Alternatives to qikkDB

BigQuery is a serverless, multicloud data warehouse that makes working with all types of data effortless, allowing you to focus on extracting valuable business insights quickly. As a central component of Google’s data cloud, it streamlines data integration, enables cost-effective and secure scaling of analytics, and offers built-in business intelligence for sharing detailed data insights. With a simple SQL interface, it also supports training and deploying machine learning models, helping to foster data-driven decision-making across your organization. Its robust performance ensures that businesses can handle increasing data volumes with minimal effort, scaling to meet the needs of growing enterprises. Gemini within BigQuery brings AI-powered tools that enhance collaboration and productivity, such as code recommendations, visual data preparation, and intelligent suggestions aimed at improving efficiency and lowering costs. The platform offers an all-in-one environment with SQL, a notebook, and a natural language-based canvas interface, catering to data professionals of all skill levels. This cohesive workspace simplifies the entire analytics journey, enabling teams to work faster and more efficiently.

Amazon Redshift is the preferred choice among customers for cloud data warehousing, outpacing all competitors in popularity. It supports analytical tasks for a diverse range of organizations, from Fortune 500 companies to emerging startups, facilitating their evolution into large-scale enterprises, as evidenced by Lyft's growth. No other data warehouse simplifies the process of extracting insights from extensive datasets as effectively as Redshift. Users can perform queries on vast amounts of structured and semi-structured data across their operational databases, data lakes, and the data warehouse using standard SQL queries. Moreover, Redshift allows for the seamless saving of query results back to S3 data lakes in open formats like Apache Parquet, enabling further analysis through various analytics services, including Amazon EMR, Amazon Athena, and Amazon SageMaker. Recognized as the fastest cloud data warehouse globally, Redshift continues to enhance its performance year after year. For workloads that demand high performance, the new RA3 instances provide up to three times the performance compared to any other cloud data warehouse available today, ensuring businesses can operate at peak efficiency. This combination of speed and user-friendly features makes Redshift a compelling choice for organizations of all sizes.

StarTree Cloud is a fully-managed real-time analytics platform designed for OLAP at massive speed and scale for user-facing applications. Powered by Apache Pinot, StarTree Cloud provides enterprise-grade reliability and advanced capabilities such as tiered storage, scalable upserts, plus additional indexes and connectors. It integrates seamlessly with transactional databases and event streaming platforms, ingesting data at millions of events per second and indexing it for lightning-fast query responses. StarTree Cloud is available on your favorite public cloud or for private SaaS deployment. StarTree Cloud includes StarTree Data Manager, which allows you to ingest data from both real-time sources such as Amazon Kinesis, Apache Kafka, Apache Pulsar, or Redpanda, as well as batch data sources such as data warehouses like Snowflake, Delta Lake or Google BigQuery, or object stores like Amazon S3, Apache Flink, Apache Hadoop, or Apache Spark. StarTree ThirdEye is an add-on anomaly detection system running on top of StarTree Cloud that observes your business-critical metrics, alerting you and allowing you to perform root-cause analysis — all in real-time.

SHARK is a versatile and high-performance open-source library for machine learning, developed in C++. It encompasses a variety of techniques, including both linear and nonlinear optimization, kernel methods, neural networks, and more. This library serves as an essential resource for both practical applications and academic research endeavors. Built on top of Boost and CMake, SHARK is designed to be cross-platform, supporting operating systems such as Windows, Solaris, MacOS X, and Linux. It operates under the flexible GNU Lesser General Public License, allowing for broad usage and distribution. With a strong balance between flexibility, user-friendliness, and computational performance, SHARK includes a wide array of algorithms from diverse fields of machine learning and computational intelligence, facilitating easy integration and extension. Moreover, it boasts unique algorithms that, to the best of our knowledge, are not available in any other competing frameworks. This makes SHARK a particularly valuable tool for developers and researchers alike.

