Alternatives to CONNX

Windocks provides on-demand Oracle, SQL Server, as well as other databases that can be customized for Dev, Test, Reporting, ML, DevOps, and DevOps. Windocks database orchestration allows for code-free end to end automated delivery. This includes masking, synthetic data, Git operations and access controls, as well as secrets management. Databases can be delivered to conventional instances, Kubernetes or Docker containers. Windocks can be installed on standard Linux or Windows servers in minutes. It can also run on any public cloud infrastructure or on-premise infrastructure. One VM can host up 50 concurrent database environments. When combined with Docker containers, enterprises often see a 5:1 reduction of lower-level database VMs.

Accelerate your data journey with AnalyticsCreator. Automate the design, development, and deployment of modern data architectures, including dimensional models, data marts, and data vaults or a combination of modeling techniques. Seamlessly integrate with leading platforms like Microsoft Fabric, Power BI, Snowflake, Tableau, and Azure Synapse and more. Experience streamlined development with automated documentation, lineage tracking, and schema evolution. Our intelligent metadata engine empowers rapid prototyping and deployment of analytics and data solutions. Reduce time-consuming manual tasks, allowing you to focus on data-driven insights and business outcomes. AnalyticsCreator supports agile methodologies and modern data engineering workflows, including CI/CD. Let AnalyticsCreator handle the complexities of data modeling and transformation, enabling you to unlock the full potential of your data

Streamline the self-service provisioning and refreshing of enterprise workloads by seamlessly integrating with your current toolchain. Provide data scientists with high-performance data delivery and reuse through an extensive suite of APIs and automation capabilities. Ensure the ability to retrieve any data across multiple clouds at any moment, all while operating at scale and surpassing traditional solutions. Reduce the potential business disruption caused by ransomware or cyber threats by enabling rapid recovery using immutable backups. Offer a consolidated platform that enhances the protection, security, retention, governance, and recovery of your data, whether it's stored on-premises or in the cloud. Actifio’s innovative software platform transforms data silos into efficient data pipelines, streamlining access and usage. The Virtual Data Pipeline (VDP) facilitates comprehensive data management across on-premises, hybrid, or multi-cloud environments, providing robust application integration, SLA-based orchestration, adaptable data movement, as well as enhanced data immutability and security features. This holistic approach empowers organizations to optimize their data strategy and ensure resilience against potential data-related challenges.

Delphix is the industry leader for DataOps. It provides an intelligent data platform that accelerates digital change for leading companies around world. The Delphix DataOps Platform supports many systems, including mainframes, Oracle databases, ERP apps, and Kubernetes container. Delphix supports a wide range of data operations that enable modern CI/CD workflows. It also automates data compliance with privacy regulations such as GDPR, CCPA and the New York Privacy Act. Delphix also helps companies to sync data between private and public clouds, accelerating cloud migrations and customer experience transformations, as well as the adoption of disruptive AI technologies.

Enterprise Enabler brings together disparate information from various sources and isolated data sets, providing a cohesive view within a unified platform; this includes data housed in the cloud, distributed across isolated databases, stored on instruments, located in Big Data repositories, or found within different spreadsheets and documents. By seamlessly integrating all your data, it empowers you to make timely and well-informed business choices. The system creates logical representations of data sourced from its original locations, enabling you to effectively reuse, configure, test, deploy, and monitor everything within a single cohesive environment. This allows for the analysis of your business data as events unfold, helping to optimize asset utilization, reduce costs, and enhance your business processes. Remarkably, our deployment timeline is typically 50-90% quicker, ensuring that your data sources are connected and operational in record time, allowing for real-time decision-making based on the most current information available. With this solution, organizations can enhance collaboration and efficiency, leading to improved overall performance and strategic advantage in the market.

The primary obstacle in expanding AI-driven decision-making lies in the underutilization of data. IBM Cloud Pak® for Data provides a cohesive platform that integrates a data fabric, enabling seamless connection and access to isolated data, whether it resides on-premises or in various cloud environments, without necessitating data relocation. It streamlines data accessibility by automatically identifying and organizing data to present actionable knowledge assets to users, while simultaneously implementing automated policy enforcement to ensure secure usage. To further enhance the speed of insights, this platform incorporates a modern cloud data warehouse that works in harmony with existing systems. It universally enforces data privacy and usage policies across all datasets, ensuring compliance is maintained. By leveraging a high-performance cloud data warehouse, organizations can obtain insights more rapidly. Additionally, the platform empowers data scientists, developers, and analysts with a comprehensive interface to construct, deploy, and manage reliable AI models across any cloud infrastructure. Moreover, enhance your analytics capabilities with Netezza, a robust data warehouse designed for high performance and efficiency. This comprehensive approach not only accelerates decision-making but also fosters innovation across various sectors.

