The PHEMI Trustworthy Health DataLab is a unique, cloud-based, integrated big data management system that allows healthcare organizations to enhance innovation and generate value from healthcare data by simplifying the ingestion and de-identification of data with NSA/military-grade governance, privacy, and security built-in. Conventional products simply lock down data, PHEMI goes further, solving privacy and security challenges and addressing the urgent need to secure, govern, curate, and control access to privacy-sensitive personal healthcare information (PHI). This improves data sharing and collaboration inside and outside of an enterprise—without compromising the privacy of sensitive information or increasing administrative burden. Built on privacy-by-design principles, the software gives researchers, scientists, and clinicians faster access to more information while ensuring that they only see data on a need-to-know basis. Responsible data sharing and a governance framework facilitate compliance with privacy regulations. PHEMI Trustworthy Health DataLab can scale to any size of organization, is easy to deploy and manage, connects to hundreds of data sources, and integrates with popular data science and business analysis tools. For more information, visit https://www.phemi.com/ and follow us on Twitter @PHEMISystems, Linkedin, Youtube, and Facebook

Prefect is modern workflow orchestration. Build, observe, and react to your data pipelines with a purely Python experience.

Apache AsterixDB is a scalable, open source Big Data Management System (BDMS).

Apache Fluo is an open source implementation of Percolator (which populates Google's search index) for Apache Accumulo.

DoubleCloud is winding down operations. The company ceased creating new accounts on October 1, 2024, and will completely close on March 1, 2025. DoubleCloud specialized in data analytics infrastructure, offering managed services for open-source data technologies. Throughout its operations, DoubleCloud provided tools for building data pipelines, including solutions for data ingestion, storage, orchestration, ELT, and real-time visualization. The company was committed to helping businesses streamline and optimize their data operations with powerful, open-source-based technologies.

InforData Lake tools deliver schema-on-read intelligence along with a fast, flexible data consumption framework to enable new ways of making key decisions. With leveraged access to your entire Infor ecosystem, you can start capturing and delivering big data to power your next generation analytics and machine learning strategies.

ITONICS provides the #1 Innovation Operating System (OS) for organizations seeking to operationalize innovation and drive growth systematically. Unlike traditional innovation management software, the ITONICS Innovation OS seamlessly connects foresight, ideation, and portfolio activities with your strategic goals in one collaborative system. Centralize your innovation intelligence, break down information silos, align efforts, and steer decision-making to move from strategy to execution with speed and agility. Whether you are looking to discover emerging opportunities, spark and nurture new ideas, or ensure the right innovation projects are resourced and delivered at the right time, ITONICS does it all. Radically upgrade your end-to-end innovation capabilities with intelligent environmental scanning, interactive data visualizations, configurable workflows for idea management, agile roadmaps, portfolios, and more. ITONICS ensures that you are set up for successful and sustainable innovation management. With ITONICS, you get access to our network of innovation experts, personalized training sessions, and 24/7 customer support. Embed the ITONICS Innovation OS into your daily workflows by seamlessly integrating the tools and apps you use daily. As an ISO-certified and GDPR-compliant company, ITONICS maintains the highest data security and privacy standards to protect your company data. Scale and accelerate innovation in your organization with the ITONICS Innovation OS. Find out more information here: https://www.itonics-innovation.com/

Kpow is a sophisticated enterprise Kafka management tool designed to enhance the experience of engineering teams by providing a comprehensive solution for managing, monitoring, exploring, and securing Kafka environments. This JVM-based web application serves as an all-in-one console, empowering Kafka engineers with the capabilities they need to streamline their operations and improve productivity. Targeted primarily at engineering teams working with Kafka, Kpow addresses the complexities of managing multiple Kafka clusters, schema registries, and connection installations. With Kpow, users can efficiently monitor and control their Kafka resources from a single interface, simplifying the management process and reducing the time spent on routine tasks. The tool is particularly beneficial for organizations that rely heavily on Kafka for data streaming and processing, as it provides essential functionalities that enhance observability and operational efficiency. One of the standout features of Kpow is its real-time monitoring and visualization capabilities. Users can quickly identify unbalanced brokers and gain insights into how data is distributed across their Kafka Streams topologies. This level of visibility is crucial for diagnosing production issues and optimizing performance. Kpow's advanced search functionalities, including Data Inspect, Streaming Search, and kREPL, enable users to search through vast amounts of messages at remarkable speeds, allowing for rapid troubleshooting and data analysis. Kpow also prioritizes security and access control, making it suitable for enterprise environments. It integrates seamlessly with standard authentication providers and offers role-based access controls, ensuring that user actions can be finely tuned to meet organizational security requirements. Additional security features, such as data masking and audit logs, further enhance the tool's capability to operate in sensitive environments, including air-gapped installations. Installation of Kpow is straightforward, requiring only a single Docker container or JAR file, which operates efficiently with minimal resource requirements of 1GB memory and 1 CPU for production use. This ease of deployment, combined with its powerful features, positions Kpow as a valuable asset for organizations looking to maximize their Kafka infrastructure while maintaining robust security and operational control.

