List of the Top 8 Big Data Platforms for IRI DMaaS 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.

MongoDB is a flexible, document-based, distributed database created with modern application developers and the cloud ecosystem in mind. It enhances productivity significantly, allowing teams to deliver and refine products three to five times quicker through its adjustable document data structure and a unified query interface that accommodates various requirements. Whether you're catering to your first client or overseeing 20 million users worldwide, you can consistently achieve your performance service level agreements in any environment. The platform streamlines high availability, protects data integrity, and meets the security and compliance standards necessary for your essential workloads. Moreover, it offers an extensive range of cloud database services that support a wide spectrum of use cases, such as transactional processing, analytics, search capabilities, and data visualization. In addition, deploying secure mobile applications is straightforward, thanks to built-in edge-to-cloud synchronization and automatic conflict resolution. MongoDB's adaptability enables its operation in diverse settings, from personal laptops to large data centers, making it an exceptionally versatile solution for addressing contemporary data management challenges. This makes MongoDB not just a database, but a comprehensive tool for innovation and efficiency in the digital age.

Elastic is a prominent search technology firm that has created a suite known as the Elastic Stack, which includes Elasticsearch, Kibana, Beats, and Logstash. These software-as-a-service solutions enable users to leverage data for real-time analytics, security measures, search functionalities, and logging at scale. With a community of over 100,000 members spread across 45 nations, Elastic's products have been downloaded more than 400 million times since their launch. Currently, numerous organizations, including notable names like Cisco, eBay, Dell, Goldman Sachs, Groupon, HP, Microsoft, Netflix, Uber, Verizon, and Yelp, rely on Elastic Stack and Elastic Cloud to enhance their critical systems, driving significant revenue growth and reducing costs. Headquartered in both Amsterdam, The Netherlands, and Mountain View, California, Elastic employs a workforce of more than 1,000 individuals across more than 35 countries, contributing to its global impact in the tech industry. This extensive reach and adoption highlight Elastic's vital role in transforming how enterprises manage and utilize their data.

IRI Voracity is a comprehensive software platform designed for efficient, cost-effective, and user-friendly management of the entire data lifecycle. This platform accelerates and integrates essential processes such as data discovery, governance, migration, analytics, and integration within a unified interface based on Eclipse™. By merging various functionalities and offering a broad spectrum of job design and execution alternatives, Voracity effectively reduces the complexities, costs, and risks linked to conventional megavendor ETL solutions, fragmented Apache tools, and niche software applications. With its unique capabilities, Voracity facilitates a wide array of data operations, including: * profiling and classification * searching and risk-scoring * integration and federation * migration and replication * cleansing and enrichment * validation and unification * masking and encryption * reporting and wrangling * subsetting and testing Moreover, Voracity is versatile in deployment, capable of functioning on-premise or in the cloud, across physical or virtual environments, and its runtimes can be containerized or accessed by real-time applications and batch processes, ensuring flexibility for diverse user needs. This adaptability makes Voracity an invaluable tool for organizations looking to streamline their data management strategies effectively.

SAP HANA is a cutting-edge in-memory database that efficiently manages both transactional and analytical workloads by utilizing a single data copy, regardless of its nature. It effectively eliminates the divide between transactional and analytical functions within businesses, allowing for quick decision-making whether used in a traditional data center or through cloud services. This advanced database management system grants users the ability to develop intelligent, real-time applications, which promotes fast decision-making from a consolidated data repository. By integrating sophisticated analytics, it bolsters the performance of modern transaction processing systems. Organizations can leverage cloud-native features such as enhanced scalability, speed, and performance to create comprehensive data solutions. With SAP HANA Cloud, businesses gain access to dependable and actionable insights from a unified platform while maintaining stringent security, privacy, and data anonymization that align with established enterprise standards. In the rapidly evolving market landscape, the intelligent enterprise increasingly depends on prompt insights generated from data, highlighting the necessity for real-time access to critical information. As organizations face rising expectations for immediate insights, adopting a powerful database solution like SAP HANA is essential for maintaining a competitive edge. The ability to make informed decisions based on real-time data is becoming a key differentiator in business success.

The Apache Hadoop software library acts as a framework designed for the distributed processing of large-scale data sets across clusters of computers, employing simple programming models. It is capable of scaling from a single server to thousands of machines, each contributing local storage and computation resources. Instead of relying on hardware solutions for high availability, this library is specifically designed to detect and handle failures at the application level, guaranteeing that a reliable service can operate on a cluster that might face interruptions. Many organizations and companies utilize Hadoop in various capacities, including both research and production settings. Users are encouraged to participate in the Hadoop PoweredBy wiki page to highlight their implementations. The most recent version, Apache Hadoop 3.3.4, brings forth several significant enhancements when compared to its predecessor, hadoop-3.2, improving its performance and operational capabilities. This ongoing development of Hadoop demonstrates the increasing demand for effective data processing tools in an era where data drives decision-making and innovation. As organizations continue to adopt Hadoop, it is likely that the community will see even more advancements and features in future releases.

Discover the capabilities of HPE Ezmeral Data Fabric Software offered as a fully managed service by signing up for a 300GB instance today, which allows you to delve into its newest features and functionalities. As organizations continue to spread their data across various sites, the need for high-quality, insightful data is climbing, with users desiring more thorough insights than ever before. Hybrid cloud solutions stand out as an exceptional choice, delivering advantages in cost efficiency, data distribution, workload management, and overall user satisfaction. A key benefit of this hybrid model is its capacity to match applications with the most appropriate services throughout their entire lifecycle. Nevertheless, this hybrid framework can also lead to increased complexities, such as limited data visibility, the requirement for various analytical formats, and potential rises in organizational risks and costs. Consequently, while embracing hybrid solutions provides the benefits of flexibility and scalability, it is crucial to carefully navigate these complexities to optimize performance and ensure success in the long run. Additionally, organizations must remain vigilant in addressing these challenges to fully leverage the advantages of a hybrid approach.

Manage and safeguard the complete data lifecycle from the Edge to AI across any cloud infrastructure or data center. It operates flawlessly within all major public cloud platforms and private clouds, creating a cohesive public cloud experience for all users. By integrating data management and analytical functions throughout the data lifecycle, it allows for data accessibility from virtually anywhere. It guarantees the enforcement of security protocols, adherence to regulatory standards, migration plans, and metadata oversight in all environments. Prioritizing open-source solutions, flexible integrations, and compatibility with diverse data storage and processing systems, it significantly improves the accessibility of self-service analytics. This facilitates users' ability to perform integrated, multifunctional analytics on well-governed and secure business data, ensuring a uniform experience across on-premises, hybrid, and multi-cloud environments. Users can take advantage of standardized data security, governance frameworks, lineage tracking, and control mechanisms, all while providing the comprehensive and user-centric cloud analytics solutions that business professionals require, effectively minimizing dependence on unauthorized IT alternatives. Furthermore, these features cultivate a collaborative space where data-driven decision-making becomes more streamlined and efficient, ultimately enhancing organizational productivity.