With data growing at the speed of light, modern companies now require robust ETL tools. Managing such complex data needs with traditional ETL tools requires companies to make large investments in terms of engineering bandwidth, physical data warehouses, or data centers.
To overcome all these challenges, companies have now started to shift to Cloud ETL Tools, which provides robust & automated ETL pipelines that users can deploy in a matter of minutes. It also takes away the need to invest in any hardware by allowing users to store their data in cloud data warehouses.
This article focuses on Cloud ETL Tools and provides you with a comprehensive list of some of the best tools you can use to simplify ETL for your business.
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What is Cloud ETL?
ETL stands for extract, transform and load and refers to the process of integrating data from a variety of sources, transforming it into an analysis-ready form and loading it into the desired destination, usually a data warehouse. It helps bring in data and store it in a centralized location, thereby allowing users to use diverse data for analysis.
With Cloud ETL, both, the sources from where companies bring in the data and the destination data warehouses are purely online.
There is no physical data warehouse or any other hardware that a business needs to maintain. Cloud ETL manages these dataflows with the help of robust Cloud ETL Tools that allows users to create and monitor automated ETL data pipelines, all through a single user interface.
Cloud ETL has the following three stages:
- Extract: It is the process of integrating structured and unstructured data from a diverse set of sources such as databases, data warehouses, marketing tools, CRMs, mobile apps, etc.
- Transform: It is the most critical part of an ETL process and refers to the process of enriching and transforming data into an analysis-ready form using techniques such as sorting, cleaning, removing redundancy, verifying, etc.
- Load: It refers to the process of loading data into the desired destination in a ready-to-use form. Data can be loaded either entirely using the full-loading technique or at scheduled intervals using the incremental loading technique.
Some key advantages of Cloud ETL:
- Cost-Effective: Most of the Cloud ETL services make use of the pay-as-you-go pricing model and charge users only for the resources they consume, rather than hefty fixed costs.
- Quick Insights: Cloud ETL services have minimal latency and provide the data in an analysis-ready form in almost real-time and hence makes the job of data analyst easy, allowing them to draw crucial business insights quickly.
- Easy Setup: Cloud ETL eradicates the need for having physical devices or servers set up on-premises. Such physical devices not only take a lot of space but also require a lot of maintenance to be done manually.
What Types Of ETL Tools Exist?
ETL tools come in two categories: classic ETL tools and cloud ETL solutions. These two groups have a greater variety of distinct ETL tool types.
1. Custom ETL Solutions
Data engineering and ETL pipeline specialists create, oversee, and manage unique solutions and pipeline designs.
To construct their data pipelines, they could make use of Hadoop processes, SQL, or Python scripts. Although this approach offers high compatibility and usability, it is labor-intensive, time-consuming, and error-prone.
2. Batch ETL tools
These programs use batch processing to retrieve data from many sources. Data is loaded, transformed, and extracted in batches. The strategy is economical because it makes efficient use of the few resources available.
3. Streaming or Real-Time ETL Tools
These are real-time technologies that can load, enhance, and extract data. This kind of ETL solution is, therefore growing in popularity as businesses look for quick, actionable information.
4. Tools for on-premise ETL
Certain ETL methods work better with on-premises and legacy systems, such as outdated databases that adhere to antiquated data management conventions. Others adhere to single-tenant architectural guidelines and guarantee data security by using more advanced ETL technologies.
5. Cloud ETL tools
Large volumes of data are managed by cloud-based ETL systems from a variety of cloud-native and cloud-enabled sources. If they have explicit authority to do so, they greatly increase the accessibility of data for many stakeholders, regardless of location.
6. Open-source ETL Tools
Open-source ETL software can serve as the foundation for custom ETL tool development by various organizations. By doing this, businesses may combine, store, safeguard, and analyze their sensitive data without relying on outside tools or services.
7. Hybrid ETL tools
To provide versatility, some ETL systems integrate capabilities from several ETL platforms. What was the outcome? Multiple data management tasks may be handled at scale by a single ETL platform.
Factors to consider before selecting Cloud ETL Tools
Choosing the perfect Cloud ETL Tool that matches all your business requirements can be a challenging task, even for experienced professionals. Here are some of the factors that you must look into before making a choice:
- Data Sources: Before making a final tool choice, you must consider the fact that whether these tools support ingesting data from your data sources that you’re currently using or might need in the future. Having a clear idea about this helps eradicate possible ingestion failures and also ensures a smooth ETL process.
