
RaimaDB is an embedded time series database designed specifically for Edge and IoT devices, capable of operating entirely in-memory. This powerful and lightweight relational database management system (RDBMS) is not only secure but has also been validated by over 20,000 developers globally, with deployments exceeding 25 million instances. It excels in high-performance environments and is tailored for critical applications across various sectors, particularly in edge computing and IoT. Its efficient architecture makes it particularly suitable for systems with limited resources, offering both in-memory and persistent storage capabilities. RaimaDB supports versatile data modeling, accommodating traditional relational approaches alongside direct relationships via network model sets. The database guarantees data integrity with ACID-compliant transactions and employs a variety of advanced indexing techniques, including B+Tree, Hash Table, R-Tree, and AVL-Tree, to enhance data accessibility and reliability. Furthermore, it is designed to handle real-time processing demands, featuring multi-version concurrency control (MVCC) and snapshot isolation, which collectively position it as a dependable choice for applications where both speed and stability are essential. This combination of features makes RaimaDB an invaluable asset for developers looking to optimize performance in their applications.
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High-Performance Data Engineering. 100% Sovereign.
TIMi delivers the full power of a enterprise data cloud—on-premises, fully sovereign, and blisteringly fast.
No vendor lock-in. No hidden costs. Just pure engineering excellence that gives your team total freedom to experiment, innovate, and solve your toughest AI and automation challenges in record time.
The TIMi Advantages:
No-Code Integration: Automate complex workflows and connect your entire tech stack instantly—from SAP and Salesforce to SharePoint and Google BigTable.
Radical Efficiency: Competitors such as Databricks, Dataiku, and MS Fabric relies heavily on a Spark back-end. Spark quickly burns budget because of bloated Java virtual machines. TIMi strips away the waste with pure, bare-metal, hand-optimized assembly code. The result: A single €2k TIMi server outperforms a 267-node Spark cluster, processing billions of rows in seconds and effortlessly running petabyte-scale data lakes at a fraction of the cost.
Pioneering AI: Harness advanced machine learning built on the legacy of the first Auto-ML engine (pioneered in 2007).
Available on-premises or via our EU-Hosted Sovereign Cloud. Trusted across Telecoms, Banking, Manufacturing, Retail, Defense, and Government.
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Tableau
Tableau is a powerful and versatile analytics platform that enables organizations to transform their data into valuable insights, supporting better decision-making at all levels. With the introduction of Tableau Next, businesses can now take advantage of agentic analytics, powered by AI, to uncover deeper insights and make faster, more informed decisions. Whether deployed in the cloud, on-premises, or natively within Salesforce CRM, Tableau integrates seamlessly with various data sources, providing a unified experience that ensures data accuracy, governance, and management. The platform’s AI and machine learning capabilities allow users to predict trends, optimize workflows, and identify key business opportunities in real-time. Tableau’s visual storytelling and intuitive interface make it easy for analysts and business leaders to explore data, share insights, and drive action. Tableau fosters a Data Culture within organizations, helping to accelerate innovation and improve operational efficiency. With solutions tailored to analysts, IT leaders, business executives, and developers, Tableau empowers everyone in an organization to make data-driven decisions that drive business growth and improve customer outcomes.
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IBM SPSS Statistics
IBM® SPSS® Statistics software is utilized by diverse clients to address specific business challenges within various industries, ultimately enhancing the quality of decision-making processes.
The platform encompasses sophisticated statistical analysis, an extensive collection of machine learning algorithms, capabilities for text analysis, open-source integration, compatibility with big data, and effortless application deployment.
Notably, its user-friendly interface, adaptability, and scalability ensure that SPSS remains accessible to individuals with varying levels of expertise. Furthermore, it is well-suited for projects ranging from small-scale tasks to complex initiatives, enabling users to uncover new opportunities, boost operational efficiency, and reduce potential risks.
In addition, the software's robust features make it a valuable tool for organizations looking to enhance their analytical capabilities.
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