7 Great ETL Tools For 2022
Companies in all industries and of all sizes now deal with an ever-increasing amount of data, far beyond human comprehension. This vital information is rendered practically useless unless you have an efficient way to process and analyze it to reveal valuable insights within the clutter. The ETL (extract, transform, load) process collects data from multiple sources such as spreadsheets, files and databases and loads it into a centralized data warehouse.
As important as ETL tools are to your company, they are all created for different situations. The best ETL tool for your business depends on your situation. These are seven great ETL tools for 2022 you may want to consider:
- Infromatica
- Talend
- Matillion
- Google Data Flow
- Airflow
- Azure Data Factory
- Dataddo
Why Companies Use ETLs
Companies use ETL tools because they are much easier, faster and more efficient than traditional methods of manually moving data through written code. ETL tools employ graphical interfaces that speeds up the process of mapping tables and columns between source data and final storage space. This allows quick access all in one place and helps to create a comprehensive support system needed for critical decisions.
Additionally, ETL tools provide clear and filtered data structures that can be exploited by a variety of end-user tools, which increases the value and quality of the data for optimum decision making. Transactional databases are not capable of answering such complex business queries.
The data warehouse is updated automatically and keeps an extensive history while collecting vast amounts of historical data that can be analyzed for different time periods to help identify trends for future predictions. The data is integrated from many sources to reduce processing and total response time, while facilitating the preparation of detailed reports.
1. Informatica
Informatica smoothly blends four data engineering products into one system, which makes it one of the most powerful and feature-rich ETL platform on the market. However, this also makes it the most complicated. By combining data management, integrated apps, an API gateway and specialized iPaaS features, small or inexperienced teams may find Informatica too difficult to handle and may opt for a simpler solution.
While Informatica optimizes monitoring, data design, workflow management and repository management, the platform requires the skills of certified data engineers, making it a better choice for larger companies that have a bigger tech budget. When you add in other expenses such as hardware and server management, the overall cost can really add up quickly.
2. Talend
Talend allows you to easily handle all stages of the Data Lifecycle. It is a comprehensive, open-source ETL solution. This platform is compatible with on-premises data sources as well as cloud-sourced data. It comes complete with hundreds of integrations already built and ready to go.
While most users find the open-source version of Talend more than adequate for their needs, larger companies may prefer the paid version. The paid version includes more tools and additional features for data design, governance, management, monitoring and productivity.
Talend averages a 4 out of 5 star rating on G2, plus rave reviews from users naming it a great all-around data integration tool with a clear and concise interface.
3. Matillion
The Matillion solution is an extract, transform, load (ETL) tool used by many large cloud-based data warehouses including Google BigQuery, Snowflake and Amazon Redshift. The powerful platform enables users to collect all types of data from a variety of sources and delivers it in structured and semi-structured frameworks. The search function allows companies to find specific results within all projects in the system.
Key features of Matillion include data export/import, collaboration, audit logs, scripting, job scheduling, version control and task management. Businesses can use the automation tools to schedule multiple orchestration jobs against a project at predefined time intervals. Plus, it enables administrators to ensure data security by managing user access across directories.
4. Google Data Flow
Google Data Flow is a fully-managed solution that smoothly executes the Apache Beam Pipeline within the Google Cloud ecosystem. The service offers large-scale data processing capabilities with real-time computation. It can help you minimize the processing time, improve latency and reduce cost through autoscaling and batch processing.
Key features of Google Data Flow include the ability to simplify the fast Streaming Data Pipeline development with lower Data Latency when compared to the competition and real-time AI capabilities that enable real-time reactions with human-like intelligence. Customers are able to build intelligent solutions that range from anomaly detection and predictive analytics to real-time personalization and other advanced analytics.
5. Airflow
Airflow isn’t technically an ETL tool, but it does manage, structure and organize ETL pipelines by the use of Directed Acyclic Graphs (DAGs). This metadata database stores workflows, tasks and is completely scalable. It employs a modular architecture that creates a message queue for more efficient handling of large amounts of data.
Airflow pipelines are defined in Python, which allows for dynamic pipeline generation. This allows you to easily define operators and expand your libraries to fit the level of abstraction that suits your environment.
The easy-to-understand interface helps you monitor, schedule and manage your workflow through a robust web application. You don’t need to learn antiquated interfaces. This makes Airflow easy to apply to your current infrastructure and easily extend it to next generation technologies.
6. Azure Data Factory
Azure Data Factory is a well-known serverless and fully-managed Data Integration service. It allows you to easily build ETL processes in an intuitive environment without previous coding knowledge. Then, you can deliver integrated data to Azure Synapse Analytics to reveal valuable insights to help make informed business decisions for growth and increased productivity.
Azure Data Factory offers affordable pay-as-you-go pricing and lets you ingest all of your software data and Software as a Service (SaaS) with more than 90 built-in connectors.
7. Dataddo
Dataddo is a no-code, cloud-based ETL platform that puts flexibility first. It it fully equipped with a wide range of connectors and fully customizable metrics. The platform simplifies the process of creating and implementing an automated data pipeline. Dataddo is capable of seamlessly integrating with your existing data stack, eliminating the need for extra software. The intuitive interface and simple set-up lets you focus on consolidating your data instead of wasting time learning new procedures. The API changes are fully managed so once your pipelines are set, you don’t have to worry about them again. If you need a connector that isn’t provided by Dataddo, it can be easily added within 10 days.
Conclusion
These are seven of the best ETL tools currently available on the market. Only you can really be the judge of which one is best for you, based on your requirements and budget. You can easily implement one of these solutions to boost your productivity and data management through a clear improvement in the efficiency of your operations.
Extracting complex data from various, diverse data sources can be a complex and challenging task. ETL tools make the process quick and easy!
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