Miele-LXIV is a 64-bit DICOM viewer and workstation created by Alex Bettarini. The macOS variant, developed in Objective-C and compiled with Xcode, is offered as a free download. In contrast, the Windows and Linux versions are entirely re-engineered in C++ using CMake and wxWidgets, currently boasting around 25% of the features available in the macOS edition. To utilize the Windows version, OpenGL (Core profile) is required, and interested users can obtain a complimentary evaluation version by reaching out to the developer. Similarly, the Linux release, developed with gcc, also demands OpenGL drivers (Core profile) and has been verified for functionality on Ubuntu 24.04 and Linux Mint 22.1. Miele-LXIV serves not only as a DICOM workstation and viewer but also encompasses additional capabilities. This project originated in November 2014 as a derivative of the well-known open-source 32-bit project OsiriX, yet it has undergone significant modifications to transform it into a 64-bit application while eliminating many of the constraints imposed by the 32-bit predecessor. As a result, it continues to evolve, aiming to enhance the user experience and functionality further.

InfiniDB is a column-oriented database management system specifically designed for online analytical processing (OLAP) workloads, featuring a distributed architecture that facilitates Massive Parallel Processing (MPP). Its integration with MySQL allows users who are accustomed to MySQL to transition smoothly to InfiniDB, as they can connect using any MySQL-compatible connector. To manage concurrency, InfiniDB employs Multi-Version Concurrency Control (MVCC) and utilizes a System Change Number (SCN) to represent the system's versioning. In the Block Resolution Manager (BRM), it effectively organizes three key structures: the version buffer, the version substitution structure, and the version buffer block manager, which all work together to handle multiple data versions. Additionally, InfiniDB implements deadlock detection mechanisms to address conflicts that arise during data transactions. Notably, it supports all MySQL syntax, including features like foreign keys, making it versatile for users. Moreover, it employs range partitioning for each column, maintaining the minimum and maximum values of each partition in a compact structure known as the extent map, ensuring efficient data retrieval and organization. This unique approach to data management enhances both performance and scalability for complex analytical queries.

MSYS2 is a comprehensive suite of tools and libraries designed to create a user-friendly environment for developing, installing, and executing native software on Windows. It includes a command line interface known as mintty, a shell environment with bash, version control systems such as git and subversion, as well as utilities like tar and awk, alongside build systems including autotools, all built upon a modified Cygwin framework. While some of its core components are derived from Cygwin, MSYS2 primarily aims to establish a robust build environment for native Windows applications, minimizing reliance on Cygwin. The platform offers modern native builds for a variety of programming tools and languages such as GCC, mingw-w64, CPython, CMake, Meson, OpenSSL, FFmpeg, Rust, and Ruby, among others. To simplify the installation and updating of software packages, MSYS2 incorporates a package management system named Pacman, which should be recognizable to users familiar with Arch Linux. This efficient package management system allows users to easily manage their software, ensuring they have access to the latest versions and features available in the ecosystem.

Introducing a robust cross-platform columnar database designed for high-performance historical time-series data, which includes: - A compute engine optimized for in-memory operations - A streaming processor that functions in real time - A powerful query and programming language known as q Kdb+ drives the kdb Insights portfolio and KDB.AI, offering advanced time-focused data analysis and generative AI functionalities to many of the world's top enterprises. Recognized for its unparalleled speed, kdb+ has been independently benchmarked* as the leading in-memory columnar analytics database, providing exceptional benefits for organizations confronting complex data challenges. This innovative solution significantly enhances decision-making capabilities, enabling businesses to adeptly respond to the ever-evolving data landscape. By leveraging kdb+, companies can gain deeper insights that lead to more informed strategies.

Sadas Engine is the fastest columnar database management system in cloud and on-premise. Sadas Engine is the solution that you are looking for. * Store * Manage * Analyze It takes a lot of data to find the right solution. * BI * DWH * Data Analytics The fastest columnar Database Management System can turn data into information. It is 100 times faster than transactional DBMSs, and can perform searches on large amounts of data for a period that lasts longer than 10 years.

Parquet was developed to provide the benefits of efficient, compressed columnar data representation to all projects within the Hadoop ecosystem. Designed with a focus on accommodating complex nested data structures, Parquet employs the record shredding and assembly technique outlined in the Dremel paper, which we consider to be a more effective strategy than merely flattening nested namespaces. This format supports highly efficient compression and encoding methods, and various projects have shown the significant performance improvements that arise from utilizing appropriate compression and encoding strategies for their datasets. Furthermore, Parquet enables the specification of compression schemes at the column level, ensuring its adaptability for future developments in encoding technologies. It is crafted to be accessible for any user, as the Hadoop ecosystem comprises a diverse range of data processing frameworks, and we aim to remain neutral in our support for these different initiatives. Ultimately, our goal is to empower users with a flexible and robust tool that enhances their data management capabilities across various applications.

