Teradata VantageCloud
Teradata VantageCloud: Open, Scalable Cloud Analytics for AI
VantageCloud is Teradata’s cloud-native analytics and data platform designed for performance and flexibility. It unifies data from multiple sources, supports complex analytics at scale, and makes it easier to deploy AI and machine learning models in production. With built-in support for multi-cloud and hybrid deployments, VantageCloud lets organizations manage data across AWS, Azure, Google Cloud, and on-prem environments without vendor lock-in. Its open architecture integrates with modern data tools and standard formats, giving developers and data teams freedom to innovate while keeping costs predictable.
Learn more
RaimaDB
RaimaDB, an embedded time series database that can be used for Edge and IoT devices, can run in-memory. It is a lightweight, secure, and extremely powerful RDBMS. It has been field tested by more than 20 000 developers around the world and has been deployed in excess of 25 000 000 times.
RaimaDB is a high-performance, cross-platform embedded database optimized for mission-critical applications in industries such as IoT and edge computing. Its lightweight design makes it ideal for resource-constrained environments, supporting both in-memory and persistent storage options. RaimaDB offers flexible data modeling, including traditional relational models and direct relationships through network model sets. With ACID-compliant transactions and advanced indexing methods like B+Tree, Hash Table, R-Tree, and AVL-Tree, it ensures data reliability and efficiency. Built for real-time processing, it incorporates multi-version concurrency control (MVCC) and snapshot isolation, making it a robust solution for applications demanding speed and reliability.
Learn more
Hydrolix
Hydrolix serves as a streaming data lake that integrates decoupled storage, indexed search, and stream processing, enabling real-time query performance at a terabyte scale while significantly lowering costs. CFOs appreciate the remarkable 4x decrease in data retention expenses, while product teams are thrilled to have four times more data at their disposal. You can easily activate resources when needed and scale down to zero when they are not in use. Additionally, you can optimize resource usage and performance tailored to each workload, allowing for better cost management. Imagine the possibilities for your projects when budget constraints no longer force you to limit your data access. You can ingest, enhance, and transform log data from diverse sources such as Kafka, Kinesis, and HTTP, ensuring you retrieve only the necessary information regardless of the data volume. This approach not only minimizes latency and costs but also eliminates timeouts and ineffective queries. With storage being independent from ingestion and querying processes, each aspect can scale independently to achieve both performance and budget goals. Furthermore, Hydrolix's high-density compression (HDX) often condenses 1TB of data down to an impressive 55GB, maximizing storage efficiency. By leveraging such innovative capabilities, organizations can fully harness their data potential without financial constraints.
Learn more
Lentiq
Lentiq offers a collaborative data lake as a service that empowers small teams to achieve significant results. It allows users to swiftly execute data science, machine learning, and data analysis within the cloud platform of their choice. With Lentiq, teams can seamlessly ingest data in real time, process and clean it, and share their findings effortlessly. This platform also facilitates the building, training, and internal sharing of models, enabling data teams to collaborate freely and innovate without limitations. Data lakes serve as versatile storage and processing environments, equipped with machine learning, ETL, and schema-on-read querying features, among others. If you’re delving into the realm of data science, a data lake is essential for your success. In today’s landscape, characterized by the Post-Hadoop era, large centralized data lakes have become outdated. Instead, Lentiq introduces data pools—interconnected mini-data lakes across multiple clouds—that work harmoniously to provide a secure, stable, and efficient environment for data science endeavors. This innovative approach enhances the overall agility and effectiveness of data-driven projects.
Learn more
