e6data vs. BigLake

Accelerate your data initiatives with AnalyticsCreator—a metadata-driven data warehouse automation solution purpose-built for the Microsoft data ecosystem. AnalyticsCreator simplifies the design, development, and deployment of modern data architectures, including dimensional models, data marts, data vaults, and blended modeling strategies that combine best practices from across methodologies. Seamlessly integrate with key Microsoft technologies such as SQL Server, Azure Synapse Analytics, Microsoft Fabric (including OneLake and SQL Endpoint Lakehouse environments), and Power BI. AnalyticsCreator automates ELT pipeline generation, data modeling, historization, and semantic model creation—reducing tool sprawl and minimizing the need for manual SQL coding across your data engineering lifecycle. Designed for CI/CD-driven data engineering workflows, AnalyticsCreator connects easily with Azure DevOps and GitHub for version control, automated builds, and environment-specific deployments. Whether working across development, test, and production environments, teams can ensure faster, error-free releases while maintaining full governance and audit trails. Additional productivity features include automated documentation generation, end-to-end data lineage tracking, and adaptive schema evolution to handle change management with ease. AnalyticsCreator also offers integrated deployment governance, allowing teams to streamline promotion processes while reducing deployment risks. By eliminating repetitive tasks and enabling agile delivery, AnalyticsCreator helps data engineers, architects, and BI teams focus on delivering business-ready insights faster. Empower your organization to accelerate time-to-value for data products and analytical models—while ensuring governance, scalability, and Microsoft platform alignment every step of the way.

BigQuery serves as a serverless, multicloud data warehouse that simplifies the handling of diverse data types, allowing businesses to quickly extract significant insights. As an integral part of Google’s data cloud, it facilitates seamless data integration, cost-effective and secure scaling of analytics capabilities, and features built-in business intelligence for disseminating comprehensive data insights. With an easy-to-use SQL interface, it also supports the training and deployment of machine learning models, promoting data-driven decision-making throughout organizations. Its strong performance capabilities ensure that enterprises can manage escalating data volumes with ease, adapting to the demands of expanding businesses. Furthermore, Gemini within BigQuery introduces AI-driven tools that bolster collaboration and enhance productivity, offering features like code recommendations, visual data preparation, and smart suggestions designed to boost efficiency and reduce expenses. The platform provides a unified environment that includes SQL, a notebook, and a natural language-based canvas interface, making it accessible to data professionals across various skill sets. This integrated workspace not only streamlines the entire analytics process but also empowers teams to accelerate their workflows and improve overall effectiveness. Consequently, organizations can leverage these advanced tools to stay competitive in an ever-evolving data landscape.

Google's Compute Engine, which falls under the category of infrastructure as a service (IaaS), enables businesses to create and manage virtual machines in the cloud. This platform facilitates cloud transformation by offering computing infrastructure in both standard sizes and custom machine configurations. General-purpose machines, like the E2, N1, N2, and N2D, strike a balance between cost and performance, making them suitable for a variety of applications. For workloads that demand high processing power, compute-optimized machines (C2) deliver superior performance with advanced virtual CPUs. Memory-optimized systems (M2) are tailored for applications requiring extensive memory, making them perfect for in-memory database solutions. Additionally, accelerator-optimized machines (A2), which utilize A100 GPUs, cater to applications that have high computational demands. Users can integrate Compute Engine with other Google Cloud Services, including AI and machine learning or data analytics tools, to enhance their capabilities. To maintain sufficient application capacity during scaling, reservations are available, providing users with peace of mind. Furthermore, financial savings can be achieved through sustained-use discounts, and even greater savings can be realized with committed-use discounts, making it an attractive option for organizations looking to optimize their cloud spending. Overall, Compute Engine is designed not only to meet current needs but also to adapt and grow with future demands.

Delska operates as a specialized data center and network service provider, delivering customized IT and networking solutions for enterprises. With a total of five data centers in Latvia and Lithuania—one of which is set to open in 2025—and additional points of presence in Germany, the Netherlands, and Sweden, we create a robust regional ecosystem for data centers and networking. Our commitment to sustainability is reflected in our goal to reach net-zero CO2 emissions by 2030, establishing a benchmark for eco-friendly IT infrastructure in the Baltic region. Beyond traditional services like cloud computing, colocation, and data security, we also introduced the myDelska self-service cloud platform, designed for rapid deployment of virtual machines and management of IT resources, with bare metal services expected soon. Our platform boasts several essential features, including unlimited traffic and fixed monthly pricing, API integration, customizable firewall settings, comprehensive backup solutions, real-time network topology visualization, and a latency measurement map, supporting various operating systems such as Alpine Linux, Ubuntu, Debian, Windows OS, and openSUSE. In June 2024, Delska expanded its portfolio by merging with two companies—DEAC European Data Center and Data Logistics Center (DLC)—which continue to function as separate legal entities under the ownership of Quaero European Infrastructure Fund II. This strategic merger enhances our capacity to provide even more innovative services and solutions to our clients.