Qt Creator's sophisticated code editor supports a variety of programming languages such as C++, QML, JavaScript, and Python. It boasts features like code completion, syntax highlighting, and refactoring, while providing easy access to built-in documentation. This powerful tool seamlessly integrates with popular version control systems, including Git, Subversion, Perforce, and Mercurial. With integrated visual editors, you can create C++ widget-based applications or dynamic UIs using Qt Quick, complete with pre-built controls. Whether you're importing an existing project or starting from scratch, Qt Creator takes care of generating all necessary files for you. It also includes support for CMake and facilitates cross-compiling with qmake. You can build and execute your software on various platforms, including desktop, mobile, and embedded operating systems. The build configurations are user-friendly, allowing you to easily switch between different targets. Furthermore, you can thoroughly test and debug your applications under conditions that closely mimic those of your intended devices, ensuring a smoother development process. This versatility makes Qt Creator an invaluable tool for developers seeking efficiency and ease of use in their projects.

Utilize Apache HBase™ when you require immediate and random read/write capabilities for your extensive data sets. This initiative aims to manage exceptionally large tables that can contain billions of rows across millions of columns on clusters built from standard hardware. It features automatic failover capabilities between RegionServers to ensure reliability. Additionally, it provides an intuitive Java API for client interaction, along with a Thrift gateway and a RESTful Web service that accommodates various data encoding formats, including XML, Protobuf, and binary. Furthermore, it supports the export of metrics through the Hadoop metrics system, enabling data to be sent to files or Ganglia, as well as via JMX for enhanced monitoring and management. With these features, HBase stands out as a robust solution for handling big data challenges effectively.

Ccminer is a community-driven open-source initiative designed for CUDA-compatible NVIDIA GPUs. This project supports both Linux and Windows operating systems, providing a versatile solution for miners. The purpose of this platform is to offer reliable tools for cryptocurrency mining that users can depend on. We ensure that all available open-source binaries are compiled and signed by our team for added security. While many of these projects are open-source, some may necessitate a certain level of technical expertise for proper compilation. Overall, this initiative aims to foster trust and accessibility within the cryptocurrency mining community.

Firejail is a SUID application designed to enhance security by isolating untrusted programs through the use of Linux namespaces and seccomp-bpf. This tool enables a process and its child processes to maintain a distinct view of shared kernel resources, including the network stack, process table, and mount table. Developed in C with minimal dependencies, Firejail is compatible with any Linux system that operates on version 3.x of the kernel or later. Its sandboxing solution is efficient, resulting in minimal overhead. Users benefit from its simplicity, as there are no intricate configuration files to manage, no open socket connections, and no background daemons to contend with. All security mechanisms are built directly into the Linux kernel, making them accessible on any Linux machine. This combination of features makes Firejail an appealing choice for those looking to bolster their system's defenses against potential threats.

Greenplum Database® stands out as a sophisticated, comprehensive, and open-source data warehouse solution. It excels in providing swift and robust analytics on data volumes that reach petabyte scales. Designed specifically for big data analytics, Greenplum Database is driven by a highly advanced cost-based query optimizer that ensures exceptional performance for analytical queries on extensive data sets. This project operates under the Apache 2 license, and we extend our gratitude to all current contributors while inviting new ones to join our efforts. In the Greenplum Database community, every contribution is valued, regardless of its size, and we actively encourage diverse forms of involvement. This platform serves as an open-source, massively parallel data environment tailored for analytics, machine learning, and artificial intelligence applications. Users can swiftly develop and implement models aimed at tackling complex challenges in fields such as cybersecurity, predictive maintenance, risk management, and fraud detection, among others. Dive into the experience of a fully integrated, feature-rich open-source analytics platform that empowers innovation.