- Selecting a Destination: Cloud ETL Tools only help users or businesses bring in data from their desired sources into a destination of their choice. They never provide users with an in-built warehouse solution, hence selecting the right destination becomes crucial. This requires users to think about whether they are going to use an existing database or set up a warehousing solution to leverage the power of their Cloud ETL Tools.
- Simplicity: When selecting the tool for your business, you must also take into consideration the extent to which it will simplify the ETL process. If you choose an ETL tool that requires you to manually code pipelines or have a wide engineering bandwidth to maintain it, it will lead to a lot of long-term problems. Hence, you must choose a tool that not only automates the ETL process but also requires minimal maintenance.
- Use Case: One of the most important considerations that a company must look into is its use case. Companies must weigh tools against each other to see if they can meet the business requirements before making a final choice.
- Budget: Even though Cloud ETL Tools are cost-effective, there are a diverse set of options available in the market, each of which has a different pricing model. Companies must take into consideration the amount of money they want to invest and then choose a tool that provides maximum functionalities, meets their business requirements and yet stays within their budget.
- Level of customizability: Businesses should base their ETL Cloud tools selection on the technical know-how of their IT staff as well as their needs for customization. While most ETL solutions include built-in connections and transformations that may be suitable for a start-up, a large business with custom data gathering would likely want the ability to create custom transformations with the support of a capable engineering team.
Top 14 Cloud ETL Tools
Choosing the ideal Cloud ETL Tool that perfectly meets your business requirements can be a challenging task, especially when there’s a large variety of ETL tools available in the market. To simplify your search, here is a comprehensive list of 14 best Cloud ETL Tools that you can choose from and start setting up ETL pipelines with ease:
1. Hevo Data
Hevo Data, a No-code Data Pipeline helps you to replicate data from any data source with zero maintenance. You can get started with Hevo’s 14-day Free Trial and instantly move data from 150+ pre-built integrations comprising of a wide range of SaaS apps and databases. Using Hevo, you can precisely control pipeline schedules down to the minute.
Setting up data pipelines with Hevo is a simple 3-step process by just selecting the data source, providing valid credentials, and choosing the destination.
Hevo not only loads the data onto the desired Data Warehouse but also enriches the data and transforms 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.
Check out what makes Hevo amazing:
- Near Real-Time Replication -: Get access to near real-time replication on All Plans. Near Real-time via pipeline prioritization for Database Sources. For SaaS Sources, near real-time replication depend on API call limits.
- In-built Transformations – Format your data on the fly with Hevo’s preload transformations using either the drag-and-drop interface, or our nifty python interface. Generate analysis-ready data in your warehouse using Hevo’s Postload Transformation.
- Monitoring and Observability-: Monitor pipeline health with intuitive dashboards that reveal every stat of pipeline and data flow. Bring real-time visibility into your ETL with Alerts and Activity Logs.
- Reliability at Scale -: With Hevo, you get a world-class fault-tolerant architecture that scales with zero data loss and low latency.
- 24×7 Customer Support – With Hevo you get more than just a platform, you get a partner for your pipelines. Discover peace with round-the-clock “Live Chat” within the platform. What’s more, you get 24×7 support even during the 14-day free trial.
Hevo Data provides Transparent Hevo Pricing to bring complete visibility to your ETL spend. You can also choose a plan based on your business needs.
Pricing Model of Hevo Data
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2. Skyvia
Skyvia is one of the most popular Cloud ETL Tools that provide users with robust data integration, migration and backup support. Being a SaaS application, it only requires users to have smooth internet connectivity and a web browser to be able to access it.
Skyvia’s impeccable no-code data integration wizard allows users to bring in data from a variety of sources such as databases, cloud applications, CSV files, etc. to data warehouses of their choice such as Google BigQuery, Amazon Redshift, etc.
Some of the common issues that you might encounter while using Skyvia is that it doesn’t have fast customer support response times. Similarly, another problem with Skyvia is that it provides less integration support and transformation functionalities.
Skyvia Use Case
Skyvia can be a suitable choice for you if you’re looking for a tool that provides a no-code solution to help you automate your ETL pipelines, and you’re okay with minimal data transformation functionalities.
Pricing Model of Skyvia
Skyvia provides users with four different use cases, namely data integration, backup, query, and connect to choose from, with the basic plan for all them available free of cost. You can choose to pay either monthly or annually based on your business needs.
3. Integrate.io
Integrate.io is a robust Cloud ETL Tool that provides an easy-to-use data integration platform and helps you integrate data from a diverse set of sources. Its intuitive user interface lets users set up data pipelines with ease.
It houses powerful data transformation functionalities that allow users to clean, transform and normalise their data into an analysis-ready form. It provides integration support with a diverse set of sources such as on-premise databases, cloud applications, SaaS offerings, etc. such as MongoDB, MySQL, PostgreSQL, etc.