AWS Glue is a fully managed, serverless service designed for data integration, allowing users to easily discover, prepare, and merge data for various purposes such as analytics, machine learning, and application development. This service encompasses all necessary features for efficient data integration, enabling rapid data analysis and utilization in mere minutes rather than taking months. The data integration process includes multiple steps, including the discovery and extraction of data from diverse sources, as well as enhancing, cleaning, normalizing, and merging this data before it is loaded and organized within databases, data warehouses, and data lakes. Different users, each utilizing distinct products, typically manage these various tasks. Operating within a serverless architecture, AWS Glue eliminates the need for users to manage any infrastructure, as it autonomously provisions, configures, and scales the resources essential for executing data integration jobs. This allows organizations to focus on deriving insights from their data rather than being bogged down by operational complexities. With AWS Glue, businesses can seamlessly streamline their data workflows and enhance productivity across teams.

Connect and centralize data. Transform your data landscape into a flexible powerhouse. Data Virtuality is a data integration platform that allows for instant data access, data centralization, and data governance. Logical Data Warehouse combines materialization and virtualization to provide the best performance. For high data quality, governance, and speed-to-market, create your single source data truth by adding a virtual layer to your existing data environment. Hosted on-premises or in the cloud. Data Virtuality offers three modules: Pipes Professional, Pipes Professional, or Logical Data Warehouse. You can cut down on development time up to 80% Access any data in seconds and automate data workflows with SQL. Rapid BI Prototyping allows for a significantly faster time to market. Data quality is essential for consistent, accurate, and complete data. Metadata repositories can be used to improve master data management.

DevOps can be simplified and privacy concerns eliminated by giving your teams full data autonomy via an easy-to use self-service portal. You can simplify access, remove data roadblocks, and speed up provisioning for data analysts, dev, testing, and other purposes. The Accelario Continuous DataOps platform is your one-stop-shop to all of your data needs. Eliminate DevOps bottlenecks, and give your teams high-quality, privacy-compliant information. The platform's four modules can be used as standalone solutions or as part of a comprehensive DataOps management platform. Existing data provisioning systems can't keep pace with agile requirements for continuous, independent access and privacy-compliant data in autonomous environments. With a single-stop-shop that provides comprehensive, high-quality, self-provisioning privacy compliant data, teams can meet agile requirements for frequent deliveries.

TIBCO provides robust solutions designed to fulfill your requirements for performance, throughput, reliability, and scalability, while also offering diverse technology and deployment alternatives to ensure real-time data accessibility in critical areas. The TIBCO Platform integrates a continuously developing array of your TIBCO solutions, regardless of their hosting environment—be it cloud-based, on-premises, or at the edge—into a cohesive, single experience that simplifies management and monitoring. By doing so, TIBCO supports the creation of solutions vital for the success of major enterprises around the globe, enabling them to thrive in a competitive landscape. This commitment to innovation positions TIBCO as a key player in the digital transformation journey of businesses.

K2View believes that every enterprise should be able to leverage its data to become as disruptive and agile as possible. We enable this through our Data Product Platform, which creates and manages a trusted dataset for every business entity – on demand, in real time. The dataset is always in sync with its sources, adapts to changes on the fly, and is instantly accessible to any authorized data consumer. We fuel operational use cases, including customer 360, data masking, test data management, data migration, and legacy application modernization – to deliver business outcomes at half the time and cost of other alternatives.

Adaptive Data Virtualization™ technology empowers businesses to operate their current applications on contemporary cloud data warehouses without the need for extensive modifications or reconfiguration. With Datometry Hyper-Q™, organizations can swiftly embrace new cloud databases, effectively manage ongoing operational costs, and enhance their analytical capabilities to accelerate digital transformation efforts. This virtualization software from Datometry enables any existing application to function on any cloud database, thus facilitating interoperability between applications and databases. Consequently, enterprises can select their preferred cloud database without the necessity of dismantling, rewriting, or replacing their existing applications. Furthermore, it ensures runtime application compatibility by transforming and emulating legacy data warehouse functionalities. This solution can be deployed seamlessly on major cloud platforms like Azure, AWS, and GCP. Additionally, applications can leverage existing JDBC, ODBC, and native connectors without any alterations, ensuring a smooth transition. It also establishes connections with leading cloud data warehouses, including Azure Synapse Analytics, AWS Redshift, and Google BigQuery, broadening the scope for data integration and analysis.

Numerous products are available that assist businesses in this endeavor, but if your main goals are to build a data-driven organization while maximizing efficiency and minimizing costs, the only option worth considering is Fraxses, the leading distributed data platform in the world. Fraxses gives clients on-demand access to data, providing impactful insights through a solution that supports either a data mesh or data fabric architecture. Imagine a data mesh as a framework that overlays various data sources, linking them together and allowing them to operate as a cohesive unit. In contrast to other platforms focused on data integration and virtualization, Fraxses boasts a decentralized architecture that sets it apart. Although Fraxses is fully capable of accommodating traditional data integration methods, the future is leaning towards a novel approach where data is delivered directly to users, eliminating the necessity for a centrally managed data lake or platform. This innovative perspective not only enhances user autonomy but also streamlines data accessibility across the organization.

