Best ETL Tools & Software 2023
Future ETL will be providing a data management framework – comprehensive and hybrid approach for managing big data. ETL solutions will encompass not only data integration but also data governance, data quality, and data security. Also, help in automating the process of data processing and designing.
Thus, an expert in this skill will have plenty of job roles to play. There are multiple companies to hire these skills. In this way, we can say that this popular ETL software will have a good demand in the future IT market.
The best ETL tools
ETL tools can work in either cloud or on premises IT environments; they also come in either proprietary or open source software. Here are some of the most popular ETL tools in those categories.
- AWS Glue
- Azure Data factory
- Google Cloud Dataflow
- InfoSphere DataStage
- Oracle Data Integrator
- Informatica PowerCenter Mapping Designer
ETL in the cloud
AWS Glue is a nice fit for companies that use SQL databases, AWS and Amazon S3 storage services. AWS Glue enables you to clean, validate, organize and load data from disparate static or streaming data sources into a data warehouse or a data lake. It also allows you to process semi-structured data such as clickstream (e.g., website hyperlinks) and process logs. Its strength is in its ability to work with SQL, which many companies have competence in. On the programming side, AWS Glue executes jobs using either Scala or Python code.
With AWS Glue, you can schedule ETL jobs based on a schedule or event, or you can trigger jobs as soon as data becomes available. AWS Glue is an on-demand tool that automatically scales to accommodate the processing and storage resources that you need, and that gives you visibility of runtime metrics while it processes.
AWS Glue integrates well with other AWS systems and processes, so if AWS is your primary data repository and processor, AWS Glue works well. It also has APIs for third party JDBC (JAVA)-accessible databases like DB2, MySQL, Oracle, SyBase, Apache Kafka and MongoDB.
AWS offers free online courses. It also provides certification programs. Pricing is free for the first million accesses/objects stored and is billed on a monthly basis that is based upon usage thereafter.
Azure Data Factory
Azure Data Factory is a pay-as-you-go cloud-based ETL tool that automatically scales processing and storage to meet your data and processing demands. Its strength is that it can be used by both IT professionals and end users. This is because the tool has both a no-code graphical user interface for end users and a code-based interface for IT. Both code and no-code interfaces feature data pulls from more than 90 connectors. Among these connectors are AWS, DB2, MongoDB, Oracle, MySQL, SQL, SyBase, Salesforce and SAP.
Azure Data factory is a nice choice for Microsoft shops, and for companies that want both their business end users and IT group to have access to ETL tools that enable them to pull data into data repositories.
Microsoft offers free online training. It also offers certifications for Azure Data Factory. Its standard technical support package provides 24×7 access to support engineers via email and phone, with a guaranteed response time that is within one hour. Pricing is based on usage.
Google Cloud Dataflow
Google Cloud Dataflow is part of the Google Cloud platform, and is well integrated with other Google services. Dataflow uses ApacheBeam open source technology to orchestrate the data pipelines that are used in DataFlow’s ETL operations. Google Cloud Dataflow requires IT expertise in SQL databases, and in the Java and Python programming languages.
This software can be deployed for both batch and real-time processing, and in either a scheduled or a real-time on demand mode. Because Google Cloud Dataflow is cloud-based, it can automatically scale to accommodate the processing and storage that you need for any ETL job. Google Cloud Dataflow is ideal for shops that heavily use the Google Cloud platform.
Through its Cloud Academy, Google offers a free online tutorial on Dataflow, offers hands-on training at $34/month and a Google certification program at $39/month.
Google Cloud has several technical support options that start at the Basic Level (billing/payment support) and increase to Standard (unlimited technical support), Enhanced (faster response technical support) and Premium support (a dedicated support representative). Pricing is based on usage.
IBM InfoSphere DataStage
InfoSphere DataStage is part of the IBM Information Server Platform. It uses a client/server design where jobs are created and administered via a Windows client against a central repository on a server. This server can be Intel-based, UNIX-based, LINUX-based or even an IBM mainframe.
Regardless of platform, the IBM InfoSphere DataStage ETL software can integrate data on demand across multiple, high volumes of data sources and can target applications using a high performance parallel framework. InfoSphere DataStage also facilitates extended metadata management and enterprise connectivity.
InfoSphere DataStage is well suited for large enterprises that have mainframes or large servers, and high volume processing and data. These organizations tend to run on multiple clouds, and also in on premises data centers. The connecters supported by IBM InfoSphere DataStage range from AWS, Azure and Google, to SyBase, Hive, JSON, Kafka, Oracle, Salesforce, Snowflake, Teradata and others.