Integrate.io Use Case
Integrate.io can prove to be the right choice for companies that want an easy-to-use no-code data integration platform to manage their ELT and ETL workloads. It can be a good choice for businesses that don’t want to invest much in their engineering bandwidth and prefer leveraging pre-built integrations and functionalities such as drag and drop features.
Pricing Model of Integrate.io
Integrate.io follows a pricing model where it charges users based on the number of connectors they have used. Every user has to pay a flat price of two connectors per month, and depending upon their usage, the final cost is determined. You will have to contact the Integrate.io team for the exact pricing as it doesn’t provide a transparent pricing model.
4. Talend
Talend is an open-source Cloud ETL Tool that provides more than 100 pre-built integrations and helps users bring in data from both on-premise and cloud-based applications and store it in the destination of their choice.
With Talend, you can seamlessly work with complex process workflows by making use of the large suite of apps provided by Talend. You can manage the design, testing and deployment of your integrations. It also provides a smooth drag and drops functionality along with an open studio feature for beginners.
Talend Use Case
Talend is a suitable choice for companies that require the flexibility of a diverse set of pre-built integrations and are looking for an open-source ETL solution.
Pricing Model of Talend
Talend provides users with five different subscription offerings, with the basic plan, known as the Talend Open Source plan, available free of cost. Talend also provides users with a 14-day free trial for the paid subscription plans.
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5. Informatica PowerCenter
Informatica PowerCenter is an enterprise-grade data integration platform. It is one of the most robust and well-reputed Cloud ETL Tools in the market and is available as one of the tools in the Informatica cloud data management suite.
It performs exceptionally well and helps integrate data from numerous data sources, including various SQL and NoSQL databases. PowerCenter’s data integration platform is highly scalable, and scales as your business grows to manage your business and data needs and helps transform fragmented data into an analysis-ready form.
Some of the common issues you might face using Informatica is that it has a steep learning curve and requires users some time to learn and understand the platform. Similarly, it can turn out to be an expensive solution for various small businesses.
Informatica PowerCenter Use Case
If your company is a large enterprise that can support expensive ETL solutions and has a challenging workload that requires high-end performance, then Informatica can be the right choice. You must also be ready to invest a large amount of time in learning the platform as it has a steep learning curve.
Pricing Model of Informatica
Informatica follows a pricing model where the price depends upon the type and number of your data sources, the in-place security features, etc. Informatica doesn’t provide transparent pricing. The basic plan of Informatica starts at $2000/month. It also provides users with a 30-day free trial.
6. Fivetran
Fivetran is a cloud-based ETL tool that delivers high-end performance and provides one of the most versatile integration support, supporting over 90+ SaaS sources apart from various databases and other custom integrations.
It is fully-managed and helps deploy automated ETL pipelines in a matter of minutes. It has an easy to use platform with a minimal learning curve that allows you to integrate and load data to various data-warehouses such as Google BigQuery, Amazon Redshift, etc. It further adapts to changes in the API and schema easily.
Some of the common issues that you might face while using Fivetran is that if there’s an error or technical issue, it becomes challenging to figure out the cause of it. Further, Fivetran customer support tends to be slow in responding to your queries.
Fivetran Use Case
Fivetran is a suitable choice for companies that require the flexibility of a diverse set of pre-built integrations.
Pricing Model of Fivetran
Fivetran follows a pay-as-go pricing model and provides users with three subscription offerings, with the basic plan, known as the Starter plan, available at $1/credit. Fivetran charges users only for the services they have used based on the number of data rows a user has created.
7. Stitch Data
Stitch Data is an open-source cloud-based ETL tool that is suitable for businesses of all kinds, even large enterprises. It provides users with intuitive self-service ELT pipelines that are fully-automated, allowing users to integrate data from various data sources such as SaaS applications, databases and store it in data warehouses, data lakes, etc.
Stitch doesn’t support much transformation functionalities and requires users to load the data and then transform it. It provides more advanced features to users as they go higher in the pricing tiers.
One common issue that most Stitch users face is the lack of support for some data sources and minor technical errors that occur frequently. Although Stitch has an easy-to-use UI, it can take some time to adjust to the UI.
Stitch Use Case
Stitch is suitable for companies that are looking for an open-source tool that provides a no-code solution to help them automate their ETL pipelines, and are okay with having minimal data transformation functionalities.
