Compare AWS Lake Formation vs. Huawei Cloud Data Lake Governance Center

Qrvey is the only solution for embedded analytics with a built-in data lake. Qrvey saves engineering teams time and money with a turnkey solution connecting your data warehouse to your SaaS application. Qrvey’s full-stack solution includes the necessary components so that your engineering team can build less software in-house. Qrvey is built for SaaS companies that want to offer a better multi-tenant analytics experience. Qrvey's solution offers: - Built-in data lake powered by Elasticsearch - A unified data pipeline to ingest and analyze any type of data - The most embedded components - all JS, no iFrames - Fully personalizable to offer personalized experiences to users With Qrvey, you can build less software and deliver more value.

AWS offers a wide range of services, including database storage, compute power, content delivery, and other functionality. This allows you to build complex applications with greater flexibility, scalability, and reliability. Amazon Web Services (AWS), the world's largest and most widely used cloud platform, offers over 175 fully featured services from more than 150 data centers worldwide. AWS is used by millions of customers, including the fastest-growing startups, large enterprises, and top government agencies, to reduce costs, be more agile, and innovate faster. AWS offers more services and features than any other cloud provider, including infrastructure technologies such as storage and databases, and emerging technologies such as machine learning, artificial intelligence, data lakes, analytics, and the Internet of Things. It is now easier, cheaper, and faster to move your existing apps to the cloud.

Engineered for peak performance and efficient resource use, KrakenD can manage a staggering 70k requests per second on just one instance. Its stateless build ensures hassle-free scalability, sidelining complications like database upkeep or node synchronization. In terms of features, KrakenD is a jack-of-all-trades. It accommodates multiple protocols and API standards, offering granular access control, data shaping, and caching capabilities. A standout feature is its Backend For Frontend pattern, which consolidates various API calls into a single response, simplifying client interactions. On the security front, KrakenD is OWASP-compliant and data-agnostic, streamlining regulatory adherence. Operational ease comes via its declarative setup and robust third-party tool integration. With its open-source community edition and transparent pricing model, KrakenD is the go-to API Gateway for organizations that refuse to compromise on performance or scalability.

Ambassador Edge Stack, a Kubernetes-native API Gateway, provides simplicity, security, and scalability for some of the largest Kubernetes infrastructures in the world. Ambassador Edge Stack makes it easy to secure microservices with a complete set of security functionality including automatic TLS, authentication and rate limiting. WAF integration is also available. Fine-grained access control is also possible. The API Gateway is a Kubernetes-based ingress controller that supports a wide range of protocols, including gRPC, gRPC Web, TLS termination, and traffic management controls to ensure resource availability.

Big Data Quality must always be verified to ensure that data is safe, accurate, and complete. Data is moved through multiple IT platforms or stored in Data Lakes. The Big Data Challenge: Data often loses its trustworthiness because of (i) Undiscovered errors in incoming data (iii). Multiple data sources that get out-of-synchrony over time (iii). Structural changes to data in downstream processes not expected downstream and (iv) multiple IT platforms (Hadoop DW, Cloud). Unexpected errors can occur when data moves between systems, such as from a Data Warehouse to a Hadoop environment, NoSQL database, or the Cloud. Data can change unexpectedly due to poor processes, ad-hoc data policies, poor data storage and control, and lack of control over certain data sources (e.g., external providers). DataBuck is an autonomous, self-learning, Big Data Quality validation tool and Data Matching tool.

Satori is a Data Security Platform (DSP) that enables self-service data and analytics for data-driven companies. With Satori, users have a personal data portal where they can see all available datasets and gain immediate access to them. That means your data consumers get data access in seconds instead of weeks. Satori’s DSP dynamically applies the appropriate security and access policies, reducing manual data engineering work. Satori’s DSP manages access, permissions, security, and compliance policies - all from a single console. Satori continuously classifies sensitive data in all your data stores (databases, data lakes, and data warehouses), and dynamically tracks data usage while applying relevant security policies. Satori enables your data use to scale across the company while meeting all data security and compliance requirements.

Transparency, choice and control are key to trust. Organizations have the opportunity to leverage these moments to build trust, and provide more valuable experiences. People expect greater control over their data. We offer privacy and data governance automation to help organizations better understand and comply with regulatory requirements. We also operationalize risk mitigation to ensure transparency and choice for individuals. Your organization will be able to achieve data privacy compliance quicker and build trust. Our platform helps to break down silos between processes, workflows, teams, and people to operationalize regulatory compliance. It also allows for trusted data use. Building proactive privacy programs that are rooted in global best practice and not just reacting to individual regulations is possible. To drive mitigation and risk-based decision-making, gain visibility into unknown risks. Respect individual choice and integrate privacy and security by default in the data lifecycle.

Red Points is the most widely used AI-driven platform to recover digital revenue. Red Points' software actively fights online fraud by scanning the Internet on behalf of its clients to automatically find and take down intellectual property infringements that are, in effect, stealing revenue.

ConWize, a cloud-based platform that assists construction companies in estimating projects more accurately and winning more tenders, is ConWize. Estimating construction projects can be time-consuming and complex. Errors that are not corrected can lead to lost tenders or a reduction in budget during the execution phase. ConWize makes it easier to bid and estimate during the tender phase. This protects your company from critical mistakes so you can win more tenders and make them profitable. We offer: ALL-IN-ONE BIDDING & ESTIMATING PLATFORM TO TENDER DEPARTMENTS Tenders pipeline management, subcontractors bid automation, advanced estimating instruments, indirect costs, profit loading tools, Tender KPI Analytics, and many more. MANAGE EXECUTION AND ESTIMATE PROJECTS IN ONE PLATFORM We know that profitability is the most important factor in projects. ConWize's precontract management module seamlessly links the execution and tender phases to maximize control and project monitoring.

Theum is cutting-edge software that fuses advanced knowledge management technology with generative AI capabilities to create an unparalleled platform for automating and controlling your organization’s knowledge processes and at the same time maximizing the value of your knowledge assets. Theum enables you to: - Streamline and automate complex tasks such as aggregating, curating, synchronizing, securing, converting, publishing, and delivering knowledge from diverse knowledge silos - Provide instant access to the precise, detailed knowledge required for any task via advanced, multilingual semantic search bolstered by a unique, intelligent context guidance system - Equip users with the full analytical and generative power of ChatGPT, seamlessly integrated into your knowledge and available for immediate use - Enhance knowledge quality and efficacy by analyzing user engagement, access trends, emerging needs, knowledge hot points, and more - Mitigate scalability issues in AI development and the compliance risks of unmonitored knowledge flows and the accidental use of unauthorized knowledge