WebIssues is a versatile open-source platform that facilitates issue tracking and enhances team collaboration across multiple operating systems. It enables users to efficiently store, manage, and monitor various issues, complete with detailed attributes, descriptive notes, comments, and file uploads. While its installation and usage are straightforward, the system boasts a wide array of powerful features and extensive customization options. The integrated web client is part of the server setup, which requires PHP version 5.6 or later, along with a database such as MySQL, PostgreSQL, or SQL Server. Additionally, a desktop application is available for Windows, Mac, and Linux users, necessitating WebIssues server version 2.0. For further guidance on installation and utilization, refer to the WebIssues Guide. Should any issues arise, users are encouraged to seek assistance through the Support forum. Ideas for enhancements can be proposed in the Feature requests forum, while bug reports should be submitted via the Issues tracker on GitHub. Furthermore, anyone interested can join the WebIssues Team, contributing to the ongoing development of this collaborative project. Engaging with this community not only fosters skill development but also drives innovation within the platform.

Introducing a versatile, open-source multi-cloud platform for contemporary data applications, built on Apache Cassandra™. Achieve global-scale performance with guaranteed 100% uptime while avoiding vendor lock-in. You have the flexibility to deploy on multi-cloud environments, on-premises infrastructures, or use Kubernetes. The platform is designed to be elastic and offers a pay-as-you-go pricing model to enhance total cost of ownership. Accelerate your development process with Stargate APIs, which support NoSQL, real-time interactions, reactive programming, as well as JSON, REST, and GraphQL formats. Bypass the difficulties associated with managing numerous open-source projects and APIs that lack scalability. This solution is perfect for various sectors including e-commerce, mobile applications, AI/ML, IoT, microservices, social networking, gaming, and other highly interactive applications that require dynamic scaling based on demand. Start your journey of creating modern data applications with Astra, a database-as-a-service powered by Apache Cassandra™. Leverage REST, GraphQL, and JSON alongside your preferred full-stack framework. This platform ensures that your richly interactive applications are not only elastic but also ready to gain traction from the very first day, all while offering a cost-effective Apache Cassandra DBaaS that scales seamlessly and affordably as your needs evolve. With this innovative approach, developers can focus on building rather than managing infrastructure.

CUDA® is a powerful parallel computing platform and programming framework created by NVIDIA, designed for executing general computing tasks on graphics processing units (GPUs). By utilizing CUDA, developers can significantly enhance the performance of their computing applications by leveraging the immense capabilities of GPUs. In applications that are GPU-accelerated, the sequential components of the workload are handled by the CPU, which excels in single-threaded tasks, while the more compute-heavy segments are processed simultaneously across thousands of GPU cores. When working with CUDA, programmers can use familiar languages such as C, C++, Fortran, Python, and MATLAB, incorporating parallelism through a concise set of specialized keywords. NVIDIA’s CUDA Toolkit equips developers with all the essential tools needed to create GPU-accelerated applications. This comprehensive toolkit encompasses GPU-accelerated libraries, an efficient compiler, various development tools, and the CUDA runtime, making it easier to optimize and deploy high-performance computing solutions. Additionally, the versatility of the toolkit allows for a wide range of applications, from scientific computing to graphics rendering, showcasing its adaptability in diverse fields.

Darknet is a neural network framework that is open-source, developed using C and CUDA. Known for its speed and simplicity in installation, it accommodates both CPU and GPU processing. The source code is available on GitHub, where you can also explore its capabilities further. The installation process is straightforward, requiring only two optional dependencies: OpenCV for enhanced image format support and CUDA for GPU acceleration. While Darknet performs efficiently on CPUs, it boasts a performance increase of approximately 500 times when running on a GPU! To leverage this speed, you'll need an Nvidia GPU alongside the CUDA installation. By default, Darknet utilizes stb_image.h for loading images, but for those seeking compatibility with more obscure formats like CMYK jpegs, OpenCV can be employed. Additionally, OpenCV provides the functionality to visualize images and detections in real-time without needing to save them. Darknet supports the classification of images using well-known models such as ResNet and ResNeXt, and it has become quite popular for employing recurrent neural networks in applications related to time-series data and natural language processing. Whether you're a seasoned developer or a newcomer, Darknet offers an accessible way to implement advanced neural network solutions.

