Best On-Premises Data Management Software of 2026 - Page 15

Infobright DB is an enterprise-grade database that utilizes a columnar storage architecture, enabling business analysts to efficiently analyze data and rapidly generate reports. This versatile database can be implemented both on-premise and in cloud environments. It is designed to store and analyze substantial amounts of big data, facilitating interactive business intelligence and handling complex queries with ease. By enhancing query performance and lowering storage costs, it significantly boosts overall efficiency in analytics and reporting processes. With capabilities to manage hundreds of terabytes of data, Infobright DB overcomes the limitations often faced by traditional databases. This solution supports big data applications while removing the need for indexing and partitioning, resulting in no administrative burden. In an era where machine data is growing exponentially, IgniteTech’s Infobright DB is purpose-built to deliver exceptional performance for large quantities of machine-generated information. Furthermore, it allows users to manage intricate ad hoc analytical environments without the heavy database administration demands seen in other solutions. This makes it an invaluable tool for organizations seeking to optimize their data handling and analysis.

HEAVY.AI is a pioneer in accelerated analysis. The HEAVY.AI platform can be used by government and business to uncover insights in data that is beyond the reach of traditional analytics tools. The platform harnesses the huge parallelism of modern CPU/GPU hardware and is available both in the cloud or on-premise. HEAVY.AI was developed from research at Harvard and MIT Computer Science and Artificial Intelligence Laboratory. You can go beyond traditional BI and GIS and extract high-quality information from large datasets with no lag by leveraging modern GPU and CPU hardware. To get a complete picture of what, when and where, unify and explore large geospatial or time-series data sets. Combining interactive visual analytics, hardware accelerated SQL, advanced analytics & data sciences frameworks, you can find the opportunity and risk in your enterprise when it matters most.

IBM Storage Protect serves as a robust solution for data backup and recovery. It is integrated within the software-defined storage offerings of the IBM Storage suite. For those seeking backup and recovery solutions tailored specifically for SaaS applications, Storage Protect for Cloud is available. Formerly known as IBM Spectrum Protect, IBM Storage Protect ensures extensive data resilience across physical file servers, virtual platforms, and a diverse array of applications. Organizations have the capability to expand and manage billions of objects on each backup server. Clients benefit from reduced costs associated with backup infrastructure, thanks to inherent data efficiency features and options for data migration or copying to various destinations, including tape, public cloud services, and local object storage. Additionally, IBM Storage Protect can accommodate data from IBM Storage Protect Plus, enabling businesses to leverage their prior investments for sustained data retention and effective disaster recovery strategies. This flexibility and integration make IBM Storage Protect a versatile choice for modern data management needs.

FairCom DB is ideal to handle large-scale, mission critical core-business applications that demand performance, reliability, and scalability that cannot easily be achieved with other databases. FairCom DB provides predictable high-velocity transactions with big data analytics and massively parallel big-data processing. It provides developers with NoSQL APIs that allow them to process binary data at machine speed. ANSI SQL allows for simple queries and analysis over the same binary data. Verizon is one of the companies that has taken advantage of FairCom DB's flexibility. Verizon recently selected FairCom DB to be its in-memory database for the Verizon Intelligent Network Control Platform Transaction Server Migrating. FairCom DB, an advanced database engine, gives you a Continuum of Control that allows you to achieve unparalleled performance at a low total cost of ownership (TCO). FairCom DB doesn't conform to you. FairCom DB conforms. FairCom DB doesn't force you to conform to the database's limitations.

Direct is the fastest path from data to insight. Incorta empowers your business with a true self service data experience and breakthrough performance to make better decisions and achieve amazing results. Imagine if you could deliver data projects in days instead of weeks or months, instead of weeks and months with fragile ETL and expensive data warehouses. Our direct approach to analytics enables self-service on-premises or in the cloud with agility and performance. The world's most successful brands use Incorta to succeed where other analytics solutions fail. We offer connectors and pre-built solutions that can be used in your enterprise applications and technologies across multiple industries. Incorta's partners include Microsoft, eCapital and Wipro. They are responsible for delivering innovative solutions and customer success. Join our vibrant partner ecosystem.