IBM InfoSphere DataStage is a robust ETL solution, and also a costly one. This tool is designed for IT professionals who have a sound understanding of SQL and also knowledge of the BASIC programming language, which InfoSphere DataStage uses.
IBM offers pay-for online and classroom training and certifications for DataStage. It also provides 24/7 technical support packages. Pricing is available upon request.
Oracle Data Integrator
Oracle Data Integrator (ODI) is a strong platform for larger enterprises that run other Oracle applications such as Enterprise Resource Planning (ERP). ODI is designed to move data from point to point across an entire company’s business functions. Like ERP, it can support integrated workflows across entire organizations.
ODI can process data integration requests that range from high-volume batch loads to service-oriented architecture (SOA) data services that enable software components to be called and reused in new processes. ODI also supports parallel task execution for faster data processing and offers built-in integrations with other Oracle tools, such as Oracle GoldenGate and Oracle Warehouse Builder.
ODI ETL software supports data integration for both structured and unstructured data. It supports relational databases, and has a library of APIs for third party data and applications. On the big data side, ODI also supports Spark Streaming, Hive, Kafka, Cassandra, HBase, Sqoop and Pig. ODI is a sophisticated and proprietary tool that requires IT expertise and experience in Java programming.
On a subscription basis, Oracle offers access to online training and certifications for ODI. Technical support is available, and will be added to licensing fees. Pricing is license based.
Informatica PowerCenter Mapping Designer
Informatica PowerCenter is an enterprise-strength ETL tool that is best utilized by large organizations with the need to move data across many different business functions. PowerCenter extracts, transforms and loads data from a variety of different structured and unstructured data sources that span internal and external (cloud-based) enterprise applications. PowerCenter has many APIs to variety of different third party applications and data.
Common data formats that PowerCenter works with include JSON, XML, PDF and Internet of Things (IoT) machine data. PowerCenter can work with many different third party databases, such as SQL and Oracle database. PowerCenter will transform data based upon the transformation rules that are defined by IT.
Informatica PowerCenter furnishes a user-friendly graphical interface that is designed for the use of business users, but the tool is best used by IT, as it is highly sophisticated. PowerCenter can automatically scale to meet processing and data needs at the same time that it works to optimize performance.
Although PowerCenter is a proprietary ETL tool, it can work in both cloud and on premises environments.
Informatica offers PowerCenter online training subscriptions and provides learning paths for developers, administrators and data integrators through its Informatica University. It also offers technical support options that companies can subscribe to. Pricing is based upon usage.
What is an ETL tool?
Today, data analytics plays a major role in corporate decision making. It is able to do this because data is culled from a variety of sources and then assembled in a single data repository that corporate decision makers can access. When data is combined from different areas throughout the company, corporate decision makers get a 360-degree view of what is going on. This enables them to make more informed decisions.
For example, if a vice president of sales wants to know why a certain product isn’t selling well, he/she can query a central data analytics repository which contains all of the information on that particular product from throughout the enterprise.
The sales VP can see the customer complaints about the product that customer service logged, as well as the number of product returns that the warehouse processed. He/she can also see that engineering is working on a revision of the product to cure the defects that have been reported. The VP now has a thorough understanding of why the product hasn’t been doing as well in revenues as was projected.
How do ETL tools work?
ETL software obtains data from one source, transforms the data into a form that is acceptable for another source and then moves the data to the new target source. ETL software is an automated software tool. When companies use ETL software, they no longer have to convert data from one source to another by hand. This saves time, effort and manual errors.
What do you need the ETL for?
Are you going to be pulling data from different sources that range from unstructured or semi-structured IoT data to legacy system data that resides on internal servers and mainframes? Or is your company almost wholly cloud-based, with a clear preference for an ETL solution that operates within the cloud where most of your data and applications are hosted? What if your company has data and systems that are both on premises and cloud based? What’s the best choice for that scenario?
How do you want to prepare your data?
Is the generic formatting (system to system or database to database) that your ETL tool comes pre-packaged with going to meet your data cleaning and formatting needs, or do you need to add extra edit rules to data?
How well can you support and leverage your ETL tool?
If you are a smaller company, do you have skilled personnel on board who are trained in ETL methods and tools? Even if you have this personnel on board, do you have a need to also have your non-IT end business users use the ETL software?
Data integration is one of the most persistent challenges for IT teams. What ETL tools bring to the table is a simplified way of moving data from system to system and from data repository to data repository. These ETL tools comes in a wide variety of flavors that can meet the needs of enterprises with complex data and system integration needs in hybrid environments to smaller companies that lack IT expertise and must watch their budgets. The ETL tool your business chooses will depends on its specific use cases and budget.