Best Data Management Software for Azure Marketplace - Page 6

Introducing an accessible, open-source solution that empowers everyone within your organization to seek answers and gain insights from data. Seamlessly connect your data and present it to your team with ease. Creating, sharing, and exploring dashboards is straightforward and user-friendly. Team members, from the CEO to Customer Support, can access answers to their data-related inquiries with just a few clicks. For more complex questions, the SQL capabilities and our notebook editor cater to those with advanced data skills. Tools such as visual joins, multiple aggregations, and filtering options enable you to delve deeper into your data for comprehensive analysis. Enhance your queries by incorporating variables to produce interactive visualizations that can be adjusted by users for exploration. You can also configure alerts and scheduled reports to ensure the right information reaches the appropriate individuals at the ideal moment. Getting started is simple with the hosted version, or you can opt for Docker to set everything up independently at no cost. Once you connect to your existing data and invite your team, you’ll have a robust BI solution that typically requires a sales pitch. This empowers your organization to make data-driven decisions swiftly and effectively.

The pioneering integration of 'in-line' edge detection alongside swift ransomware recovery capabilities instills confidence in IT professionals to effectively counter cyber threats. Nasuni is revolutionizing the file storage sector through its cloud-centric model, which supplants conventional on-premises primary and secondary storage solutions. By utilizing object storage technology, Nasuni offers a file storage platform that is not only simpler and more cost-effective but also more efficient as a SaaS offering that adapts seamlessly to the rapid growth of unstructured data. This innovative solution allows for cloud file storage across countless locations from a unified console, ensuring on-demand capacity when and where it is required, all while incorporating inherent backup and disaster recovery features. Designed to support cloud, hybrid cloud, and traditional on-premises setups, Nasuni consolidates various data silos and toolsets into a singular global file system that provides a comprehensive overview of your file data while being straightforward to deploy and manage. Ultimately, this approach empowers organizations to streamline their file storage processes, enhancing overall operational efficiency.

AI Cloud represents an innovative strategy designed to meet the current demands, challenges, and potential of artificial intelligence. This comprehensive system acts as a single source of truth, expediting the process of bringing AI solutions into production for organizations of all sizes. Users benefit from a collaborative environment tailored for ongoing enhancements throughout the entire AI lifecycle. The AI Catalog simplifies the process of discovering, sharing, tagging, and reusing data, which accelerates deployment and fosters teamwork. This catalog ensures that users can easily access relevant data to resolve business issues while maintaining high standards of security, compliance, and consistency. If your database is subject to a network policy restricting access to specific IP addresses, please reach out to Support for assistance in obtaining a list of IPs that should be added to your network policy for whitelisting, ensuring that your operations run smoothly. Additionally, leveraging AI Cloud can significantly improve your organization’s ability to innovate and adapt in a rapidly evolving technological landscape.

Neo4j's graph platform is designed to help you leverage data and data relationships. Developers can create intelligent applications that use Neo4j to traverse today's interconnected, large datasets in real-time. Neo4j's graph database is powered by a native graph storage engine and processing engine. It provides unique, actionable insights through an intuitive, flexible, and secure database.

PostgreSQL stands out as a highly capable, open-source object-relational database system that has been actively developed for more than three decades, earning a solid reputation for its reliability, extensive features, and impressive performance. Comprehensive resources for installation and usage are readily available in the official documentation, which serves as an invaluable guide for both new and experienced users. Additionally, the open-source community fosters numerous forums and platforms where individuals can learn about PostgreSQL, understand its functionalities, and explore job opportunities related to it. Engaging with this community can enhance your knowledge and connection to the PostgreSQL ecosystem. Recently, the PostgreSQL Global Development Group announced updates for all supported versions, including 15.1, 14.6, 13.9, 12.13, 11.18, and 10.23, which address 25 reported bugs from the past few months. Notably, this marks the final release for PostgreSQL 10, meaning that it will no longer receive any security patches or bug fixes going forward. Therefore, if you are currently utilizing PostgreSQL 10 in your production environment, it is highly recommended that you plan to upgrade to a more recent version to ensure continued support and security. Upgrading will not only help maintain the integrity of your data but also allow you to take advantage of the latest features and improvements introduced in newer releases.