Amazon EMR stands as the leading cloud-based big data solution for handling extensive datasets through popular open-source frameworks like Apache Spark, Apache Hive, Apache HBase, Apache Flink, Apache Hudi, and Presto. This platform enables you to conduct Petabyte-scale analyses at a cost that is less than half of traditional on-premises systems and delivers performance more than three times faster than typical Apache Spark operations. For short-duration tasks, you have the flexibility to quickly launch and terminate clusters, incurring charges only for the seconds the instances are active. In contrast, for extended workloads, you can establish highly available clusters that automatically adapt to fluctuating demand. Additionally, if you already utilize open-source technologies like Apache Spark and Apache Hive on-premises, you can seamlessly operate EMR clusters on AWS Outposts. Furthermore, you can leverage open-source machine learning libraries such as Apache Spark MLlib, TensorFlow, and Apache MXNet for data analysis. Integrating with Amazon SageMaker Studio allows for efficient large-scale model training, comprehensive analysis, and detailed reporting, enhancing your data processing capabilities even further. This robust infrastructure is ideal for organizations seeking to maximize efficiency while minimizing costs in their data operations.

Gilhari is a microservice framework that provides persistence for JSON objects in relational database. This microservice framework is available as a Docker image and can be configured according to an app-specific object or relational model. Gilhari exposes REST (Representational State Transfer) interface for APIs (POST/GET, PUT and DELETE ) to perform CRUD (Create. Retrieve. Update. Delete) operations on app-specific JSON objects. Here are some highlights from Gilhari: * Metadata driven, object model independent and database agnostic framework * Easily customizable/configurable to your JSON object model * JSON attributes can be mapped to table columns, allowing full query capabilities as well as optimizations * Supports complex object modeling, including 1-m, 1-m and m-m relationships * No code is required to handle REST APIs (POST/GET, PUT/DELETE), data exchange (CRUD), or database schema creation.

Arctera Enterprise Vault is an advanced data archiving solution that helps organizations maintain compliance with global regulations. It captures data from a wide array of communication platforms, ensuring compliance with industry standards like GDPR, SEC, and MiFID II. The platform features intelligent classification tools to organize and retain data according to specific needs, improving data supervision, search, and eDiscovery. Arctera supports fast and accurate data retrieval with Elasticsearch, delivering quick results for complex queries. Deployment options are flexible, offering on-prem, hybrid, or cloud solutions, including secure encryption and WORM storage. With enhanced security features like multi-factor authentication and privileged account management, Arctera ensures the integrity and confidentiality of sensitive information while maintaining compliance.

Effortlessly integrate your on-premises infrastructure with cloud solutions. VMware HCX facilitates the smooth transition of applications, workload redistribution, and ensures business continuity across various data centers and cloud environments. It enables the large-scale transfer of workloads between any VMware platform, allowing for migrations from vSphere 5.0+ to the latest vSphere versions in either cloud settings or modern data centers. Additionally, it supports conversions from KVM and Hyper-V to the latest vSphere versions. The platform is compatible with VMware Cloud Foundation, VMware Cloud on AWS, Azure VMware Services, and additional offerings. Users benefit from a variety of migration strategies tailored to their specific workload requirements. With the capability for live large-scale HCX vMotion migration of thousands of virtual machines, it promises zero downtime, significantly minimizing business interruptions. The solution includes a secure proxy for both vMotion and replication traffic, along with a migration planning and visibility dashboard that provides valuable insights. Automated migration-aware routing via NSX ensures seamless network connectivity, while WAN-optimized links facilitate migrations over the Internet or WAN. Featuring high-throughput Layer 2 extension and advanced traffic engineering, VMware HCX significantly enhances application migration efficiency and speed. This robust framework ultimately empowers organizations to make cloud transitions with confidence and ease.

Transition your data, applications, and workloads to the cloud seamlessly, ensuring zero downtime with Arcserve Live Migration, which is specifically crafted to facilitate your cloud transformation without causing any disruptions. This solution allows for the effortless relocation of your essential data and workloads to your chosen cloud destination while maintaining uninterrupted business operations. By streamlining the cutover process, it reduces complexity and provides a centralized console for managing the entire migration journey. Arcserve Live Migration makes the task of moving data, applications, and workloads straightforward and efficient. Its versatile architecture supports the migration of almost any data type or workload to various environments, including cloud, on-premises, or remote locations like edge computing, and is compatible with virtual, cloud, and physical systems alike. Furthermore, it automatically keeps files, databases, and applications synchronized between Windows and Linux systems and a secondary physical or virtual environment, whether located on-site, at a remote site, or in the cloud, ensuring consistent data integrity throughout the process. This comprehensive approach not only enhances operational efficiency but also provides peace of mind during critical migrations.