Pricing Model of Stitch
Stitch follows a pricing model that charges users based on the number of rows they are going to create, either monthly or annually. Stitch provides users with two subscription offerings, with the Stitch Standard plan starting at $100/month or $1000/annum. It also provides an Enterprise plan for which you need to get in contact with the Stitch team. It also provides users with a 14-day free trial.
8. AWS Glue
AWS Glue is one of the most popular Cloud ETL Tools by Amazon, meant for big data analytics. It simplifies ETL workloads and provides exceptional integration support with other AWS ecosystem applications.
It is a serverless offering by Amazon that allows users to make use of the AWS Management Console to run their ETL tasks and shut down the server once their workload is over.
AWS Glue Use Case
AWS is suitable for companies that are looking for a fully-managed ETL solution and have experience of how the AWS ecosystem looks like and functions.
Pricing Model of AWS Glue
AWS Glue follows a pay-as-you-go pricing model. It charges an hourly rate, billed by the second. The pricing is in terms of data processing units at 0.44 per DPU hour.
9. IBM Infosphere Datastage
Among the popular cloud based ETL tools is Infospehere Datastage offered by IBM, within the Infosphere Information Server environment. Users may create data pipelines that harvest data from many sources, carry out intricate transformations, and send the data to desired applications using the graphical framework.
The speed of IBM Infosphere is well-known, owing to features like parallelization and load balancing. In addition, a variety of data services, including data warehousing and AI applications, are supported, along with metadata and automatic failure detection.
IBM Infosphere use case
Infosphere Datastage provides a variety of connectors for merging various data sources, much as other business ETL solutions. Additionally, it easily interfaces with other IBM Infosphere Information Server modules, enabling users to create, test, implement, and keep an eye on ETL processes.
Pricing Model of IBM Infosphere
Depending on the size of your company, the service level needed, and the particular modules or components you want, IBM usually offers a variety of InfoSphere versions and price choices. They could have choices for cloud-based deployments, hybrid environments, or on-premises solutions.
10. Oracle Data Integrator
Oracle Data Integrator is one of the cloud-based data extraction tools that aids customers in creating, implementing, and maintaining intricate data warehouses and providing ETL automation in the cloud. Many databases, including Hadoop, EREPs, CRMs, XML, JSON, LDAP, JDBC, and ODBC, have pre-installed connections included with it.
Oracle Data Integrator Use Case
Data Integrator Studio, a component of ODI, offers developers and business users graphical user interface access to several artifacts. All the components of data integration are provided by these artifacts, including data transportation, synchronization, quality assurance, and management.
Pricing Model of Oracle Data Integrator
Oracle often offers many product versions to meet diverse business demands; the cost of a product may also vary depending on whether it is being used in a hybrid, on-premises, or cloud context.
11. Microsoft SQL Server Integration Services (SSIS)
SSIS is a platform for data integration and transformation at the corporate level. Connectors are included to enable data extraction from many sources, including relational databases, flat files, and XML files. The graphical user interface of SSIS designer allows practitioners to create data flows and transformations.
Microsoft SQL Server Integration Services (SSIS) Use Cases
The platform reduces the amount of code needed for development by including a library of built-in transforms. Additionally, SSIS provides thorough instructions for creating unique processes. But the platform’s complexity and steep learning curve can deter novices from building ETL pipelines rapidly.
Price Model of SSIS
Depending on the edition and licensing type selected, as well as any extra services or support needed, the price of SSIS may change. By acquiring SQL Server Integration Services (SSIS) Runtime, which has a different pricing structure, organizations can also choose to use SQL Server Integration Services as a stand-alone capability.
12. Google Cloud Dataflow
Google Cloud Dataflow is a fully-managed cloud service for executing data processing pipelines, including ETL workflows, in a cost-effective and scalable manner. It is serverless, automatically provisioning compute resources and scaling them as needed, allowing users to focus on defining their data processing logic rather than managing infrastructure.
Google Cloud Dataflow Use Cases
Google Cloud Dataflow enables real-time streaming data analytics with low latency. It reduces the total cost of ownership by offering cost-optimized batch and streaming processing, allowing organizations to handle seasonal and spiky workloads with virtually limitless capacity without overspending.
Pricing Model of Google Cloud Dataflow
Google Cloud Dataflow offers flexible pricing models based on the resources utilized by your jobs. The pricing for Dataflow is determined by measuring and billing the resources differently, depending on the chosen pricing model.
Additionally, Google Cloud Dataflow offers a generous free trial for new customers, providing $300 in free credits to explore and experiment with the service before incurring any charges.
13. Apache Airflow
Apache Airflow is an open-source workflow management platform that can be used as a cloud-based ETL tool for authoring, scheduling, and monitoring data pipelines. It enables programmatic authoring of data pipelines, provides rich monitoring capabilities, and supports a wide range of integrations with various data sources and destinations.