Dell EMC Avamar facilitates quick and efficient data backup and recovery by utilizing its advanced variable-length deduplication technology. It is specifically designed to perform rapid, daily full backups across a range of environments, including physical and virtual systems, NAS servers, enterprise applications, as well as remote offices and personal devices. Available in both virtual edition and as part of the comprehensive Dell EMC Data Protection Suite, Avamar provides a wide array of data protection software options. It is particularly effective for virtual environments and ensures application-consistent recovery for critical enterprise applications. By employing variable-length deduplication, it achieves impressive performance while minimizing costs. Additionally, it offers a user-friendly centralized management interface and robust encryption features to enhance data security. Moreover, Dell Technologies On Demand presents an extensive array of consumption-based and as-a-service solutions that align perfectly with the evolving needs of on-premises infrastructure and services in today’s on-demand economy. This flexibility ensures that businesses can scale their resources efficiently while maintaining control over their data management strategies.

The Apache Hadoop software library serves as a framework for the distributed processing of extensive data sets across computer clusters, utilizing straightforward programming models. It is built to scale from individual servers to thousands of machines, each providing local computation and storage capabilities. Instead of depending on hardware for high availability, the library is engineered to identify and manage failures within the application layer, ensuring that a highly available service can run on a cluster of machines that may be susceptible to disruptions. Numerous companies and organizations leverage Hadoop for both research initiatives and production environments. Users are invited to join the Hadoop PoweredBy wiki page to showcase their usage. The latest version, Apache Hadoop 3.3.4, introduces several notable improvements compared to the earlier major release, hadoop-3.2, enhancing its overall performance and functionality. This continuous evolution of Hadoop reflects the growing need for efficient data processing solutions in today's data-driven landscape.

Apache Spark™ serves as a comprehensive analytics platform designed for large-scale data processing. It delivers exceptional performance for both batch and streaming data by employing an advanced Directed Acyclic Graph (DAG) scheduler, a sophisticated query optimizer, and a robust execution engine. With over 80 high-level operators available, Spark simplifies the development of parallel applications. Additionally, it supports interactive use through various shells including Scala, Python, R, and SQL. Spark supports a rich ecosystem of libraries such as SQL and DataFrames, MLlib for machine learning, GraphX, and Spark Streaming, allowing for seamless integration within a single application. It is compatible with various environments, including Hadoop, Apache Mesos, Kubernetes, and standalone setups, as well as cloud deployments. Furthermore, Spark can connect to a multitude of data sources, enabling access to data stored in systems like HDFS, Alluxio, Apache Cassandra, Apache HBase, and Apache Hive, among many others. This versatility makes Spark an invaluable tool for organizations looking to harness the power of large-scale data analytics.

Aggregate all your data seamlessly using Enterprise plugins such as Splunk, ServiceNow, Datadog, and others. The integrated collaboration tools enable teams to engage efficiently from a unified dashboard. With enhanced security and compliance features, you can rest assured that your data remains protected at all times. Gain insights from experts in Prometheus, Graphite, and Grafana, along with dedicated support teams ready to assist. While other providers may promote a "one-size-fits-all" database solution, Grafana Labs adopts a different philosophy: we focus on empowering your observability rather than controlling it. Grafana Enterprise offers access to a range of enterprise plugins that seamlessly integrate your current data sources into Grafana. This innovative approach allows you to maximize the potential of your sophisticated and costly monitoring systems by presenting all your data in a more intuitive and impactful manner. Ultimately, our goal is to enhance your data visualization experience, making it simpler and more effective for your organization.

Kibana serves as a free and open user interface that enables the visualization of your Elasticsearch data while providing navigational capabilities within the Elastic Stack. You can monitor query loads or gain insights into how requests traverse your applications. This platform offers flexibility in how you choose to represent your data. With its dynamic visualizations, you can start with a single inquiry and discover new insights along the way. Kibana comes equipped with essential visual tools such as histograms, line graphs, pie charts, and sunbursts, among others. Additionally, it allows you to conduct searches across all your documents seamlessly. Utilize Elastic Maps to delve into geographic data or exercise creativity by visualizing custom layers and vector shapes. You can also conduct sophisticated time series analyses on your Elasticsearch data using our specially designed time series user interfaces. Furthermore, articulate queries, transformations, and visual representations with intuitive and powerful expressions that are easy to master. By employing these features, you can uncover deeper insights into your data, enhancing your overall analytical capabilities.