Microsoft is actively advancing its R-related offerings, evident not only in the latest release of Machine Learning Server but also in the newest versions of Microsoft R Client and Microsoft R Open. Furthermore, R and Python integration is available within SQL Server Machine Learning Services for both Windows and Linux platforms, alongside R support in Azure SQL Database. The R components maintain backward compatibility, allowing users to execute existing R scripts on newer versions, as long as they do not rely on outdated packages or platforms that are no longer supported, or on known problems that necessitate workarounds or code modifications. Microsoft R Open serves as the enhanced version of R provided by Microsoft Corporation, with the most recent release, Microsoft R Open 4.0.2, built on the statistical language R-4.0.2, offering additional features for better performance, reproducibility, and platform compatibility. This version ensures compatibility with all packages, scripts, and applications built on R-4.0.2, making it a reliable choice for developers and data scientists alike. Overall, Microsoft's dedication to R fosters an environment of continuous improvement and support for its users.

DeepPy is a deep learning framework that operates under the MIT license, designed to infuse a sense of tranquility into the deep learning process. It primarily utilizes CUDArray for its computational tasks, so installing CUDArray is a prerequisite. Additionally, it's worth mentioning that you have the option to install CUDArray without the CUDA back-end, which makes the installation procedure more straightforward. This flexibility can be particularly beneficial for users who prefer a simpler setup.

We offer comprehensive support for various platforms including GitHub, GitHub Enterprise, Bitbucket, GitLab, Azure Repos, Kiln, Gitea, and custom repositories. You can set up builds using either versioned YAML configurations or through an intuitive user interface. Each build operates within a clean, isolated environment to ensure reliability and quality. With integrated deployment features and a built-in NuGet server, our service streamlines your workflow. Enjoy branch and pull request builds designed to enhance your development process, alongside access to professional support and a dynamic community. Our tools cater specifically to Windows developers, and we proudly provide our services free of charge for open-source projects, while subscriptions are available for private projects and AppVeyor Enterprise installations on-site. Experience expedited build, test, and deployment processes across any platform. You can get started within minutes as our service is compatible with any source control system and offers fast build virtual machines with administrative access. Our platform supports multi-stage deployments and is compatible with Windows, Linux, and macOS. Installation is quick and simple on any of these operating systems, and you can effortlessly run unlimited pipelines locally, within Docker, or on any cloud provider. Additionally, we offer free access for an unlimited number of users, projects, jobs, clouds, and agents, making it an ideal choice for teams of all sizes.

With the Toradex Easy Installer, TorizonCore can be set up effortlessly in just one click. You will find that the Graphical User Interface (GUI) and Debian containers equipped with the APT Package Manager allow for a quick and easy start. Moreover, a growing array of development tools, including the Flash Analytics tool, facilitates the rapid development of dependable products. Built with the Yocto Project and based on the Toradex Embedded Linux BSP, TorizonCore is open-source, allowing for extensive customization options. Additionally, Torizon seamlessly integrates with Visual Studio 2019, empowering developers to utilize a Windows development PC while benefiting from the robust Linux ecosystem. Although Toradex continues to offer support for Windows Embedded Compact / WinCE, transitioning to Torizon with Visual Studio presents a compelling opportunity for developers eager to embrace the advantages of Linux. This combination not only enhances productivity but also encourages innovation in software development.

When seeking a database that ensures both scalability and high availability without sacrificing performance, Apache Cassandra stands out as an ideal option. Its linear scalability paired with proven fault tolerance on standard hardware or cloud services positions it as an excellent choice for handling mission-critical data effectively. Additionally, Cassandra's superior capability to replicate data across several datacenters not only enhances user experience by reducing latency but also offers reassurance in the event of regional failures. This combination of features makes it a robust solution for organizations that prioritize data resilience and efficiency.

Apache Druid is a distributed data storage solution that is open source. Its fundamental architecture merges concepts from data warehouses, time series databases, and search technologies to deliver a high-performance analytics database capable of handling a diverse array of applications. By integrating the essential features from these three types of systems, Druid optimizes its ingestion process, storage method, querying capabilities, and overall structure. Each column is stored and compressed separately, allowing the system to access only the relevant columns for a specific query, which enhances speed for scans, rankings, and groupings. Additionally, Druid constructs inverted indexes for string data to facilitate rapid searching and filtering. It also includes pre-built connectors for various platforms such as Apache Kafka, HDFS, and AWS S3, as well as stream processors and others. The system adeptly partitions data over time, making queries based on time significantly quicker than those in conventional databases. Users can easily scale resources by simply adding or removing servers, and Druid will manage the rebalancing automatically. Furthermore, its fault-tolerant design ensures resilience by effectively navigating around any server malfunctions that may occur. This combination of features makes Druid a robust choice for organizations seeking efficient and reliable real-time data analytics solutions.

