Best Data Management Software for Small Business - Page 98

FalconStor stands out as a reliable innovator in data protection, managing more than an Exabyte of data and empowering some of the globe's most challenging enterprises to upgrade their data backup and archival processes across both data centers and public cloud environments. The firm enhances data security and facilitates rapid recovery from ransomware incidents, all while reducing costs by as much as 90 percent. With a strong reputation, FalconStor serves a diverse clientele of 1,000 customers and collaborates with a wide-reaching network of partners worldwide. This commitment to excellence and innovation makes FalconStor a key player in the data management sector.

Hitachi Universal Replicator meets the rigorous demands of business continuity and disaster recovery by providing asynchronous data replication between Hitachi storage systems, regardless of distance. This cutting-edge software helps maintain uninterrupted access to your data and operations through its high-performance synchronous and asynchronous replication capabilities. Delve into this datasheet to discover how Hitachi TrueCopy remote replication software guarantees both business continuity and disaster recovery through synchronous replication, while also enhancing productivity for business and IT workflows alike. When faced with the necessity for everyday uptime and swift recovery in case of outages, Hitachi TrueCopy remote replication software stands out as an ideal solution. It effectively mirrors data synchronously between Hitachi storage systems across metropolitan distances. Furthermore, Hitachi TrueCopy remote replication software can seamlessly integrate with Hitachi ShadowImage replication software, fostering comprehensive business continuity strategies that are essential for modern enterprises. This integration further enhances the resilience and reliability of your data management systems.

Oracle GoldenGate is a robust software suite designed for the real-time integration and replication of data across diverse IT environments. This solution facilitates high availability, real-time data integration, change data capture for transactions, data replication, and the ability to transform and verify data between operational and analytical systems within enterprises. The 19c version of Oracle GoldenGate offers remarkable performance enhancements along with an easier configuration and management experience, deeper integration with Oracle Database, cloud environment support, broader compatibility, and improved security features. Apart from the core platform for real-time data transfer, Oracle also offers the Management Pack for Oracle GoldenGate, which provides a visual interface for managing and monitoring deployments, along with Oracle GoldenGate Veridata, a tool that enables swift and high-volume comparisons between databases that are actively in use. This comprehensive ecosystem positions Oracle GoldenGate as a vital asset for organizations seeking to optimize their data management strategies.

Syniti Data Replication, previously known as DBMoto, simplifies the process of heterogeneous Data Replication, Change Data Capture, and Data Transformation, eliminating the dependence on consulting services. With an intuitive graphical user interface and wizard-guided steps, users can effortlessly deploy and operate robust data replication features, avoiding the complications of developing stored procedures, learning proprietary syntax, or programming for either the source or target database systems. This solution accelerates the ingestion of data from various database systems, enabling seamless transfer to preferred cloud platforms such as Google Cloud, AWS, Microsoft Azure, and SAP Cloud, all without disrupting existing on-premises operations. The software is designed to be source- and target-agnostic, allowing it to replicate all chosen data as a snapshot, thereby facilitating a smoother data migration process. It is offered as a standalone solution, accessible via a cloud-based option from the Amazon Web Services (AWS) Marketplace, or as part of a subscription to the Syniti Knowledge Platform, making it capable of addressing your most critical integration needs. Furthermore, this versatility ensures that organizations can effectively manage data across diverse environments and optimize their data workflows.

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.

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.

Aircloak Insights acts as a secure intermediary between data analysts and the sensitive information they require for their work. Analysts can interact with the system using standard SQL queries or visual dashboards such as Tableau. The system intercepts these queries and customizes them for the underlying data sources, whether they are SQL databases or NoSQL big data repositories. The results are then delivered through the proxy, which guarantees that the data is both aggregated and completely anonymized. Moreover, Aircloak Insights seamlessly fits into your established workflow, enabling you to access sensitive datasets through its user-friendly web interface, Insights Air, or by utilizing business intelligence tools, including Tableau and any other platforms that support the Postgres Message Protocol. Additionally, for those who prefer automation, Aircloak Insights offers the capability to execute queries programmatically via a RESTful API, providing further flexibility in data handling. This comprehensive approach ensures that analysts can work efficiently while maintaining data privacy and security.

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.

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.