The significance of streaming data derived from operations, transactions, sensors, and IoT devices becomes apparent when it is thoroughly comprehended. SAS's event stream processing offers a comprehensive solution that encompasses streaming data quality, analytics, and an extensive selection of SAS and open source machine learning techniques alongside high-frequency analytics. This integrated approach facilitates the connection, interpretation, cleansing, and comprehension of streaming data seamlessly. Regardless of the velocity at which your data flows, the volume of data you manage, or the diversity of data sources you utilize, you can oversee everything effortlessly through a single, user-friendly interface. Moreover, by defining patterns and addressing various scenarios across your entire organization, you can remain adaptable and proactively resolve challenges as they emerge while enhancing your overall operational efficiency.

Combine data silos effortlessly using Azure Data Factory, a versatile service designed to meet diverse data integration requirements for users of all expertise levels. You can easily create both ETL and ELT workflows without any coding through its user-friendly visual interface, or opt to write custom code if you prefer. The platform supports the seamless integration of data sources with over 90 pre-built, hassle-free connectors, all at no extra cost. With a focus on your data, this serverless integration service manages everything else for you. Azure Data Factory serves as a robust layer for data integration and transformation, facilitating your digital transformation goals. Furthermore, it empowers independent software vendors (ISVs) to enhance their SaaS applications by incorporating integrated hybrid data, enabling them to provide more impactful, data-driven user experiences. By utilizing pre-built connectors and scalable integration capabilities, you can concentrate on enhancing user satisfaction while Azure Data Factory efficiently handles the backend processes, ultimately streamlining your data management efforts.

Foundry is a transformative data platform built to help solve the modern enterprise’s most critical problems by creating a central operating system for an organization’s data, while securely integrating siloed data sources into a common analytics and operations picture. Palantir works with commercial companies and government organizations alike to close the operational loop, feeding real-time data into your data science models and updating source systems. With a breadth of industry-leading capabilities, Palantir can help enterprises traverse and operationalize data to enable and scale decision-making, alongside best-in-class security, data protection, and governance. Foundry was named by Forrester as a leader in the The Forrester Wave™: AI/ML Platforms, Q3 2022. Scoring the highest marks possible in product vision, performance, market approach, and applications criteria. As a Dresner-Award winning platform, Foundry is the overall leader in the BI and Analytics market and rated a perfect 5/5 by its customer base.

Instead of transferring data to a centralized system for analysis, Zetaris allows for immediate analytics across all your data in real-time. This innovative approach lets you link various databases and examine them simultaneously, eliminating the delays and expenses typically associated with data migration. Our proprietary analytical query optimizer guarantees both speed and scalability for any query executed across diverse data sources. By keeping the data at its original location, you can maintain strict data governance and security without the need for movement. No need for data extraction, transformation, or duplication into another repository; this significantly reduces unnecessary storage and processing costs. Embrace a more efficient way of data handling that streamlines operations while enhancing security.

CluedIn is the fastest master data management platform to implement. CluedIn transformed traditional MDM into an enhanced experience. There is less manual work. You get better results. This is impossible with traditional MDM. CluedIn revolutionized MDM by introducing a new type without restrictions. CluedIn was designed to eliminate the complexities of traditional MDM. CluedIn, a cloud-native Master Data Management Platform, was designed to be low-cost. Enterprise software that is as easy to use as a SAAS platform. Traditional MDM vendors will require you to connect different products to create an end-to-end story. We have instead gathered the core pillars of masterdata management for you. We went against the grain of traditional master data management, and came out the other end with methods that automate the most difficult parts and render traditional approaches obsolete.