Autorun Organizer offers seamless updates to the latest versions of the software, identifies faulty entries, allows users to navigate various Windows startup categories, presents a graphical representation of Windows boot times, enables users to toggle autorun items on and off, and efficiently manages disabled entries as well. This comprehensive tool streamlines the process of optimizing startup performance while ensuring that all elements are effectively monitored.

The toolkit is available as a collection of resources distributed through the Maven Central repository. It necessitates Java version 7 or higher to run tests, which must be executed using either JUnit or TestNG. For guidance on incorporating the library into a Java project, refer to the section on Running tests with JMockit. This tutorial explores the various APIs offered by the library, illustrated through example tests that utilize Java 8. The primary API consists of a singular annotation that facilitates the automatic creation and setup of the objects intended for testing. Additionally, there exists the mocking API, commonly referred to as the "Expectations" API, which is designed for tests that engage with mocked dependencies. Furthermore, a compact faking API, known as the "Mockups" API, is provided for generating and utilizing fake implementations, thereby mitigating the full resource demands of external components. Overall, this toolkit enhances testing efficiency by streamlining the setup process and providing versatile mocking capabilities.

Distcc is a system designed for distributed compilation that speeds up the build process for C, C++, Objective-C, and Fortran by distributing compile tasks across various networked machines. This tool works effectively with both GCC and Clang toolchains, seamlessly intercepting compiler commands and redistributing them to remote daemons while maintaining optimization settings, include directories, and tracking of dependencies. The architecture is client-server based, featuring a lightweight listener that oversees job queues, prioritizes local compilation as necessary, and easily identifies available hosts through straightforward configuration or DNS. Additionally, Distcc accommodates cross-compilation setups, offers SSH tunneling for secure clusters, allows for the blacklisting of unreliable servers, and integrates well with modern build systems such as Make, CMake, and Ninja. It also includes monitoring tools that supply real-time data on job distribution and performance, and its compatibility with compilation databases (compdb) permits detailed management of distributed workloads. Overall, Distcc is a powerful solution that significantly enhances build efficiency across diverse development environments.

POS Pizza serves as an affordable point of sale (POS) solution specifically tailored for pizza and sandwich establishments. The user-friendly software is straightforward to learn and can be easily taught to staff members. This POS system accommodates delivery, takeout, and dine-in services for various restaurant types. It includes comprehensive features such as support for half and half toppings, caller ID functionality, touch screen compatibility, online ordering capabilities, and driver dispatch tools, making it ideal for pizza delivery operations, among other services. Additionally, a fully functional version of POS Pizza is offered at no cost, allowing users to download and start using it without any registration requirements. This package is categorized as "Software Only" and is compatible with Windows XP and later versions, with optimal performance on Windows 7, 8, and 10. If you require hardware that seamlessly integrates with POS Pizza, it is advisable to explore compatible options. The ease of use and accessibility of POS Pizza make it a practical choice for restaurant owners looking to streamline their operations.

SparkyLinux is a distinctive GNU/Linux distribution built on the foundation of Debian GNU/Linux. Known for its speed and lightweight nature, Sparky provides a fully customizable operating system that caters to a variety of users and tasks. It offers several versions, including a fully featured OS equipped with a lightweight desktop environment, which is ready to use right out of the box and comes with a selection of commonly used software for home users. Additionally, there is a MinimalGUI version that utilizes the Openbox window manager, featuring only basic software for users who wish to personalize their OS and desktop according to their preferences, along with the flexibility to install any desktop environment or window manager they desire. For advanced users, the MinimalCLI version omits the X server entirely, allowing for a more hands-on approach to building and configuring their desktop environments. With support for approximately 20 different desktop environments and window managers, SparkyLinux ensures users have the freedom to choose how they want their computing experience to be, whether for productivity, leisure, socializing, or a multitude of other activities. This versatility makes SparkyLinux not just an operating system, but a platform for creativity and personal expression in computing.