Boost the pace of AI innovation through cloud-native data integration offered by IBM Cloud Pak for Data. With AI-driven data integration capabilities accessible from anywhere, the effectiveness of your AI and analytics is directly linked to the quality of the data supporting them. Utilizing a modern container-based architecture, IBM® DataStage® for IBM Cloud Pak® for Data ensures the delivery of superior data. This solution merges top-tier data integration with DataOps, governance, and analytics within a unified data and AI platform. By automating administrative tasks, it helps in lowering total cost of ownership (TCO). The platform's AI-based design accelerators, along with ready-to-use integrations with DataOps and data science services, significantly hasten AI advancements. Furthermore, its parallelism and multicloud integration capabilities enable the delivery of reliable data on a large scale across diverse hybrid or multicloud settings. Additionally, you can efficiently manage the entire data and analytics lifecycle on the IBM Cloud Pak for Data platform, which encompasses a variety of services such as data science, event messaging, data virtualization, and data warehousing, all bolstered by a parallel engine and automated load balancing features. This comprehensive approach ensures that your organization stays ahead in the rapidly evolving landscape of data and AI.

Red Hat JBoss Data Virtualization serves as an efficient solution for virtual data integration, effectively releasing data that is otherwise inaccessible and presenting it in a unified, user-friendly format that can be easily acted upon. It allows data from various, physically distinct sources, such as different databases, XML files, and Hadoop systems, to be viewed as a cohesive set of tables within a local database. This solution provides real-time, standards-based read and write access to a variety of heterogeneous data repositories. By streamlining the process of accessing distributed data, it accelerates both application development and integration. Users can integrate and adapt data semantics to meet the specific requirements of data consumers. Additionally, it offers central management for access control and robust auditing processes through a comprehensive security framework. As a result, fragmented data can be transformed into valuable insights swiftly, catering to the dynamic needs of businesses. Moreover, Red Hat provides ongoing support and maintenance for its JBoss products during specified periods, ensuring that users have access to the latest enhancements and assistance.

The fundamental technology that powers contemporary solutions for data integration and management is designed to swiftly link various structured and unstructured data sources. It allows for the comprehensive cataloging of your entire data environment, ensuring that data remains within its original sources and is retrieved as needed, eliminating the requirement for duplicate copies. Users can construct data models tailored to their needs, even when drawing from multiple data sources, while also concealing the intricacies of back-end systems from end users. The virtual model can be securely accessed and utilized through standard SQL alongside other formats such as REST, SOAP, and OData, promoting easy access to diverse data types. It features complete data integration and modeling capabilities, along with an Active Data Catalog that enables self-service for data and metadata exploration and preparation. Furthermore, it incorporates robust data security and governance measures, ensures rapid and intelligent execution of data queries, and provides real-time data delivery in various formats. The system also supports the establishment of data marketplaces and effectively decouples business applications from data systems, paving the way for more informed, data-driven decision-making strategies. This innovative approach enhances the overall agility and responsiveness of organizations in managing their data assets.

Rapidly establish cloud environments tailored for spontaneous development, testing, and enhanced productivity for IT and business personnel. Mitigate the risks and expenses associated with managing your data lake by adopting robust data governance practices that include comprehensive end-to-end data lineage for business users. Achieve greater cost efficiency by providing clean, reliable, and timely data for your data lakes, data warehouses, or big data initiatives, while also consolidating applications and phasing out legacy databases. Benefit from automatic schema propagation to accelerate job creation, implement type-ahead search features, and maintain backward compatibility, all while following a design that allows for execution across varied platforms. Develop data integration workflows and enforce governance and quality standards through an intuitive design that identifies and recommends usage trends, thus enhancing user experience. Furthermore, boost visibility and information governance by facilitating complete and authoritative insights into data, backed by proof of lineage and quality, ensuring that stakeholders can make informed decisions based on accurate information. With these strategies in place, organizations can foster a more agile and data-driven culture.

If you're looking to establish a governed delta lake, create a data warehouse, or transition from a conventional database to a contemporary cloud data solution, Lyftrondata has you covered. You can effortlessly create and oversee all your data workloads within a single platform, automating the construction of your pipeline and warehouse. Instantly analyze your data using ANSI SQL and business intelligence or machine learning tools, and easily share your findings without the need for custom coding. This functionality enhances the efficiency of your data teams and accelerates the realization of value. You can define, categorize, and locate all data sets in one centralized location, enabling seamless sharing with peers without the complexity of coding, thus fostering insightful data-driven decisions. This capability is particularly advantageous for organizations wishing to store their data once, share it with various experts, and leverage it repeatedly for both current and future needs. In addition, you can define datasets, execute SQL transformations, or migrate your existing SQL data processing workflows to any cloud data warehouse of your choice, ensuring flexibility and scalability in your data management strategy.