Oracle Exadata stands out as the premier platform for running Oracle Database, facilitating digital transformations, enhancing database performance, and lowering expenses. According to an analysis by Wikibon, customers experience increased availability, improved performance, and cost savings of up to 40% with Oracle Exadata. The platform offers flexible deployment options, including Oracle Cloud Infrastructure, Oracle Cloud@Customer, and on-premises solutions, allowing businesses to modernize their database infrastructure, migrate enterprise applications to the cloud, and swiftly execute digital transformations. Additionally, Oracle Exadata enables users to maintain exceptional performance, scalability, and reliability for Oracle Database, irrespective of the deployment environment. Customers can seamlessly transition workloads between on-premises data centers, Cloud@Customer setups, and Oracle Cloud Infrastructure, ultimately streamlining operations and enhancing cost efficiency. This versatility not only supports modernization but also empowers organizations to adapt to evolving technological demands effectively.

Data Safe serves as a comprehensive management hub for your Oracle Databases, enabling you to grasp the sensitivity levels of your data, analyze potential risks, and implement measures to mask sensitive information. It also facilitates the establishment and oversight of security protocols, user security evaluations, and user activity monitoring, while ensuring compliance with data protection regulations. Regardless of whether you're operating Oracle Autonomous Database, Oracle Database Cloud Service (including Exadata, virtual machines, or bare metal), or managing Oracle Databases within your own on-premises environment, Data Safe provides critical data security features that enhance your security posture and mitigate risks. Furthermore, it assists in assessing user risks by pinpointing crucial users, roles, and privileges, while allowing you to configure audit policies and gather user activity data to detect any anomalies. In addition, Data Safe aids in the identification of sensitive data, clarifying its locations, and minimizes risks associated with non-production data sets by effectively masking sensitive information. By leveraging these capabilities, organizations can foster a more secure data environment and maintain better control over their information assets.

Make informed decisions by efficiently testing and modeling intricate business assumptions, whether in the cloud or on-premises. Oracle Essbase empowers organizations to swiftly extract insights from multidimensional datasets through what-if analyses and data visualization tools. Forecasting both company and departmental performance becomes a straightforward task, enabling the development and management of analytic applications that leverage business drivers to simulate various what-if scenarios. Users can oversee workflows for multiple scenarios all within a unified interface, simplifying submissions and approvals. The sandboxing features allow for rapid testing and evaluation of models, ensuring the best-suited model is chosen for production. Additionally, financial and business analysts benefit from over 100 ready-to-use mathematical functions that can be effortlessly implemented to generate new data insights. This comprehensive approach enhances the strategic capabilities of organizations, ultimately driving better performance outcomes.

IBM® InfoSphere® Data Replication offers a log-based change data capture feature that ensures transactional integrity, which is essential for large-scale big data integration, consolidation, warehousing, and analytics efforts. This tool gives users the versatility to replicate data across various heterogeneous sources and targets seamlessly. Additionally, it facilitates zero-downtime migrations and upgrades, making it an invaluable resource. In the event of a failure, IBM InfoSphere Data Replication ensures continuous availability, allowing for quick workload switches to remote database replicas within seconds rather than hours. Participate in the beta program to gain an early insight into the innovative on-premises-to-cloud and cloud-to-cloud data replication functionalities. By joining, you can discover the criteria that make you a great fit for the beta testing and the benefits you can expect. Don’t miss the opportunity to sign up for the exclusive IBM Data Replication beta program and partner with us in shaping the future of this product. Your feedback will be crucial in refining these new capabilities.

Prefect is a Python-native automation platform built to orchestrate workflows and power AI applications at scale. It allows developers to convert simple Python functions into fully observable workflows using a lightweight, open-source framework. Prefect eliminates the need for complex rewrites while supporting production-grade orchestration. The platform offers managed services through Prefect Cloud, reducing operational overhead with autoscaling and enterprise security. Prefect Horizon provides managed AI infrastructure, enabling teams to deploy MCP servers and connect AI agents to internal systems. Both platforms run on the same codebase written by developers. Prefect delivers deep observability to help teams debug and optimize workflows efficiently. With zero vendor lock-in and Apache 2.0 licensing, it offers flexibility and control. Prefect is trusted by companies across industries to automate mission-critical processes. It supports faster deployment and reduced operational costs.

