Qubole is the open data lake company that provides a simple and secure data lake platform for machine learning, streaming, and ad-hoc analytics. No other platform provides the openness and data workload flexibility of Qubole while radically accelerating data lake adoption, reducing time to value, and lowering cloud data lake costs by 50 percent. Qubole’s Platform provides end-to-end data lake services such as cloud infrastructure management, data management, continuous data engineering, analytics, and machine learning with near-zero administration. Qubole is trusted by leading brands such as Expedia, Disney, Oracle, Gannett and Adobe to spur innovation and to transform their businesses for the era of big data. For more information, visit us at www.qubole.com.

The Aerospike Real-time Data Platform enables organizations to act instantly across billions of transactions while reducing server footprint by up to 80 percent. The Aerospike multi-cloud platform powers real-time applications with predictable sub-millisecond performance up to petabyte-scale with five-nines uptime with globally distributed, strongly consistent data. Applications built on the Aerospike Real-time Data Platform fight fraud, provide recommendations that dramatically increase shopping cart size, enable global digital payments, and deliver hyper-personalized user experiences to tens of millions of customers. Customers such as Airtel, Experian, Nielsen, PayPal, Snap, Wayfair, and Yahoo rely on Aerospike as their data foundation for the future.

Hadoop HDFS is a distributed, scalable, and portable filesystem written in Java.

Apache Apex is an enterprise grade native YARN big data-in-motion platform designed to unify stream processing as well as batch processing.

Apache Ambari is a software project designed to enable system administrators to provision, manage and monitor a Hadoop cluster, and also to integrate Hadoop with the existing enterprise infrastructure.

GridGain® is an in-memory computing platform solution designed to help organizations manage and process large volumes of data in real-time. Built on the robust Apache® Ignite™ framework, GridGain enables businesses to accelerate their applications, enhance data processing speeds, and scale efficiently to meet the demands of modern digital enterprises. This platform is particularly well-suited for scenarios where rapid data access and processing are critical, such as in financial services, e-commerce, telecommunications, and IoT applications. The target audience for GridGain includes IT professionals, data engineers, and business analysts who require high-performance computing capabilities to support their data-intensive applications. Organizations facing challenges related to data latency, scalability, and the need for real-time analytics will find GridGain to be a valuable solution. By leveraging in-memory computing, users can significantly reduce the time it takes to retrieve and analyze data, enabling them to make faster, data-driven decisions. Key features of the GridGain platform include distributed in-memory storage, advanced data processing capabilities, and seamless integration with existing data sources and applications. The platform supports SQL queries, key-value access, and various data processing frameworks, allowing users to work with data in the format that best suits their needs. Additionally, GridGain provides built-in support for machine learning and streaming analytics, empowering organizations to harness the full potential of their data in real-time. One of the primary benefits of using GridGain is its ability to enhance application performance by reducing latency and increasing throughput. By storing data in-memory rather than on traditional disk storage, GridGain enables faster data access and processing, which is crucial for applications that require immediate insights. Furthermore, the platform's scalability allows organizations to expand their computing resources as needed, ensuring that they can handle growing data volumes without compromising performance. GridGain stands out in the in-memory computing market due to its robust architecture, flexibility, and comprehensive support for various data processing needs. With a proven track record of success among major clients and numerous industry awards, GridGain continues to lead the way in addressing the challenges of Fast Data and helping organizations unlock the full potential of their data assets.

Apache Chukwa is an open source data collection system for monitoring large distributed systems.

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Apache Druid is an open source real-time analytics database. Druid combines ideas from OLAP/analytic databases, timeseries databases, and search systems to create a complete real-time analytics solution for real-time data. It includes stream and batch ingestion, column-oriented storage, time-optimized partitioning, native OLAP and search indexing, SQL and REST support, flexible schemas; all with true horizontal scalability on a shared nothing, cloud native architecture that makes it easy to deploy, monitor and manage at scale. It is downloadable for free for unlimited use from druid.apache.org and also hosted in the cloud by Imply Data.

Apache Beam is an open source unified programming model designed to define and execute data processing pipelines, including ETL, batch and stream processing.

Prophecy is the AI data prep and analysis platform. We make business data teams incredibly productive with AI agentic coworkers. Prophecy introduces an AI-powered data lifecycle — generate, refine, deploy — where AI agents and data teams collaborate across text, visual, and code interfaces to move faster, automate repetitive tasks, and ship trusted pipelines to production.

Apache Storm is a free and open source distributed realtime computation system. Storm makes it easy to reliably process unbounded streams of data, doing for realtime processing what Hadoop did for batch processing.

Tinybird is a fully managed ClickHouse® service designed for software developers and AI-native product teams by enabling them to create large-scale real-time analytics projects with minimal effort. Tinybird makes integrating the open source ClickHouse database into applications simpler, faster, and more reliable, allowing engineers to focus on feature development rather than infrastructure management. Tinybird eliminates the complexities associated with traditional database management, making it an ideal choice for teams looking to leverage the power of ClickHouse without the overhead of server maintenance and scaling concerns. The target audience for Tinybird includes software developers, data engineers, technical founders, and AI-native product teams building real-time analytics capabilities in their applications. With the increasing demand for real-time data processing, Tinybird caters to teams that need to deliver insights quickly and efficiently. Use cases for Tinybird span various industries, including SaaS, e-commerce, finance, crypto, AI, and IoT, where real-time data analysis is crucial for decision-making and operational efficiency. By providing a managed service, Tinybird allows software engineers to deploy analytics features in days rather than months, significantly accelerating project timelines. Key features of Tinybird include a hosted ClickHouse database plus managed data ingestion and API layers, which simplify the process of integrating analytics into applications. The built-in authentication tools enhance security and data privacy, with support for row-level access policies using JWTs. Free observability logs storage and querying allow users to keep tabs on usage and performance. AI-native features, including Tinybird Code - a CLI agent with deep ClickHouse expertise - plus the Tinybird MCP Server, make integrating analytics features into LLM apps simpler and more robust. Additionally, Tinybird's architecture is designed to handle scaling automatically, allowing teams to focus on their core development tasks without worrying about understanding a new database or worrying about infrastructure details. For those who desire infrastructure control, Tinybird offers self-managed deployment, for free. This unique combination of features enables users to ship data-driven features rapidly while maintaining high performance and reliability. Tinybird stands out in the real-time analytics database landscape by providing the performance of one of the world's fastest OLAP databases without the associated complexity. By abstracting the technical challenges of managing clusters and provisioning resources, Tinybird empowers teams to innovate and iterate on their products more quickly. The service's emphasis on ease of use and rapid deployment makes it an attractive option for organizations looking to harness the power of real-time analytics without the burden of extensive operational overhead. With Tinybird, users can unlock the potential of their data and drive impactful insights, all while enjoying a seamless and efficient development experience.

HVR is a real-time data replication solution designed to move large volumes of data FAST and efficiently in hybrid environments for real-time analytics. With HVR, discover the benefits of using log-based change data capture for replicating data from common DBMS such as SQL Server, Oracle, SAP Hana, and more to sources such as AWS, Azure, Teradata and more.

Hazelcast Platform is the Live Data Platform that delivers data at the speed of relevance, providing the in‑memory foundation for applications that act on data the instant it's created—ensuring businesses never miss a moment of opportunity. By converging distributed caching, compute, stream processing, and real‑time AI into one low‑latency runtime, Hazelcast delivers sub‑millisecond performance, linear scalability, and enterprise resilience. Global 2000 firms trust Hazelcast to simplify architectures, reduce costs, and power mission‑critical, time‑sensitive applications.