitch
Price: Free trial with paid plans available
Type: Cloud
Stitch is a data integration service designed to source data
from 130+ platforms, services, and applications. The tool centralizes this
information in a data warehouse without requiring any manual coding. Stitch is
open source, allowing development teams to extend the tool to support
additional sources and features. In addition, Stitch focuses on compliance,
providing the power to analyze and govern data to meet internal and external
requirements.
15. Informatica PowerCenter
Price: Free trial with paid plans available
Type: Enterprise
Informatica PowerCenter is a metadata-driven platform focused on improving collaboration between the business and IT teams and streamlining data pipelines. PowerCenter parses advanced data formats, including JSON, XML, PDF, and Internet of Things machine data, and automatically validates transformed data to enforce defined standards.
The platform also has pre-built transformations for ease of use, and it offers high availability and optimized performance to scale to meet computing demands.
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