Rayven's a low-code platform that enables you to build, deploy and scale powerful apps, AI tools + automations - fast. It's flexible, scalable, works with your existing technologies, and also gives you full-code control. Start building for free now using AI prompts, drag-and-drop tools, templates, or code (when you want) to. - Build apps, tools, automations + AI agents in minutes using templates or from scratch - Connect systems, unify data, and integrate them into what you build - in real-time - Connect and train LLMs with your data in the moment, then deploy anywhere - Modernise processes without replacing legacy tech or adding risk - Enable IT, Developers, DevOps, Ops, and Product teams to work from the same platform Rayven is designed for developers and non-technical users alike; giving you the all-in-one, low-cost tool to get from idea to outcome, fast. Start for free at rayven.io

TileDB is foundational software designed by scientists for scientific discovery. TileDB structures all data types, including data that does not fit into relational databases built for structured tabular data. Built on a powerful shape-shifting array database, TileDB handles the complexities of non-traditional “unstructured” multimodal data, such as genomic variants, bulk and single-cell transcriptomics, proteomics, biomedical imaging, as well as the frontier data of the future. Used by big pharma and biotechs to power their multiomic FAIR data platforms, TileDB is the destination for scientific breakthroughs where frontier multimodal data is driving drug and target discovery.

Alibaba Cloud Elastic MapReduce (E-MapReduce) is a big data processing solution to quickly process huge amounts of data. Based on open source Apache Hadoop and Apache Spark, E-MapReduce flexibly manages your big data use cases such as trend analysis, data warehousing, and analysis of continuously streaming data

Apache Falcon is a feed processing and feed management system designed to make it easier for end consumers to onboard their feed processing and feed management on hadoop clusters.

Apache Storm is a distributed, fault-tolerant, open-source, real-time event processing solution for large, fast streams of data.

Aparavi is THE Data Intelligence and Automation Platform. We help organizations find and unlock the value of data no matter where it lives to mitigate risk, reduce costs and exploit new value from their data. Our SaaS-based platform finds, automates, governs, and consolidates distributed data. We ensure secure access for modern data demands of analytics, machine learning, and collaboration. Aparavi connects business and IT to transform data into a competitive asset.

Bluemetrix's flagship management application, BDM Control, is a suite of data and governance control capabilities, which integrate with your data and governance processes to create a single view of your data governance and when applied to your data will apply, capture and extract the data access and governance enforcement data from your pipelines ad auto-populate your governance tools, ensuring they are up to date at all times. BDM allows a non-technical resource to build, schedule, transform, ingest and manage data pipelines inside Hadoop without having to write any code or know the underlying Hadoop environment. It applies automation to a range of different tasks so that the necessary code and commands are created and deployed as required. BDM fully compliments the Hadoop ecosystem and creates no proprietary code. It works exclusively on the Spark environment within Hadoop. BDM is a framework for the Ingestion, Masking, Translation, Transformation, Governance, Validation, Management and Quality Assurance of Data on Hadoop. Data Ingest ● Simple template-based Connector system for all data sources ● Multiple Connectors available ● No need to develop any ingest code or select appropriate Hadoop components ● New data sources can be deployed in hours rather than weeks or months ● Storage can be selected to suit the data type and processing requirement i.e. HIVE, HBase, etc. ● No extra code is developed, reducing the code release cycle time and complexity Data Masking/Tokenization ● Data Masking is available on ingest to the cluster; ● It can be carried out on a column or table basis ● Stateful and Stateless Tokenization solutions are available ● Different masking algorithms can be applied to suit the data i.e. ⮚ Complete removal of selected columns ⮚ Replace values with random data ⮚ Add a random value to each row in the table ⮚ Categorize data e.g. exact salary replaced with a range ⮚ Geolocation data – apply rotation methods to mask the data Data Quality & Validation ● Data Consistency is guaranteed by applying checksums and other controls on the data ● Data Integrity is provided by Regular Expression and ML algorithms ● All quality data is accessible through a dashboard which will provide a snapshot of the health of the data on the cluster Data Transformation ● Data transformations are coded and stored in a custom library deployed in Spark ● Data maps/flows can be created using a drag and drop interface ● Dramatic reduction in code developed and deployed ● Dramatic reduction in scripts developed ● No requirement for SQL skills or HIVE knowledge to transform the data ● No requirement for Spark expertise to create transformations ● An API can be provided to the Spark library allowing client developers create and deploy their own Spark transformations Data Governance & Lineage ● All data governance capabilities – Audit, Change Tracking, etc. – are built into Atlas ● Governance functionality can be easily customized to add new data and features i.e. addition of new GDPR compliance tags, etc. ● Process is completely independent of the end user and happens in the background ● Only solution with end-to-end data governance enabled on Atlas available in the market today As one of the first companies to use Hadoop in Europe in 2009, and since 2016 we have carried out over 400 Hadoop Big Data implementations across all major enterprises in Europe in all industry sectors – Automotive, Finance, Insurance, Healthcare, Retail, Government, etc. These projects cover the full spectrum of activities from Architecture, Design, Development, Infrastructure, Security, Implementation to Operations.