Zend Server is a PHP server that has been trusted by global innovators including Fortune 100 companies. It offers easy-to-use tools as well as comprehensive services. * Improve Debugging * Streamline Deployments * Speed Performance * Boost Security * Unleash Scale * Simplify Integrations Zend Server comes with a certified PHP stack. Depending on which Zend Server edition you choose you can take advantage: * ZendPHP versions 5.6 or newer * PHP support includes 5-year code support and 24x7x365 options. * Zend Server support, including 24x7x365 options. * Automatic PHP updates and patches included with Zend Server Updates Zend Server can be run on Windows and Linux, as well as on IBM i. You can also use ready-to-go Zend Server Cloud instances.

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.

CelerData is an advanced SQL engine designed to enable high-performance analytics directly on data lakehouses, removing the necessity for conventional data warehouse ingestion processes. It achieves impressive query speeds in mere seconds, facilitates on-the-fly JOIN operations without incurring expensive denormalization, and streamlines system architecture by enabling users to execute intensive workloads on open format tables. Based on the open-source StarRocks engine, this platform surpasses older query engines like Trino, ClickHouse, and Apache Druid in terms of latency, concurrency, and cost efficiency. With its cloud-managed service operating within your own VPC, users maintain control over their infrastructure and data ownership while CelerData manages the upkeep and optimization tasks. This platform is poised to support real-time OLAP, business intelligence, and customer-facing analytics applications, and it has garnered the trust of major enterprise clients, such as Pinterest, Coinbase, and Fanatics, who have realized significant improvements in latency and cost savings. Beyond enhancing performance, CelerData’s capabilities allow businesses to harness their data more effectively, ensuring they remain competitive in a data-driven landscape.

Mageia is an operating system based on GNU/Linux and adheres to the principles of Free Software. This initiative is driven by a community project that relies on a nonprofit organization comprised of elected contributors. In addition to providing a secure, stable, and sustainable computing environment, Mageia aims to foster and uphold a reputable and recognized community in the realm of free software. As part of the GNU/Linux family, Mageia can be installed either as the primary operating system on a computer or as an alternative alongside one or more existing systems through dual booting. This community-driven project is backed by the nonprofit organization Mageia.Org, which consists of a team of elected contributors dedicated to its development. Mageia caters to a diverse range of users, from newcomers exploring GNU/Linux for the first time to seasoned developers and system administrators. The software packages available in Mageia are organized into three distinct repositories or media, each determined by the licensing conditions applicable to the respective packages. Overall, Mageia embodies the principles of collaboration, accessibility, and user empowerment within the software community.

BitLocker Drive Encryption serves as a crucial data security feature, seamlessly integrated into the operating system, designed to combat risks associated with data theft or exposure due to lost, stolen, or improperly retired computers. The most robust protection is achieved when BitLocker is paired with a Trusted Platform Module (TPM) version 1.2 or higher, a hardware element that many modern computers come equipped with. This TPM collaborates with BitLocker to safeguard user data and verify that the computer remains untampered while offline. For machines lacking a TPM version 1.2 or more advanced, BitLocker can still encrypt the Windows operating system drive, but this setup necessitates the user to utilize a USB startup key to power on the computer or wake it from hibernation. Since the introduction of Windows 8, users can also opt for an operating system volume password to secure the operating system volume on computers without a TPM. This additional flexibility enhances usability while maintaining security standards.

Introducing Scuba, a complimentary vulnerability scanner designed to reveal concealed security threats within enterprise databases. This tool allows users to conduct scans to identify vulnerabilities and misconfigurations, providing insight into potential risks to their databases. Furthermore, it offers actionable recommendations to address any issues detected. Scuba is compatible with various operating systems, including Windows, Mac, and both x32 and x64 versions of Linux, and boasts an extensive library of over 2,300 assessment tests tailored for prominent database systems such as Oracle, Microsoft SQL Server, SAP Sybase, IBM DB2, and MySQL. With Scuba, users can efficiently identify and evaluate security vulnerabilities and configuration deficiencies, including patch levels. Running a Scuba scan is straightforward and can be initiated from any compatible client, with an average scan duration of just 2-3 minutes, depending on the complexity of the database, the number of users and groups, as well as the network connection. Best of all, no prior installation or additional dependencies are necessary to get started.