When deployed as an on-premises server, SQL Server Analysis Services provides comprehensive support for various model types, including tabular models at all compatibility levels based on the version, multidimensional models, data mining capabilities, and Power Pivot features for SharePoint. The standard process for implementation involves setting up a SQL Server Analysis Services instance, designing either a tabular or multidimensional data model, deploying this model as a database to the server instance, processing it to populate with data, and configuring user permissions to facilitate data access. Once the setup is complete, client applications that are compatible with Analysis Services can easily utilize the data model as a source. These models typically gather data from external systems, primarily from data warehouses utilizing either SQL Server or Oracle relational database engines, though tabular models can connect to a variety of additional data sources. This versatility makes SQL Server Analysis Services a powerful tool for analytics and business intelligence.

The rapid expansion of consumer data over the last ten years is now being eclipsed by a remarkable surge in business data, creating both unique opportunities and significant challenges for companies and cloud service providers alike. This situation necessitates a revolutionary approach to developing and scaling storage infrastructure. Our vision for this evolution is embodied in the Infinidat Elastic Data Fabric, which reimagines enterprise storage, transitioning from conventional hardware appliances to flexible, high-performance pools of digital storage that are both highly reliable and cost-effective, with effortless data mobility across data centers and public cloud environments. Today, professionals in various industries are grappling with a similar challenge due to the wave of digital transformation influencing their operations. As traditional hardware-based storage solutions are becoming prohibitively expensive and increasingly difficult to manage, they also fall drastically short of the requirements for the data-centric future. Consequently, it is imperative for these systems to transform into innovative software-defined on-premises enterprise storage clouds to meet the demands of the evolving digital landscape. This shift not only enhances efficiency but also positions organizations to better harness the power of their data.

Utilize Azure Table storage to manage petabytes of semi-structured data efficiently while keeping expenses low. In contrast to various data storage solutions, whether local or cloud-based, Table storage enables seamless scaling without the need for manual sharding of your dataset. Additionally, concerns about data availability are mitigated through the use of geo-redundant storage, which ensures that data is replicated three times within a single region and an extra three times in a distant region, enhancing data resilience. This storage option is particularly advantageous for accommodating flexible datasets—such as user data from web applications, address books, device details, and various other types of metadata—allowing you to develop cloud applications without restricting the data model to specific schemas. Each row in a single table can possess a unique structure, for instance, featuring order details in one entry and customer data in another, which grants you the flexibility to adapt your application and modify the table schema without requiring downtime. Furthermore, Table storage is designed with a robust consistency model to ensure reliable data access. Overall, it provides an adaptable and scalable solution for modern data management needs.

We gather personal information through a wide array of integrations with databases, CRM systems, ERP platforms, and proprietary applications, capturing both structured and unstructured data like emails, PDFs, Word documents, and spreadsheets. Our approach involves meticulously mapping data by monitoring all extraction points, enabling us to identify customer information with minimal input while accommodating billions of records. This consolidation process culminates in a visual or textual representation of the risks associated with the organization’s databases, employing a scoring system based on twelve key steps in alignment with the primary aspects of the LGPD. Notably, our solution is not dependent on any specific cloud provider technology, allowing for deployment in on-premises data centers or across various cloud environments. The architecture of Pontus Vision LGPD is designed to minimize manual intervention, facilitating the efficient processing of vast quantities of data. With the capability to handle billions of records seamlessly, Pontus Vision LGPD stands out as a modular solution adept at integrating data from numerous formats. Ultimately, our offering ensures compliance while enhancing data management efficiency across diverse systems.

Nowadays, many organizations are increasingly utilizing object and cloud storage to hold unstructured data, in addition to traditional file systems. The benefits of cloud and object storage, especially for inactive data, have prompted a significant migration or replication of files from legacy NAS systems to these modern solutions. This shift has resulted in a growing amount of data being housed in cloud and object storage; however, it has also introduced an often-overlooked security vulnerability. Typically, the data stored in cloud services or on-premises object storage remains unbacked up due to the common misconception that it is inherently secure. Such an assumption is both negligent and fraught with risk, as the high availability and redundancy provided by these services do not safeguard against issues like human error, ransomware attacks, malware infections, or technology failures. Therefore, it is crucial to implement backup or replication strategies for data kept in cloud and object storage, ideally using a different storage technology located elsewhere, and retaining the original format as it exists in the cloud. By doing so, organizations can enhance their data protection measures and mitigate potential threats to their valuable information.