A comprehensive enterprise data virtualization solution enables seamless access to a variety of data sources while establishing a robust foundation of datasets and IT-managed data services suitable for virtually any application. The TIBCO® Data Virtualization system, functioning as a contemporary data layer, meets the dynamic demands of organizations with evolving architectures. By eliminating bottlenecks, it fosters consistency and facilitates reuse by providing on-demand access to all data through a unified logical layer that is secure, governed, and accessible to a wide range of users. With immediate availability of all necessary data, organizations can derive actionable insights and respond swiftly in real-time. Users benefit from the ability to effortlessly search for and choose from a self-service directory of virtualized business data, utilizing their preferred analytics tools to achieve desired outcomes. This shift allows them to concentrate more on data analysis rather than on the time-consuming task of data retrieval. Furthermore, the streamlined process enhances productivity and enables teams to make informed decisions quickly and effectively.

Clonetab has many options to meet the needs of each site. Although Clonetab's core features will suffice for most site requirements, Clonetab also offers infrastructure to allow you to add custom steps to make it more flexible to meet your specific needs. Clonetab base module for Oracle Databases, eBusiness Suite, and PeopleSoft is available. Normal shell scripts used to perform refreshes can leave sensitive passwords in flat file. They may not have an audit trail to track who does refreshes and for which purpose. This makes it difficult to support these scripts, especially if the person who created them leaves the organization. Clonetab can be used to automate refreshes. Clonetab's features, such as pre, post and random scripts, target instances retention options like dblinks, concurrent processes, and appltop binary copying, allow users to automate most of their refresh steps. These steps can be done once. The tasks can then be scheduled.

Streamline your data protection strategies by removing outdated backup silos, enabling efficient safeguarding of virtual, physical, and cloud workloads alongside ensuring rapid recovery. By processing data where it resides and utilizing applications to extract insights, you can enhance your operational efficiency. Protect your organization from advanced ransomware threats through a comprehensive data security framework, as relying on numerous single-purpose tools for disparate silos increases vulnerability. Cohesity boosts cyber resilience and addresses extensive data fragmentation by centralizing information within a singular hyper-scale platform. Transform your data centers by unifying backups, archives, file shares, object stores, and data utilized in analytics and development/testing processes. Our innovative solution for these issues is Cohesity Helios, a unified next-generation data management platform that delivers a variety of services. With our next-gen approach, managing your data becomes simpler and more efficient, all while adapting to the continuous growth of your data landscape. This unification not only enhances operational efficiency but also fortifies your defenses against evolving cyber threats.

Oracle's server virtualization offerings are engineered for high efficiency and enhanced performance, catering to both x86 and SPARC architectures while accommodating diverse workloads, including Linux, Windows, and Oracle Solaris. Beyond hypervisor-based solutions, Oracle also provides virtualization that is integrated with hardware and its operating systems, ensuring a comprehensive and finely-tuned solution for your entire computing ecosystem. This combination of flexibility and optimization makes Oracle a compelling choice for organizations looking to streamline their virtualization strategy.

Oracle Big Data SQL Cloud Service empowers companies to swiftly analyze information across various platforms such as Apache Hadoop, NoSQL, and Oracle Database, all while utilizing their existing SQL expertise, security frameworks, and applications, achieving remarkable performance levels. This solution streamlines data science initiatives and facilitates the unlocking of data lakes, making the advantages of Big Data accessible to a wider audience of end users. It provides a centralized platform for users to catalog and secure data across Hadoop, NoSQL systems, and Oracle Database. With seamless integration of metadata, users can execute queries that combine data from Oracle Database with that from Hadoop and NoSQL databases. Additionally, the service includes utilities and conversion routines that automate the mapping of metadata stored in HCatalog or the Hive Metastore to Oracle Tables. Enhanced access parameters offer administrators the ability to customize column mapping and govern data access behaviors effectively. Furthermore, the capability to support multiple clusters allows a single Oracle Database to query various Hadoop clusters and NoSQL systems simultaneously, thereby enhancing data accessibility and analytics efficiency. This comprehensive approach ensures that organizations can maximize their data insights without compromising on performance or security.

An attacker cannot discover your backups because of a logical air gap. Our append-only file system makes backup data inaccessible to hackers. Multi-factor authentication can be enforced globally to keep unauthorized users from accessing your backups. You can replace hundreds of backup jobs, or even thousands, with just a few policies. The same policies should be applied to all workloads, both on-premises as well as in the cloud. Archive your data to your cloud provider's blob storage. With real-time predictive searching, you can quickly access archived data. You can search across your entire environment down to the file level and choose the right time to recover. Recoveries can be done in a matter of hours, instead of days or weeks. Microsoft and Rubrik have joined forces to help businesses build cyber-resilience. You can reduce the risk of data loss, theft, and backup data breaches by storing immutable copies in a Rubrik-hosted cloud environment that is isolated from your core workloads.