Safeguard your data and implement governance controls for contemporary cloud workloads across your dynamic physical, virtual, and cloud infrastructures. Tackle the ever-evolving landscape of growth and IT complexity by utilizing Dell EMC’s software-defined data protection solutions. The PowerProtect Data Manager facilitates next-generation data protection that accelerates IT transformation, while ensuring you can effectively secure and swiftly access the value of your data. With its comprehensive software-defined protection features, automated discovery, deduplication, operational flexibility, self-service options, and IT governance, Dell EMC PowerProtect Data Manager is tailored for physical, virtual, and cloud settings. Furthermore, it enhances data protection capabilities by leveraging the latest advancements in Dell EMC's trusted protection storage architecture, ensuring your data remains secure and readily available. By adopting these innovative solutions, organizations can maintain a robust data management strategy while adapting to the swiftly changing technological landscape.

Utilizing graph analytics throughout the customer lifecycle can help uncover hidden risks and unveil unexpected opportunities. Conventional Master Data Management (MDM) solutions struggle to accommodate the vast amounts of distributed and diverse data generated from various applications and external sources. The traditional methods of probabilistic matching in MDM are ineffective when dealing with siloed data sources, leading to missed connections and a lack of context, ultimately resulting in poor decision-making and uncapitalized business value. An inadequate MDM solution can have widespread repercussions, negatively impacting both the customer experience and operational efficiency. When there's no immediate access to comprehensive payment patterns, trends, and risks, your team’s ability to make informed decisions swiftly is compromised, compliance expenses increase, and expanding coverage becomes a challenge. If your data remains unintegrated, it creates fragmented customer experiences across different channels, business sectors, and regions. Efforts to engage customers on a personal level often fail, as they rely on incomplete and frequently outdated information, highlighting the urgent need for a more cohesive approach to data management. This lack of a unified data strategy not only hampers customer satisfaction but also stifles business growth opportunities.

QuestDB is an advanced relational database that focuses on column-oriented storage optimized for time series and event-driven data. It incorporates SQL with additional features tailored for time-based analytics to facilitate real-time data processing. This documentation encompasses essential aspects of QuestDB, including initial setup instructions, comprehensive usage manuals, and reference materials for syntax, APIs, and configuration settings. Furthermore, it elaborates on the underlying architecture of QuestDB, outlining its methods for storing and querying data, while also highlighting unique functionalities and advantages offered by the platform. A key feature is the designated timestamp, which empowers time-focused queries and efficient data partitioning. Additionally, the symbol type enhances the efficiency of managing and retrieving frequently used strings. The storage model explains how QuestDB organizes records and partitions within its tables, and the use of indexes can significantly accelerate read access for specific columns. Moreover, partitions provide substantial performance improvements for both calculations and queries. With its SQL extensions, users can achieve high-performance time series analysis using a streamlined syntax that simplifies complex operations. Overall, QuestDB stands out as a powerful tool for handling time-oriented data effectively.

Utilize widely-used open-source frameworks like Apache Hadoop, Spark, Hive, and Kafka with Azure HDInsight, a customizable and enterprise-level service designed for open-source analytics. Effortlessly manage vast data sets while leveraging the extensive open-source project ecosystem alongside Azure’s global capabilities. Transitioning your big data workloads to the cloud is straightforward and efficient. You can swiftly deploy open-source projects and clusters without the hassle of hardware installation or infrastructure management. The big data clusters are designed to minimize expenses through features like autoscaling and pricing tiers that let you pay solely for your actual usage. With industry-leading security and compliance validated by over 30 certifications, your data is well protected. Additionally, Azure HDInsight ensures you remain current with the optimized components tailored for technologies such as Hadoop and Spark, providing an efficient and reliable solution for your analytics needs. This service not only streamlines processes but also enhances collaboration across teams.

Break down data silos through a unified storage solution that effectively optimizes expenses by employing tiered storage and comprehensive policy management. Enhance data authentication with Azure Active Directory (Azure AD) alongside role-based access control (RBAC), while bolstering data protection with features such as encryption at rest and advanced threat protection. This approach ensures a highly secure environment with adaptable mechanisms for safeguarding access, encryption, and network-level governance. Utilizing a singular storage platform, you can seamlessly ingest, process, and visualize data while supporting prevalent analytics frameworks. Cost efficiency is further achieved through the independent scaling of storage and compute resources, lifecycle policy management, and object-level tiering. With Azure's extensive global infrastructure, you can effortlessly meet diverse capacity demands and manage data efficiently. Additionally, conduct large-scale analytical queries with consistently high performance, ensuring that your data management meets both current and future needs.