ManageEngine's Endpoint Central, which was previously known as Desktop Central, serves as a comprehensive Unified Endpoint Management Solution that oversees enterprise mobility management. This solution encompasses all aspects of mobile app and device management, in addition to client management for various endpoints, including mobile devices, laptops, tablets, servers, and other computing machines. With ManageEngine Endpoint Central, users can streamline and automate numerous desktop management activities, such as software installation, patching, IT asset management, imaging, and operating system deployment, thereby enhancing operational efficiency across the organization. This tool is particularly beneficial for IT departments looking to maintain control over their diverse technology environments.

Approximately 25 million engineers are employed across a wide variety of specific roles. As companies increasingly transform into software-centric organizations, engineers are leveraging New Relic to obtain real-time insights and analyze performance trends of their applications. This capability enables them to enhance their resilience and deliver outstanding customer experiences. New Relic stands out as the sole platform that provides a comprehensive all-in-one solution for these needs. It supplies users with a secure cloud environment for monitoring all metrics and events, robust full-stack analytics tools, and clear pricing based on actual usage. Furthermore, New Relic has cultivated the largest open-source ecosystem in the industry, simplifying the adoption of observability practices for engineers and empowering them to innovate more effectively. This combination of features positions New Relic as an invaluable resource for engineers navigating the evolving landscape of software development.

Introducing an innovative monetization platform designed specifically for the modern billing landscape. This solution reduces risks, allows a focus on essential tasks, and broadens the array of pricing and packaging options while decreasing code complexities. Functioning as a specialized middleware, this monetization platform harmoniously connects your application with your business tools, becoming a vital component of the modern enterprise billing infrastructure. Stigg simplifies the workload for billing and platform engineers by bringing together all the necessary APIs and abstractions that would otherwise require internal development and upkeep. By serving as your definitive information source, it provides strong and flexible entitlements management, transforming the process of making pricing and packaging changes into an uncomplicated, self-service operation that is free from risks. With Stigg, engineers are afforded precise control over individually priceable and packagable components. You have the ability to set limitations and oversee your customers' commercial permissions at a granular feature level, clarifying complex billing notions within your code. Ultimately, entitlements signify a forward-thinking strategy for software monetization, offering a flexible and responsive framework for hybrid pricing models, enabling businesses to flourish in a competitive environment. This innovative strategy not only simplifies billing workflows but also equips organizations to adapt and meet market challenges swiftly, fostering an environment of continuous improvement and growth.

Aizon: Intelligent GxP Manufacturing Aizon delivers an AI-powered platform that redefines how pharmaceutical and biotech manufacturers operate under GxP requirements. Our solutions empower teams to enhance efficiency, raise yields, and maintain the highest standards of product quality. - Aizon Execute — Intelligent Batch Record (iBR): Digitize production quickly to reduce manual errors, lower deviations, and accelerate the release of compliant batches. - Aizon Unify — Contextualized Intelligent Lakehouse: Connect and contextualize data from diverse sources to improve decision-making and achieve operational excellence. - Aizon Predict — GxP AI Industrialization: Use predictive AI models to fine-tune critical process parameters, increase Right-First-Time outcomes, and deliver higher manufacturing performance. Aizon enables manufacturers to move beyond traditional compliance and embrace true operational intelligence—learning from the past, acting decisively in the present, and innovating for the future.

The Napersoft CCM Document Platform 8, compatible with both Microsoft® Windows and Linux, represents our most recent solution tailored for the modern interconnected environment. This platform boasts a variety of innovative features aimed at enhancing user experience and functionality. It serves as an ideal choice for businesses ranging from medium-sized to large enterprises, enabling the batch, interactive, and on-demand generation, formatting, and distribution of personalized customer communications across various channels such as print, text, email, and additional mediums. Moreover, this versatility ensures that companies can effectively engage with their customers, delivering timely and relevant information.

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.