Dremio provides lightning-fast queries as well as a self-service semantic layer directly to your data lake storage. No data moving to proprietary data warehouses, and no cubes, aggregation tables, or extracts. Data architects have flexibility and control, while data consumers have self-service. Apache Arrow and Dremio technologies such as Data Reflections, Columnar Cloud Cache(C3), and Predictive Pipelining combine to make it easy to query your data lake storage. An abstraction layer allows IT to apply security and business meaning while allowing analysts and data scientists access data to explore it and create new virtual datasets. Dremio's semantic layers is an integrated searchable catalog that indexes all your metadata so business users can make sense of your data. The semantic layer is made up of virtual datasets and spaces, which are all searchable and indexed.

Embrace flexibility with a top-tier, scalable enterprise data integration platform that boasts high performance. It supports every phase of the data integration lifecycle, from initiating the initial project to ensuring the success of critical enterprise deployments. PowerCenter, a platform driven by metadata, expedites data integration initiatives, enabling businesses to access data much faster than through traditional manual coding. Developers and analysts can work together to quickly prototype, revise, analyze, validate, and launch projects within days rather than taking months. Serving as the cornerstone for your data integration efforts, PowerCenter allows for the use of machine learning to effectively oversee and manage your deployments across various domains and locations, enhancing operational efficiency and adaptability. This level of integration ensures that organizations can respond swiftly to changing data needs and market demands.

A true self-service reporting platform and analytics platform will empower your business. Orbit's business intelligence and operational reporting software is powerful and scalable. Users can create their own reports and analytics. Orbit Reporting + Analytics provides pre-built integration with enterprise resources planning (ERP), key cloud business applications, such as Salesforce, Oracle E-Business Suite and PeopleSoft. Orbit allows you to quickly and efficiently discover answers from any data source, identify opportunities, and make data-driven decisions.

Embedded Data Virtualization allows you to extend your applications with unified data connectivity. CData Query Federation Drivers are a universal data access layer that makes it easier to develop applications and access data. Through a single interface, you can write SQL and access data from 250+ applications and databases. The CData Query Federation Driver provides powerful tools such as: * A Single SQL Language and API: A common SQL interface to work with multiple SaaS and NoSQL, relational, or Big Data sources. * Combined Data Across Resources: Create queries that combine data from multiple sources without the need to perform ETL or any other data movement. * Intelligent Push-Down - Federated queries use intelligent push-down to improve performance and throughput. * 250+ Supported Connections: Plug-and–Play CData Drivers allow connectivity to more than 250 enterprise information sources.

TROCCO is an all-in-one modern data platform designed to help users seamlessly integrate, transform, orchestrate, and manage data through a unified interface. It boasts an extensive array of connectors that encompass advertising platforms such as Google Ads and Facebook Ads, cloud services like AWS Cost Explorer and Google Analytics 4, as well as various databases including MySQL and PostgreSQL, and data warehouses such as Amazon Redshift and Google BigQuery. One of its standout features is Managed ETL, which simplifies the data import process by allowing bulk ingestion of data sources and offers centralized management for ETL configurations, thereby removing the necessity for individual setup. Furthermore, TROCCO includes a data catalog that automatically collects metadata from data analysis infrastructure, creating a detailed catalog that enhances data accessibility and usage. Users have the ability to design workflows that enable them to organize a sequence of tasks, establishing an efficient order and combination to optimize data processing. This capability allows for increased productivity and ensures that users can better capitalize on their data resources.

SQL Secure allows database administrators to manage SQL Server security in virtual, physical, and cloud environments. This includes managed cloud databases. It is different from other competitors because it allows for configurable data collection and customizable templates to meet audits for multiple regulatory guidelines.

CData Sync is a universal database pipeline that automates continuous replication between hundreds SaaS applications & cloud-based data sources. It also supports any major data warehouse or database, whether it's on-premise or cloud. Replicate data from hundreds cloud data sources to popular databases destinations such as SQL Server and Redshift, S3, Snowflake and BigQuery. It is simple to set up replication: log in, select the data tables you wish to replicate, then select a replication period. It's done. CData Sync extracts data iteratively. It has minimal impact on operational systems. CData Sync only queries and updates data that has been updated or added since the last update. CData Sync allows for maximum flexibility in partial and full replication scenarios. It ensures that critical data is safely stored in your database of choice. Get a 30-day trial of the Sync app for free or request more information at www.cdata.com/sync

Presto serves as an open-source distributed SQL query engine designed for executing interactive analytic queries across data sources that can range in size from gigabytes to petabytes. It addresses the challenges faced by data engineers who often navigate multiple query languages and interfaces tied to isolated databases and storage systems. Presto stands out as a quick and dependable solution by offering a unified ANSI SQL interface for comprehensive data analytics and your open lakehouse. Relying on different engines for various workloads often leads to the necessity of re-platforming in the future. However, with Presto, you benefit from a singular, familiar ANSI SQL language and one engine for all your analytic needs, negating the need to transition to another lakehouse engine. Additionally, it efficiently accommodates both interactive and batch workloads, handling small to large datasets and scaling from just a few users to thousands. By providing a straightforward ANSI SQL interface for all your data residing in varied siloed systems, Presto effectively integrates your entire data ecosystem, fostering seamless collaboration and accessibility across platforms. Ultimately, this integration empowers organizations to make more informed decisions based on a comprehensive view of their data landscape.

