In my last blog, we talked about Open Source Data Extraction Tools. The main objective of an “ETL tool” is to gather the content of various databases or operational systems across your organization and move/copy/transfer all this data into a centralized database. This “centralized database” is often named a “Data warehouse”. Alternatively, ETL tools are also used to perform complex data transformations that are difficult to make using simple SQL statements.
Here’s list of some Commercial ETL tools:
It is an ETL tool and part of IBM information Platforms Solutions suite and IBM InfoSphere. It uses a graphical notation to construct data integration solutions. It integrates data across multiple systems using a high performance parallel framework, and it supports extended metadata management and enterprise connectivity. The scalable platform provides more flexible integration of all types of data, including big data at rest (Hadoop-based) or in motion (stream-based), on distributed and mainframe platforms.
Microsoft SQL Server Integration Services (SSIS) –
Microsoft SSIS is an enterprise data integration, data transformation and data migration tool that is built into Microsoft’s SQL Server data base. It can be used for a variety of integration-related tasks, such as analyzing and cleansing data and running extract, transform and load processes to update data warehouses.
Adeptia offer full ETL functionality combined with an easy, intuitive interface; giving users the ability to transform a number of different files. Adeptia ETL Suite is designed for non-IT persons even, giving the business users power to access their data in real-time and transform their own data to fit their operations, while still allowing IT to manage processes and ensure that data is managed securely and correctly.
Informatica Powercenter –
Informatica Power Center is a widely used extraction, transformation and loading tool used in building enterprise data warehouses. The main components of Informatica PowerCenter are its client tools, server, repository server and repository. The Power Center server and repository server make up the ETL Layer, which completes the ETL processing.
Data Migrator is a powerful and comprehensive automated tool designed to dramatically simplify extract, transformation, and load (ETL) processes, including the creation, maintenance, and expansion of data warehouses, data marts and operational data stores. An intuitive interface enables fast end-to-end ETL process creation involving heterogeneous data structures across disparate computing platforms. Additionally, a change data capture feature loads only changed records into your data source, dramatically reducing the time needed to refresh data, and facilitating a near-real-time data warehouse.
See Also: The Big Data Gray Area – Do’s and Don’ts
Elixir Data ETL –
Elixir Data ETL is designed to provide on-demand, self-serviced data manipulation for business users as well as for enterprise level data processing needs. Its visual -modelling paradigm drastically reduces the time required to design, test and implement data extraction, aggregation and transformation – a critical process for any application processing, enterprise reporting and performance measurement, data mart or data warehousing initiatives.
Syncsort DMX brings all data transformations into a higher performance, in-memory ETL engine. Transformations are processed on the fly, eliminating the need for costly database staging areas or manually pushing transformations to the database.
SAS Data Management –
SAS Data Management enables your business users to update data, tweak processes and analyze results themselves, freeing up for other projects. Plus, a built-in business glossary as well as SAS and third-party metadata management and lineage visualization capabilities keep everyone on the same page.
SAP Data Services –
It helps integrate, transform, and improve data at the project or enterprise level. It delivers a single enterprise class solution for data integration, data quality, data profiling, and text data processing that allows users to integrate, transform, improve, and deliver data.
ORACLE DATA INTEGRATOR ENTERPRISE EDITION –
It delivers Extract Load and Transform (E-LT) technology that improves performance and reduces data integration costs – even across heterogeneous systems. Provides high-performance and lower TCO, Heterogeneous platform support for enterprise data integration and knowledge modules for optimized developer productivity and extensibility.
Meta Suite –
Meta Suite offers you fast time-to-value, scalability and a rich choice of supported source and target file and database types. Other than the normal operation of extract, load and merge operational data, it can also be used to consolidate and rationalize data and deliver as such support for Master Data Management.
Read Also: A Beginner’s Guide to Big Data Analytics
It is now part of Actian. It performs complex integration operations, although the software is remarkably easy-to-use and doesn’t require a specialized skill set. Its rich features are highly intuitive and configurable for design, deployment and management – without the sticker shock. It has the same full-featured web UI used for both on premise and cloud versions.
Sagent Data Flow –
It is a powerful and flexible integration engine that collates data from disparate sources. It is designed by Pitney Bowes Software and provides a comprehensive set of data transformation tools to enhance its business values. It allows for analyzing information and creating meaningful reports to aid understanding of your business
Also Read: Top 15 Big Data Tools in 2017
Choosing any software or tool is decided by what type of requirement does one have and which varies from business to business. A telecom business would have large and complex data to handle in comparison to clothes retail store. So, a telecom business would select a tool which has features to operate on complex data. Whereas, a retail store would go for easy to use tool with less complexities, as it doesn’t have the programming skills and technical background.
In my next blog, I would list tools for the next layer in the Reference Architecture.