Apache Airflow Use Cases
- Building data-powered business applications
- On-demand infrastructure management for optimal resource utilization
- Enabling the modern MLOps stack by orchestrating the machine learning lifecycle
Pricing Model of Apache Airflow
Apache Airflow is licensed under the Apache License 2.0, which allows free usage, modification, and distribution for commercial purposes. There are no licensing costs associated with Airflow itself. However, organizations may incur costs for third-party services or tools built around Airflow that provide additional features or support offerings.
14. Airbyte
Airbyte is an open-source data integration platform that simplifies the process of extracting, transforming, and loading data from various sources to destinations in the cloud. It offers pre-built connectors for seamless integration with popular data sources and destinations, enabling efficient and scalable data pipelines in cloud environments.
Airbyte Use Cases
- Cloud data integration into warehouses and lakes
- Cloud data replication and synchronization
- Enabling cloud-based analytics and BI
- Building cloud-native data pipelines
Pricing Model of Airbyte
Airbyte has a volume-based pricing model, so you only pay for the data you move. They offer a free 14-day cloud trial to get you started. There are two main options: Cloud and Cloud with Teams. Cloud is ideal for teams that prioritize quick scaling and minimal maintenance, while Cloud with Teams caters to larger teams with stricter security needs.
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What do ETL Tools do?
ETL (Extract, Transform, Load) tools are designed to automate the entire data integration process, streamlining the extraction, transformation, and loading of data from various sources into a centralized repository or analytics platform.
Instead of manually writing code to handle each step, ETL tools leverage advanced data management techniques to automate the process, reducing errors and accelerating data integration.
Some key use cases and capabilities of ETL tools include:
- Handling massive volumes of structured and unstructured data: ETL tools can automate the ingestion, processing, and management of large-scale data volumes, both on-premises and in the cloud.
- Secure data delivery: ETL tools facilitate the secure delivery of data to appropriate analytics destinations, ensuring data integrity and confidentiality.
- Historical data organization: ETL tools help organize recent and older datasets in a historical context, making it easier to view, compare, and understand data over time.
- Database replication: ETL tools can replicate databases from various sources, such as MongoDB, Cloud SQL for MySQL, Oracle, Microsoft SQL Server, and AWS Redshift, to a cloud data warehouse, enabling continuous or one-time data updates.
- Cloud migration: ETL tools assist in migrating on-premises data, applications, and workflows to the cloud, supporting seamless transitions to cloud-based environments.
Curious about the range of ETL tools? Explore our guide to understand the different types available and choose the right tool for your data strategy.
Conclusion
- This article introduced you to some of the best Cloud ETL Tools available in the market that you can use to simplify ETL. It also provided in-depth knowledge about their features, use cases and pricing.
- You can also look for the best ETL tools that are available in the market and leverage one of these to boost your productivity based on your requirements.
- If you’re looking for an all-in-one solution, that will not only help you transfer data but also transform it into analysis-ready form, then Hevo Data is the right choice for you!
- It will completely automate all your analytics needs, allowing you to focus on key business activities.
FAQ on Cloud ETL Tools
What is the best cloud ETL tool?
Choosing the best cloud ETL tool depends on your specific needs, but some of the top options in 2024 include AWS Glue, Google Cloud Dataflow, Azure Data Factory, and Hevo Data.
Is AWS Glue ETL or ELT?
AWS Glue is primarily an ETL (Extract, Transform, Load) tool. It automates data extraction, transformation, and loading, making it easier to prepare and move data for analytics.
Which ETL tool is in demand in 2024?
As of 2024, some of the most in-demand ETL tools include Hevo Data, AWS Glue, Databricks, and Azure Data Factory. These tools are popular due to their scalability, ease of use, and integration capabilities with various data sources and services.
Is Snowflake an ETL tool?
Snowflake is not primarily an ETL tool; it’s a cloud data platform. However, it has built-in data transformation capabilities and can work seamlessly with ETL tools like Hevo Data, Matillion, and Talend to provide a complete data pipeline solution.
Share your experience of learning about various Cloud ETL Tools! Let us know in the comments section below.
Divij Chawla is interested in data analysis, software architecture, and technical content creation. With extensive experience driving Marketing Operations and Analytics teams, he excels at defining strategic objectives, delivering real-time insights, and setting up efficient processes. His technical expertise includes developing dashboards, implementing CRM systems, and optimising sales and marketing workflows. Divij combines his analytical skills with a deep understanding of data-driven solutions to create impactful content and drive business growth.