Effortlessly gather, manage, and scrutinize video and data streams as they occur. Amazon Kinesis simplifies the process of collecting, processing, and analyzing streaming data in real-time, empowering you to gain insights promptly and respond swiftly to emerging information. It provides essential features that allow for cost-effective processing of streaming data at any scale while offering the adaptability to select the tools that best align with your application's needs. With Amazon Kinesis, you can capture real-time data like video, audio, application logs, website clickstreams, and IoT telemetry, facilitating machine learning, analytics, and various other applications. This service allows you to handle and analyze incoming data instantaneously, eliminating the need to wait for all data to be collected before starting the processing. Moreover, Amazon Kinesis allows for the ingestion, buffering, and real-time processing of streaming data, enabling you to extract insights in a matter of seconds or minutes, significantly reducing the time it takes compared to traditional methods. Overall, this capability revolutionizes how businesses can respond to data-driven opportunities as they arise.

Embiot®, a compact, high-performance IoT analytics software agent that can be used for smart sensor and IoT gateway applications, is available. This edge computing application can be integrated directly into devices, smart sensor and gateways but is powerful enough to calculate complex analytics using large amounts of raw data at high speeds. Embiot internally uses a stream processing model in order to process sensor data that arrives at different times and in different order. It is easy to use with its intuitive configuration language, rich in math, stats, and AI functions. This makes it quick and easy to solve any analytics problems. Embiot supports many input methods, including MODBUS and MQTT, REST/XML and REST/JSON. Name/Value, CSV, and REST/XML are all supported. Embiot can send output reports to multiple destinations simultaneously in REST, custom text and MQTT formats. Embiot supports TLS on select input streams, HTTP, and MQTT authentication for security.

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.

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.

Our distinctive software solutions facilitate SMS routing and delivery, comprehensive Data Management and Analytics, as well as Email Scoring. This capability allows our clients to effectively target customers who are most likely to engage and convert, ultimately enhancing their marketing outcomes. Additionally, the integration of these features streamlines communication strategies and maximizes the potential for successful interactions.

Tye is a Software-as-a-Service (SaaS) solution that serves as a personal assistant, enabling businesses to maintain accurate and current contact details for their clients. This innovative tool streamlines the process of managing customer information, enhancing communication and engagement.

A comprehensive platform designed to streamline and enhance provider data across the entire organization. Phynd 360 serves as an advanced provider data solution, functioning as the central hub for health systems' provider information. It effectively optimizes data related to providers—covering individuals, facilities, and services—for application within EHR, marketing, and claims systems through its suite of tools that facilitate provider enrollment, management, outreach, and search throughout the enterprise. The platform allows for the administration of data pertaining to employed, referring, and affiliated healthcare providers. Additionally, it supports the maintenance of detailed profiles for care locations intended for consumers, providers, and care coordinators alike. By aligning providers with the appropriate specialty, subspecialty, and terms that resonate with both clinical and consumer needs, it enhances the overall usability of provider data. Furthermore, it enables monitoring of provider and location engagement within various commercial and health system plans, as well as accountable care organizations (ACOs) and narrow networks, ensuring a holistic approach to provider management. Ultimately, this platform not only centralizes vital information but also improves the efficiency of care delivery.

Kaggle provides a user-friendly, customizable environment for Jupyter Notebooks without any setup requirements. You can take advantage of free GPU resources along with an extensive collection of data and code shared by the community. Within the Kaggle platform, you will discover everything necessary to perform your data science tasks effectively. With access to more than 19,000 publicly available datasets and 200,000 notebooks created by users, you can efficiently tackle any analytical challenge you encounter. This wealth of resources empowers users to enhance their learning and productivity in the field of data science.

Trifacta's Cloud Dataprep is an advanced data service designed for the visual exploration, cleansing, and preparation of both structured and unstructured datasets, facilitating analysis, reporting, and machine learning tasks. Its serverless architecture allows it to operate at any scale, eliminating the need for users to manage or deploy infrastructure. With each interaction in the user interface, the system intelligently suggests and forecasts your next ideal data transformation, removing the necessity for manual coding. As a partner service of Trifacta, Cloud Dataprep utilizes their renowned data preparation technology to enhance functionality. Google collaborates closely with Trifacta to ensure a fluid user experience, which bypasses the requirement for initial software installations, separate licensing fees, or continuous operational burdens. Fully managed and capable of scaling on demand, Cloud Dataprep effectively adapts to your evolving data preparation requirements, allowing you to concentrate on your analytical pursuits. This innovative service ultimately empowers users to streamline their workflows and maximize productivity.

