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The two types of ETL tools
ETL tool updates evolve as quickly as you can produce your data, so the ETL market has changed considerably over the past 10 years.
The first ETL tools — traditional ETL systems — were initially parts of database or warehouse software. These tools use batch processing, can take longer to upload data, but they have the advantage of greater oversight into data.
The latest cloud and SaaS systems are stand-alone ETL tools that work as a layer in between source systems or databases and the data warehouse or BI tools. This software can work faster, but they are somewhat more error-prone than batch processing.
Recommendations for the best ETL and BI tools
This article covers the best ETL tools in both categories, and includes information from public reviews of the tools from around the web.
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Traditional ETL tools
Informatica PowerCenter
Overview
PowerCenter by Informatica is an enterprise integrated data platform that connects data from across the enterprise. Connect to any type of data from databases, warehouses, or cloud apps and make that data available for analysis or use. Automated validation testing alerts users to problems quickly.
Pros
- Visual interface, drag and drop setup
- High daily record migration (up to 5 million records)
Cons
While this is a powerful tool, reviewers have expressed disappointment with support, especially if your team cannot produce complete logs. Others have expressed issues resulting from unexplained missed records that don’t load. Informatica does not include parallel functionality, and you cannot schedule load jobs in the workflow.
SAP Cloud Platform Integration
Overview
The SAP Cloud Platform Integration tool provides real time and asynchronous access to data across SAP and third-party apps. The integration also connects on-premise and cloud assets for use in a data warehouse or BI environment.
Pros
- Uses the ODATA REST protocol like all other SAP products, which makes integrating data across SAP tools easy.
Cons
Reviewers have said that SAP Cloud Platform Integration does not support real-time jobs as well as their asynchronous data uploads. Some users have also found the tools to have a steep learning curve, and they are not recommended for novice users.
Oracle Data Integrator
Overview
The Oracle Data Integrator (ODI) is a comprehensive ETL tool for loading data into a big data warehouse. The tool is designed for large data transfers and transformations across systems. ODI works best with Oracle databases and within the Oracle Enterprise Manager.
Pros
- Connect apps quickly
- Choose from a wide variety of big data connectors
- The tools are easy to use
Cons
Reviewers found the multiuser development environment is not as robust as they’d like. Oracle Data Integrator does not support real-time data transfers, and internal security controls lack sophistication.
Microsoft Azure Data Factory
Overview
Microsoft Azure Data Factory is a visual workflow interface for building data warehouses from complex apps and data connectors. Import data with over 80 pre-made connections or use a template from the library to build workflows.
Pros
- Easily create hybrid clouds
- Integrate with power bi and other Microsoft apps
- Deploy quickly
Cons
Reviewers have mentioned that the Azure security and access controls could be expanded, and while the tool has a visual interface, the interface is complex and not designed for novice users.
The best SaaS ETL tools
FiveTran
Overview
FiveTran is an ETL that automatically detects your data schema and takes only minutes to set up. Connect your data sources via account authentication and start streaming your data into a new data center quickly.
Pros
- Easy to use interface that doesn’t restrict access to data pros
- Templated data transformations to speed up transfer
Cons
Reviewers have shared they wish there was more visibility into job loads. For example, if you load a huge file or set of files you don’t have visibility into the job progress as it’s moving and can only access the log files when the job is complete. This can result in periodic delays in data uploads without support.
Alooma
Overview
Alooma brings disparate data sources together into BigQuery, Redshift, or Snowflake. Write custom code to cleanse data, then use the automatic mapping tools to quickly ready your data for transfer.
Pros
- Alooma’s data transfers are fast and easy to use
- Connect data through native connections or API
- Make use of the responsive support team to add new connections
Cons
As with FiveTran, reviewers have mentioned that Alooma doesn’t provide much visibility into data progress once you start a job in the pipeline.
Striim
Overview
Striim uses change data capture (CDC) technology to understand changes in your data and update your databases based on those changes. The tool provides real-time insight into your data for fast-paced decision making.
Pros
- With a low price point, this tool is good for small businesses
- Access to helpful support
- The in-memory platform means you can access continuous data uploads
Cons
Reviewers have found Striim is unstable when they try to upload large batches of data. Because of this, they’ve found that the tool is appropriate for small business use but may not be appropriate for enterprise companies.
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