AtScale streamlines and enhances business intelligence, leading to quicker insights, improved decision-making, and greater returns on your cloud analytics investments. By removing tedious data engineering tasks such as data curation and delivery for analysis, it allows teams to focus on strategic initiatives. Centralizing business definitions ensures that KPI reporting remains consistent across various BI platforms. This solution not only speeds up the process of gaining insights from data but also manages cloud computing expenses more effectively. You can utilize existing data security protocols for analytics regardless of the data's location. With AtScale’s Insights workbooks and models, users can conduct multidimensional Cloud OLAP analyses on datasets from diverse sources without the need for preparation or engineering of data. Our intuitive dimensions and measures are designed to facilitate quick insight generation that directly informs business strategies, ensuring that teams make informed decisions efficiently. Overall, AtScale empowers organizations to maximize their data's potential while minimizing the complexity associated with traditional analytics processes.

Elevate your integration capabilities with the most extensive, microservices-oriented, API-centric, and AI-enhanced enterprise iPaaS available. Utilizing the advanced CLAIRE engine, IICS accommodates a wide array of cloud-native integration needs, including data, application, API integration, and Master Data Management (MDM). Our global reach and support for multiple cloud environments extend to major platforms like Microsoft Azure, AWS, Google Cloud Platform, and Snowflake. With unmatched enterprise scalability and a robust security framework backed by numerous certifications, IICS stands as a pillar of trust in the industry. This enterprise iPaaS features a suite of cloud data management solutions designed to boost efficiency while enhancing speed and scalability. Once again, Informatica has been recognized as a Leader in the Gartner 2020 Magic Quadrant for Enterprise iPaaS, reinforcing our commitment to excellence. Experience firsthand insights and testimonials about Informatica Intelligent Cloud Services, and take advantage of our complimentary cloud offerings. Our customers remain our top priority in all facets, including products, services, and support, which is why we've consistently achieved outstanding customer loyalty ratings for over a decade. Join us in redefining integration excellence and discover how we can help transform your business operations.

Varada offers a cutting-edge big data indexing solution that adeptly balances performance and cost while eliminating the need for data operations. This distinct technology acts as an intelligent acceleration layer within your data lake, which remains the central source of truth and operates within the customer's cloud infrastructure (VPC). By empowering data teams to operationalize their entire data lake, Varada facilitates data democratization while ensuring fast, interactive performance, all without requiring data relocation, modeling, or manual optimization. The key advantage lies in Varada's capability to automatically and dynamically index pertinent data, maintaining the structure and granularity of the original source. Additionally, Varada ensures that any query can keep pace with the constantly changing performance and concurrency demands of users and analytics APIs, while also maintaining predictable cost management. The platform intelligently determines which queries to accelerate and which datasets to index, while also flexibly adjusting the cluster to match demand, thereby optimizing both performance and expenses. This holistic approach to data management not only enhances operational efficiency but also allows organizations to remain agile in an ever-evolving data landscape.

SAP HANA is an in-memory database designed to handle both transactional and analytical workloads using a single copy of data, regardless of type. It effectively dissolves the barriers between transactional and analytical processes within organizations, facilitating rapid decision-making whether deployed on-premises or in the cloud. This innovative database management system empowers users to create intelligent, real-time solutions, enabling swift decision-making from a unified data source. By incorporating advanced analytics, it enhances the capabilities of next-generation transaction processing. Organizations can build data solutions that capitalize on cloud-native attributes such as scalability, speed, and performance. With SAP HANA Cloud, businesses can access reliable, actionable information from one cohesive platform while ensuring robust security, privacy, and data anonymization, reflecting proven enterprise standards. In today's fast-paced environment, an intelligent enterprise relies on timely insights derived from data, emphasizing the need for real-time delivery of such valuable information. As the demand for immediate access to insights grows, leveraging an efficient database like SAP HANA becomes increasingly critical for organizations aiming to stay competitive.

We make BI and Big Data analytics easier and more efficient. Our goal is to empower business users, make BI specialists and always-busy business more independent when solving data-driven business problems. Querona is a solution for those who have ever been frustrated by a lack in data, slow or tedious report generation, or a long queue to their BI specialist. Querona has a built-in Big Data engine that can handle increasing data volumes. Repeatable queries can be stored and calculated in advance. Querona automatically suggests improvements to queries, making optimization easier. Querona empowers data scientists and business analysts by giving them self-service. They can quickly create and prototype data models, add data sources, optimize queries, and dig into raw data. It is possible to use less IT. Users can now access live data regardless of where it is stored. Querona can cache data if databases are too busy to query live.