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.

Kogni's Discover feature allows enterprises to find and detect sensitive and critical information. Find sensitive data from any source, in whatever format, and of any type. Kogni's sensitive data discovery software automates data discovery and classification. Kogni's easy-to-implement software allows seamless integration with your company's data warehouse. Kogni's sensitive information discovery tool can help you accelerate compliance with industry standards and international data regulations. Reduce the risk of data leakage and the costs of non-compliance to data protection and privacy regulations such as HIPAA, GDPR and CCPA, PCI and PII. Scans and pin-points sensitive information from more than 10 data sources. This tool creates a comprehensive dashboard of sensitive information with a variety of special features. Your sensitive data classification groups can be customized to meet your company's requirements. Supports a wide variety of data types and formats.

Gain immediate insights into shopper behavior and assess customer satisfaction effectively. Understand the characteristics of your converted customers. Our Face Analysis Technology equips physical retail businesses with real-time, anonymous insights into shopper interactions, allowing for enhanced optimization of customer experiences and daily operations. Explore our curated product suggestions. Develop more intelligent in-store environments that enhance engagement and elevate customer satisfaction. It is essential to foster customer engagement, as an engaged shopper is likely to return. Our software offers you real-time data regarding shoppers' demographics, interests, and behaviors. Identify your converted customers and refine every aspect, from product placements to store layouts, informed by shopper behavior. Are you effectively reaching your intended audience? Our software provides the solutions to uncover these crucial insights. Furthermore, understanding these dynamics can significantly improve overall business performance.

Google Cloud Bigtable provides a fully managed, scalable NoSQL data service that can handle large operational and analytical workloads. Cloud Bigtable is fast and performant. It's the storage engine that grows with your data, from your first gigabyte up to a petabyte-scale for low latency applications and high-throughput data analysis. Seamless scaling and replicating: You can start with one cluster node and scale up to hundreds of nodes to support peak demand. Replication adds high availability and workload isolation to live-serving apps. Integrated and simple: Fully managed service that easily integrates with big data tools such as Dataflow, Hadoop, and Dataproc. Development teams will find it easy to get started with the support for the open-source HBase API standard.

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.

A cloud database that can scale to handle large streaming data sets. Kinetica harnesses modern vectorized processors to perform orders of magnitude faster for real-time spatial or temporal workloads. In real-time, track and gain intelligence from billions upon billions of moving objects. Vectorization unlocks new levels in performance for analytics on spatial or time series data at large scale. You can query and ingest simultaneously to take action on real-time events. Kinetica's lockless architecture allows for distributed ingestion, which means data is always available to be accessed as soon as it arrives. Vectorized processing allows you to do more with fewer resources. More power means simpler data structures which can be stored more efficiently, which in turn allows you to spend less time engineering your data. Vectorized processing allows for incredibly fast analytics and detailed visualizations of moving objects at large scale.

The engineering team at Altinity possesses extensive expertise, enabling them to implement a wide range of functionalities from essential ClickHouse features to the behavior of Kubernetes operators and enhancements for client libraries. They offer a versatile, docker-based GUI manager for ClickHouse that enables users to install clusters, manage nodes through addition, deletion, or replacement, monitor the status of clusters, and assist with troubleshooting and diagnostics. Additionally, they support various third-party tools and software integrations, including ingestion tools like Kafka and ClickTail, APIs for Python, Golang, ODBC, and Java, as well as compatibility with Kubernetes. UI tools such as Grafana, Superset, Tabix, and Graphite are also part of their ecosystem, along with database integrations for MySQL and PostgreSQL, and business intelligence tools like Tableau and many others. Altinity.Cloud draws upon its extensive experience gained from assisting numerous clients in managing ClickHouse-based analytics, ensuring it meets diverse needs. Built on a Kubernetes-based architecture, Altinity.Cloud offers both portability and flexibility regarding deployment options, allowing users to operate without fear of vendor lock-in. Recognizing that effective cost management is vital for SaaS companies, Altinity prioritizes this aspect in its offerings to support sustainable growth.