Harness the power of your data and create innovative artificial intelligence (AI) solutions using Azure Databricks, where you can establish your Apache Spark™ environment in just minutes, enable autoscaling, and engage in collaborative projects within a dynamic workspace. This platform accommodates multiple programming languages such as Python, Scala, R, Java, and SQL, along with popular data science frameworks and libraries like TensorFlow, PyTorch, and scikit-learn. With Azure Databricks, you can access the most current versions of Apache Spark and effortlessly connect with various open-source libraries. You can quickly launch clusters and develop applications in a fully managed Apache Spark setting, benefiting from Azure's expansive scale and availability. The clusters are automatically established, optimized, and adjusted to guarantee reliability and performance, eliminating the need for constant oversight. Additionally, leveraging autoscaling and auto-termination features can significantly enhance your total cost of ownership (TCO), making it an efficient choice for data analysis and AI development. This powerful combination of tools and resources empowers teams to innovate and accelerate their projects like never before.

Harness the capabilities of both private and public clouds through a unique hybrid data platform tailored for contemporary data architectures, enabling data access from any location. Cloudera stands out as a hybrid data platform that offers unparalleled flexibility, allowing users to choose any cloud, any analytics solution, and any type of data. It streamlines data management and analytics, ensuring optimal performance, scalability, and security for data accessibility from anywhere. By leveraging Cloudera, organizations can benefit from the strengths of both private and public clouds, leading to quicker value realization and enhanced control over IT resources. Moreover, Cloudera empowers users to securely transfer data, applications, and individuals in both directions between their data center and various cloud environments, irrespective of the data's physical location. This bi-directional capability not only enhances operational efficiency but also fosters a more adaptable and responsive data strategy.

Enhance your ability to swiftly and efficiently adapt to changes by effectively managing your master data, whether it's during a cloud application migration, addressing the impacts of mergers and acquisitions, or harmonizing metadata discrepancies across various business functions and applications. You can import lists or hierarchies from different applications that contribute to your data ecosystem. By doing so, you can streamline processes and eliminate the need for data validation during entry, even when dealing with subpar data quality. Furthermore, you can elevate the overall quality of data within a specific application or business sector by validating distinct perspectives, referred to as viewpoints. Additionally, effortlessly migrate and map enterprise data elements along with ongoing modifications across diverse environments, including public, private, and hybrid clouds, whether they originate from Oracle or other third-party sources. With a user-friendly shopping cart interface, you can easily create new enterprise data or modify existing relationships and attributes, empowering you to manage your data landscape more effectively. This approach not only simplifies the data management process but also enhances collaboration across teams.

Squid serves as a caching proxy for web traffic, accommodating protocols such as HTTP, HTTPS, and FTP among others. By caching commonly accessed web pages, it significantly decreases bandwidth usage and enhances response times. With its robust access control features, Squid functions effectively as a server accelerator. It is compatible with a range of operating systems, including Windows, and operates under the GNU GPL license. Many Internet service providers globally rely on Squid to optimize user web access. By streamlining the data flow between clients and servers, Squid not only boosts performance but also conserves bandwidth by storing frequently accessed content. Additionally, it has the capability to manage content requests through various routing methods, allowing for the construction of cache server hierarchies that maximize network efficiency. Numerous online platforms utilize Squid to substantially improve their content delivery processes. Ultimately, implementing Squid can lead to a notable reduction in server strain and an enhancement in the speed at which content is delivered to users. Its effectiveness in managing web traffic makes it an invaluable tool for both service providers and website owners alike.

Semarchy's flexible, unified data platform will help you make better business decisions across your organization. xDI is the high-performance, flexible, extensible data integration that integrates all your data for all types and uses. Its single technology can federate all forms of data integration and maps business rules into executable code. xDI supports multi-cloud environments, on-premise, hybrid, and cloud environments.