The Hammerspace Global Data Environment offers worldwide visibility and accessibility of network shares, connecting remote data centers and public clouds seamlessly. It stands out as the only genuinely global file system that utilizes metadata replication, file-specific data services, an intelligent policy engine, and seamless data orchestration, ensuring that you can access your data exactly when and where it is needed. With Hammerspace, intelligent policies are employed to effectively orchestrate and manage your data resources. The objective-based policy engine is a powerful feature that enhances file-specific data services and orchestration capabilities. These services empower businesses to operate in new and innovative ways that were previously hindered by cost and performance limitations. Additionally, you can choose which files to relocate or replicate to designated locations, either through the objective-based policy engine or as needed, providing unparalleled flexibility in data management. This innovative approach enables organizations to optimize their data usage and enhance operational efficiency.

Adoki simplifies the process of transferring data across various platforms and systems, including data warehouses, databases, cloud services, Hadoop environments, and streaming applications, accommodating both single and scheduled transfers. It tailors itself to the demands of your IT framework, optimizing data transfer or replication activities to occur at the most suitable times. By providing centralized oversight and control of data transfers, Adoki empowers you to manage your data operations effectively, potentially reducing the size of your team while enhancing efficiency. This streamlined approach not only saves time but also minimizes the risk of errors during data handling.

data.world is a cloud-native service meticulously designed for contemporary data architectures, ensuring seamless management of updates, migrations, and ongoing maintenance. This streamlined setup process is complemented by a vast and expanding ecosystem of pre-built integrations with all major cloud data warehouses. When prompt results are essential, your team should concentrate on addressing genuine business challenges rather than grappling with cumbersome data management software. data.world simplifies the process for all users, not just data experts, enabling them to obtain clear, precise, and prompt answers to various business inquiries. Our platform features a cloud-based data catalog that connects isolated and distributed data to well-known business concepts, fostering a cohesive knowledge base that everyone can access, comprehend, and utilize. Furthermore, beyond our enterprise solutions, data.world hosts the largest collaborative open data community globally, where individuals collaborate on diverse projects ranging from social bot detection to acclaimed data journalism initiatives, promoting innovation and shared learning. This unique environment encourages knowledge sharing and empowers users to leverage data in creative and impactful ways.

CData Connect Real-time operational and business data is critical for your organization to provide actionable insights and drive growth. CData Connect is the missing piece in your data value chain. CData Connect allows direct connectivity to any application that supports standard database connectivity. This includes popular cloud BI/ETL applications such as: - Amazon Glue - Amazon QuickSight Domo - Google Apps Script - Google Cloud Data Flow - Google Cloud Data Studio - Looker - Microsoft Power Apps - Microsoft Power Query - MicroStrategy Cloud - Qlik Sense Cloud - SAP Analytics Cloud SAS Cloud SAS Viya - Tableau Online ... and many other things! CData Connect acts as a data gateway by translating SQL and securely proxying API calls.

You can integrate your apps with just a few clicks and not by writing code. You can get up and running in under an hour with pre-built templates and an intuitive interface. DBSync Cloud Workflow offers a robust integration platform that is available on both cloud-based and SaaS. DBSync Cloud Workflow is easily integrated into API interfaces, laptops or desktops, mobile phones or tablets. Connect to Accounting systems, Popular Databases and Apps CRM's. Any connector can be easily integrated using a custom workflow. Use out-of-the box integration Maps and Processes to help with common use cases such as CRM, Accounting integration, data replication, and other areas. You can use it as-is or modify it to suit your needs. Automate complex business processes by developing, managing and automating them into simple workflows. Support for newer archiving technology like Cassandra and Hive, Amazon RedShift and many more.

Alibaba Cloud Data Integration serves as an all-encompassing platform for data synchronization, enabling both real-time and offline data transfers among a variety of data sources, networks, and geographical locations. It accommodates synchronization between over 400 different data source combinations, covering RDS databases, semi-structured storage, unstructured storage—which includes audio, video, and images—NoSQL databases, and extensive data storage solutions. Furthermore, the platform supports real-time data transactions among various sources like Oracle, MySQL, and DataHub. Users can also automate offline tasks by establishing specific triggers based on year, month, day, hour, and minute, which simplifies the process of periodic incremental data extraction. In addition, it integrates effectively with DataWorks for data modeling, fostering a streamlined operations and maintenance workflow. By utilizing Hadoop clusters, the platform enhances its ability to synchronize HDFS data with MaxCompute efficiently. This versatility makes Alibaba Cloud Data Integration an invaluable tool for organizations seeking to optimize their data management processes.

Streamline the deployment processes for SQL Server, Oracle, and an additional 18 databases to enhance both the frequency and reliability of updates. This adaptable toolchain promotes seamless integration across various teams, allowing for rapid identification of errors while accelerating development through Continuous Integration. Gain comprehensive oversight of every modification made to your databases. Redgate Deploy empowers your teams to automate database development workflows, accelerating software delivery while maintaining high-quality code. By enhancing your existing continuous delivery framework for applications and leveraging Redgate’s premier tools alongside the Flyway migrations framework, Redgate Deploy effectively integrates DevOps practices into database management. Additionally, automate your database change deployments to facilitate quicker updates through your pipeline. To ensure both quality and uniformity, Redgate Deploy offers processes that can be consistently replicated at every phase, from version control right through to live deployment, ultimately fostering a more efficient development environment. With these capabilities, teams can focus on innovation while minimizing the risks associated with database changes.

