List of the Top 6 ETL Software for IRI Voracity in 2025

Snowflake is a comprehensive, cloud-based data platform designed to simplify data management, storage, and analytics for businesses of all sizes. With a unique architecture that separates storage and compute resources, Snowflake offers users the ability to scale both independently based on workload demands. The platform supports real-time analytics, data sharing, and integration with a wide range of third-party tools, allowing businesses to gain actionable insights from their data quickly. Snowflake's advanced security features, including automatic encryption and multi-cloud capabilities, ensure that data is both protected and easily accessible. Snowflake is ideal for companies seeking to modernize their data architecture, enabling seamless collaboration across departments and improving decision-making processes.

Apache Hive serves as a data warehousing framework that empowers users to access, manipulate, and oversee large datasets spread across distributed systems using a SQL-like language. It facilitates the structuring of pre-existing data stored in various formats. Users have the option to interact with Hive through a command line interface or a JDBC driver. As a project under the auspices of the Apache Software Foundation, Apache Hive is continually supported by a group of dedicated volunteers. Originally integrated into the Apache® Hadoop® ecosystem, it has matured into a fully-fledged top-level project with its own identity. We encourage individuals to delve deeper into the project and contribute their expertise. To perform SQL operations on distributed datasets, conventional SQL queries must be run through the MapReduce Java API. However, Hive streamlines this task by providing a SQL abstraction, allowing users to execute queries in the form of HiveQL, thus eliminating the need for low-level Java API implementations. This results in a much more user-friendly and efficient experience for those accustomed to SQL, leading to greater productivity when dealing with vast amounts of data. Moreover, the adaptability of Hive makes it a valuable tool for a diverse range of data processing tasks.

For over forty years, IRI CoSort has established itself as a leader in the realm of big data sorting and transformation technologies. With its sophisticated algorithms, automatic memory management, multi-core utilization, and I/O optimization, CoSort stands as the most reliable choice for production data processing. Pioneering the field, CoSort was the first commercial sorting package made available for open systems, debuting on CP/M in 1980, followed by MS-DOS in 1982, Unix in 1985, and Windows in 1995. It has been consistently recognized as the fastest commercial-grade sorting solution for Unix systems and was hailed by PC Week as the "top performing" sort tool for Windows environments. Originally launched for CP/M in 1978 and subsequently for DOS, Unix, and Windows, CoSort earned a readership award from DM Review magazine in 2000 for its exceptional performance. Initially created as a file sorting utility, it has since expanded to include interfaces that replace or convert sort program parameters used in a variety of platforms such as IBM DataStage, Informatica, MF COBOL, JCL, NATURAL, SAS, and SyncSort. In 1992, CoSort introduced additional manipulation capabilities through a control language interface modeled after the VMS sort utility syntax, which has been refined over the years to support structured data integration and staging for both flat files and relational databases, resulting in a suite of spinoff products that enhance its versatility and utility. In this way, CoSort continues to adapt to the evolving needs of data processing in a rapidly changing technological landscape.

The IRI Data Manager suite, developed by IRI, The CoSort Company, equips users with comprehensive tools designed to enhance the efficiency of data manipulation and transfer. IRI CoSort is adept at managing extensive data processing activities, including data warehouse ETL and business intelligence analytics, while also facilitating database loads, sort/merge utility migrations, and other substantial data processing operations. For swiftly unloading vast databases for data warehouse ETL, reorganization, and archival purposes, IRI Fast Extract (FACT) stands out as an indispensable tool. With IRI NextForm, users can accelerate file and table migrations, while also benefiting from features like data replication, reformatting, and federation. IRI RowGen is capable of producing test data that is both referentially and structurally accurate across files, tables, and reports, and it also offers capabilities for database subsetting and masking, tailored for test environments. Each of these products can be acquired separately for perpetual use and operates within a shared Eclipse job design integrated development environment, with additional support available through IRI Voracity subscriptions. Together, these tools streamline complex data workflows, making them essential for organizations seeking to optimize their data management processes.

Streamline the centralization, transformation, and storage of your data with ease. Logstash acts as a free and open-source server-side data processing pipeline, adept at ingesting data from a multitude of sources, transforming it, and routing it to your chosen storage solution. This tool proficiently manages the entire process of data ingestion, transformation, and delivery, accommodating a wide array of formats and complexities. With the use of grok, you can extract structured information from unstructured data, decipher geographic coordinates from IP addresses, and protect sensitive information by either anonymizing or omitting certain fields, thus facilitating simpler data processing. Data often resides in disparate systems and formats, leading to silos that impede effective analysis. Logstash supports numerous input types, allowing for the concurrent collection of events from various common and diverse sources. It enables the effortless gathering of data from logs, metrics, web applications, data repositories, and an assortment of AWS services, all in a continuous streaming fashion. With its powerful features, Logstash equips organizations to effectively consolidate their data landscape, enhancing both accessibility and usability. You can explore more about Logstash and download it from this link: https://sourceforge.net/projects/logstash.mirror/.

A rapid extract process can serve as a vital element in various scenarios, including: database archiving and replication database reorganizations and migrations data warehouse ETL, ELT, and operational data store activities offline reporting and extensive data safeguarding IRI Fast Extract (FACT™) functions as a parallel unloading tool specifically designed for handling very large database (VLDB) tables within several systems, such as: Oracle, DB2 UDB, MS SQL Server Sybase, MySQL, Greenplum Teradata, Altibase, Tibero Using straightforward job scripts supported by an intuitive Eclipse GUI, FACT swiftly generates portable flat files. The efficiency of FACT is attributed to its use of native connection protocols and a proprietary split query method that enables the unloading of billions of rows in mere minutes. While FACT operates independently as a standalone utility, it also integrates well with other applications and platforms. For instance, FACT can generate metadata for data definition files (.DDF) that can be utilized by IRI CoSort and its compatible data management and protection solutions, allowing for streamlined manipulation of flat files. Additionally, FACT automatically produces configuration files for database loading utilities tailored to the original source. Furthermore, FACT is an optional, seamlessly integrated part of the IRI Voracity ETL and data management platform, enhancing its functionality. The automatic generation of metadata, along with the ability to coexist with other IRI software within the same integrated development environment, further optimizes user workflows and data handling processes.