What is CloverETL used for?

CloverETL is used to move data between any number of different systems and databases. It is highly configurable, extremely fast and saves considerable time and effort not just in the development of data transformations and migrations but also for ongoing maintenance.

Any situation where you need to move and manipulate small or huge amounts of data are well suited to CloverETL. Common data processes such as Imports, Exports, Data Integration, Data Migration, Data Warehousing, SOA implementations can all be tackled with ease.

How does CloverETL work?

CloverETL uses a few key concepts to describe how data is to be manipulated. Users compose a visual description of data processing algorithm called transformation graph. The graphs are composed from existing building blocks - components - in Clover Designer, the heart of all CloverETL Editions. It provides an easy way of graphically laying out even complex data transformations. Drag and drop from our palette of data transformation components and then configure them.

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Accessing Data

Clover offers components that can read a variety of data sources. All JDBC/ODBC databases are supported, including special high speed data pumps. Flat files have comprehensive support such that every structured and many loosely structured data sources can be read in. Special formats such as LDAP, XML, dBase, Excel and others are also catered for.

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Data Transfer

Data can be read both from local systems as well as network facilities using UNC paths, HTTP, FTP, SFTP, and JMS protocols. Therefore you can move your data without having to use 3rd party tools or custom procedures to prepare it.

Transformation Components

Standard set of CloverETL components covers all common data operations: sorting, merging, joining, deduping, filtering, aggregations and more.

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Performance

Many of our customers have run their own independent assessments of Clover's performance. And each time, Clover is shown to deliver the highest performance in most benchmarks. Vendor benchmarks are rather arbitrary and are very hard to interpret or relate to and of course they are chosen to highlight the strengths and avoid the weaknesses.

If you have already set up benchmarks of your data we will provide assistance is setting up a Clover data transformation to allow you to compare performance on your own hardware. We are confident you will be impressed with the results.

Performance Benchmarking Datasheet →

Product Editions

Clover editions are designed to meet the different needs most organizations face. Based on your project size Clover scales from the single-user Desktop Edition to the Enterprise and Cloud Editions providing solid base for larger ETL undertakings. All Clover software runs on Windows, Mac, Linux, Unix (AIX, Solaris, HP-UX) as well as iSeries (AS/400).
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