An advanced analytics acceleration platform that delivers industry-leading insights and speeds up market readiness with easily deployable predictive models and comprehensive dashboards tailored to meet all gaming requirements. It offers an evaluation of existing BI frameworks, a strategic approach to business intelligence, and the modeling of BI solutions. The platform meticulously analyzes and identifies essential business variables, employs appropriate statistical modeling techniques to address business challenges, and refines models to enhance outcomes. Additionally, it reviews concerns and clarifies business goals through effective data sourcing, integration, and reporting while outlining strategies for incorporating big data technologies alongside legacy systems. The migration of on-premise CRM to the cloud and the transition of on-site data warehouses to cloud-based visual analytics are also seamlessly facilitated. In the financial services sector, entities such as investors, traders, rating agencies, and insurance companies have long recognized the significance of leveraging substantial and intricate data for informed decision-making, underscoring the platform's value in fostering strategic insights. This capability not only enhances operational efficiency but also supports competitive advantage in a rapidly evolving market landscape.

SAP BW/4HANA is an integrated data warehouse solution that utilizes SAP HANA technology. Serving as the on-premise component of SAP’s Business Technology Platform, it facilitates the consolidation of enterprise data, ensuring a unified and agreed-upon view across the organization. By providing a single source for real-time insights, it simplifies processes and fosters innovation. Leveraging the capabilities of SAP HANA, this advanced data warehouse empowers businesses to unlock the full potential of their data, whether sourced from SAP applications, third-party systems, or diverse data formats like unstructured, geospatial, or Hadoop-based sources. Organizations can transform their data management practices to enhance efficiency and agility, enabling the deployment of live insights at scale, whether hosted on-premise or in the cloud. Additionally, it supports the digitization of all business sectors, while integrating seamlessly with SAP’s digital business platform solutions. This approach allows companies to drive substantial improvements in decision-making and operational efficiency.

A Kudu cluster comprises tables that resemble those found in traditional relational (SQL) databases. These tables can range from a straightforward binary key and value structure to intricate designs featuring hundreds of strongly-typed attributes. Similar to SQL tables, each Kudu table is defined by a primary key, which consists of one or more columns; this could be a single unique user identifier or a composite key such as a (host, metric, timestamp) combination tailored for time-series data from machines. The primary key allows for quick reading, updating, or deletion of rows. The straightforward data model of Kudu facilitates the migration of legacy applications as well as the development of new ones, eliminating concerns about encoding data into binary formats or navigating through cumbersome JSON databases. Additionally, tables in Kudu are self-describing, enabling the use of standard analysis tools like SQL engines or Spark. With user-friendly APIs, Kudu ensures that developers can easily integrate and manipulate their data. This approach not only streamlines data management but also enhances overall efficiency in data processing tasks.

Proficy Historian stands out as a premier historian software solution designed to gather industrial time-series and A&E data at remarkable speeds, ensuring secure and efficient storage, distribution, and rapid access for analysis, ultimately enhancing business value. With a wealth of experience and a track record of thousands of successful implementations globally, Proficy Historian transforms how organizations operate and compete by making critical data accessible for analyzing asset and process performance. The latest version of Proficy Historian offers improved usability, configurability, and maintainability thanks to significant advancements in its architecture. Users can leverage the solution's powerful yet straightforward features to derive new insights from their equipment, process data, and business strategies. Additionally, the remote collector management feature enhances user experience, while horizontal scalability facilitates comprehensive data visibility across the enterprise, making it an essential tool for modern businesses. By adopting Proficy Historian, companies can unlock untapped potential and drive operational excellence.

The most accurate, complete, and timely data provides the best insight. Minitab Connect empowers data users across the enterprise with self service tools to transform diverse data into a network of data pipelines that feed analytics initiatives, foster collaboration and foster organizational-wide collaboration. Users can seamlessly combine and explore data from various sources, including databases, on-premise and cloud apps, unstructured data and spreadsheets. Automated workflows make data integration faster and provide powerful data preparation tools that allow for transformative insights. Data integration tools that are intuitive and flexible allow users to connect and blend data from multiple sources such as data warehouses, IoT devices and cloud storage.