Stitch is a cloud-based platform that allows you to extract, transform, load data. Stitch is used by more than 1000 companies to move billions records daily from SaaS databases and applications into data warehouses or data lakes.

Conventional techniques for integrating mainframe data, such as ETL, data warehouses, and connector development, are increasingly inadequate in terms of speed, accuracy, and efficiency in today’s business landscape. As the amount of data generated and stored on mainframes continues to surge, these outdated methods fall further behind. Data virtualization emerges as the solution to bridge this growing divide, automating the accessibility of mainframe data for developers and applications alike. This approach allows organizations to discover and map their data just once, after which it can be easily virtualized and reused across various platforms. Ultimately, this capability enables your data to align with your business goals and aspirations. By leveraging data virtualization on z/OS, organizations can simplify the complexities associated with mainframe resources. Moreover, data virtualization facilitates the integration of data from numerous disparate sources into a cohesive logical repository, significantly enhancing the ability to connect mainframe information with distributed applications. This method also allows for the enrichment of mainframe data by incorporating insights from location, social media, and other external datasets, promoting a more comprehensive understanding of business dynamics.

Establish federated source data identifiers to allow users to connect to various data sources seamlessly. Utilize a web-based administrative console to streamline the management of user access, privileges, and authorizations for easier oversight. Incorporate data quality enhancements such as match-code generation and parsing functions within the view to ensure high-quality data. Enhance performance through the use of in-memory data caches and efficient scheduling methods. Protect sensitive information with robust data masking and encryption techniques. This approach keeps application queries up-to-date and readily accessible to users while alleviating the burden on operational systems. You can set access permissions at multiple levels, including catalog, schema, table, column, and row, allowing for tailored security measures. The advanced capabilities for data masking and encryption provide the ability to control not just who can see your data but also the specific details they can access, thereby significantly reducing the risk of sensitive information being compromised. Ultimately, these features work together to create a secure and efficient data management environment.

Oracle Big Data Preparation Cloud Service is a comprehensive managed Platform as a Service (PaaS) solution that facilitates the swift ingestion, correction, enhancement, and publication of extensive data sets while providing complete visibility in a user-friendly environment. This service allows for seamless integration with other Oracle Cloud Services, like the Oracle Business Intelligence Cloud Service, enabling deeper downstream analysis. Key functionalities include profile metrics and visualizations, which become available once a data set is ingested, offering a visual representation of profile results and summaries for each profiled column, along with outcomes from duplicate entity assessments performed on the entire data set. Users can conveniently visualize governance tasks on the service's Home page, which features accessible runtime metrics, data health reports, and alerts that keep them informed. Additionally, you can monitor your transformation processes and verify that files are accurately processed, while also gaining insights into the complete data pipeline, from initial ingestion through to enrichment and final publication. The platform ensures that users have the tools needed to maintain control over their data management tasks effectively.

Today, there is a considerable amount of discussion surrounding how top-tier companies are leveraging big data to achieve a competitive edge. Your organization aims to join the ranks of these industry leaders. Nevertheless, the truth is that more than 80% of big data initiatives fail to reach production due to the intricate and resource-heavy nature of implementation, often extending over months or even years. The technology involved is multifaceted, and finding individuals with the requisite skills can be prohibitively expensive or nearly impossible. Moreover, automating the entire data workflow from its source to its end use is essential for success. This includes automating the transition of data and workloads from outdated Data Warehouse systems to modern big data platforms, as well as managing and orchestrating intricate data pipelines in a live environment. In contrast, alternative methods like piecing together various point solutions or engaging in custom development tend to be costly, lack flexibility, consume excessive time, and necessitate specialized expertise to build and sustain. Ultimately, adopting a more streamlined approach to big data management can not only reduce costs but also enhance operational efficiency.

Regardless of the location of your data—whether in cloud environments, traditional systems, or data lakes such as Hadoop—SAS Data Management provides the tools necessary to access the information you require. You can establish data management protocols once and apply them repeatedly, allowing for a consistent and efficient approach to enhancing and unifying data without incurring extra expenses. IT professionals often find themselves managing responsibilities beyond their typical scope, but SAS Data Management empowers your business users to make data updates, adjust workflows, and conduct their own analyses, thereby allowing you to concentrate on other initiatives. Moreover, the inclusion of a comprehensive business glossary along with SAS and third-party metadata management and lineage visualization features ensures that all team members remain aligned. The integrated nature of SAS Data Management technology means you won't have to deal with a disjointed solution; rather, all components, ranging from data quality to data federation, operate within a unified architecture, providing seamless functionality. This cohesive system fosters collaboration and enhances overall productivity across your organization.