Deequ is an innovative library that extends Apache Spark to create "unit tests for data," aiming to assess the quality of extensive datasets. We welcome any feedback and contributions from users. The library requires Java 8 for operation. It is important to note that Deequ version 2.x is compatible exclusively with Spark 3.1, and the two are interdependent. For those using earlier versions of Spark, the Deequ 1.x version should be utilized, which is maintained in the legacy-spark-3.0 branch. Additionally, we offer legacy releases that work with Apache Spark versions ranging from 2.2.x to 3.0.x. The Spark releases 2.2.x and 2.3.x are built on Scala 2.11, while the 2.4.x, 3.0.x, and 3.1.x releases require Scala 2.12. The primary goal of Deequ is to perform "unit-testing" on data to identify potential issues early on, ensuring that errors are caught before the data reaches consuming systems or machine learning models. In the sections that follow, we will provide a simple example to demonstrate the fundamental functionalities of our library, highlighting its ease of use and effectiveness in maintaining data integrity.

Mirantis Container Runtime (MCR), which was previously known as Docker Engine Enterprise, serves as a secure and robust container runtime designed for enterprise use, allowing development teams to create and manage containers on both Linux and Windows platforms while utilizing the familiar Docker CLI, Dockerfiles, and APIs essential for mission-critical applications. This solution is fully aligned with Docker-centric workflows and toolchains, ensuring a smooth transition from development to production with rigorously tested and validated releases across various operating systems, accompanied by comprehensive CVE patching and bug fixes that maintain workload reliability. Furthermore, MCR emphasizes top-tier security through FIPS 140-2 certified cryptographic modules, implements mandatory access controls such as AppArmor and SELinux, and incorporates image signature verification, alongside support for sandboxed runtimes like Kata and gVisor, all aimed at maintaining trusted and compliant containers. The combination of these features positions MCR as a leading choice for organizations seeking to enhance their container management capabilities while adhering to strict security standards.

SentiSight SDK is an intricate application tailored for developers focused on building applications that utilize computer vision for object recognition tasks. This toolkit facilitates both manual and fully automated learning of objects, enabling users to search for recognized objects in images captured by various devices such as cameras, webcams, still images, or live video streams, all in a straightforward yet adaptable manner. SentiSight is offered as a software development kit specifically for creating object recognition systems that are compatible with Microsoft Windows environments. To utilize the SDK, users must meet certain system prerequisites: they need either an x86 (32-bit) or x86-64 (64-bit) processor, SSE2 support (with SSSE3 support being advisable), a minimum of 256 MB of available RAM, a webcam, the Microsoft .NET framework version 2.0 or later (for .NET component integration), Microsoft DirectX 9.0 or a later version (for webcam functionality), and Microsoft Visual Studio 2005 SP1 or a more recent version (to develop applications using C/C++, C#, or Visual Basic .NET). Additionally, it's important for users to note the limitations of the unregistered version, which is available for a trial period of 30 days. By adhering to these requirements, developers can effectively leverage the capabilities of SentiSight to enhance their applications with robust object recognition features.

TestEngine serves as a highly efficient platform designed for the automated execution of SoapUI and ReadyAPI tests on a large scale. It offers versatile deployment options, enabling installation across various environments, including cloud solutions or on-premises setups, utilizing Docker, virtual machines, or operating systems like Mac, Linux, and Windows, thus accommodating both centralized and distributed execution models. By leveraging TestEngine, teams can significantly speed up their delivery pipelines through concurrent test execution. This tool is capable of running extensive test suites in conjunction with shorter, spontaneous test cases, all while requiring minimal infrastructure upkeep. TestEngine effectively manages the queuing of test requests as they come in, even during peak submission times. As demand varies, it returns results to users on distributed clients and retains data for future access. The importance of robust testing cannot be overstated, as it is crucial for delivering and maintaining high-quality applications and services. With TestEngine, teams can enhance their testing processes and streamline execution without the challenges typically associated with complex environments, leading to increased productivity and efficiency in software development.

BlackArch Linux is a specialized distribution based on Arch Linux, designed specifically for penetration testers and security researchers. Users have the flexibility to install tools either individually or in groups, making it adaptable to various needs. This distribution seamlessly integrates with existing Arch installations, enhancing its usability. The BlackArch Full ISO provides a comprehensive system that includes numerous window managers and all available tools at the time of its build. In contrast, the BlackArch Slim ISO offers a lightweight experience with the XFCE Desktop Environment, featuring a curated selection of commonly used tools and system utilities ideal for penetration testing. Additionally, the netinstall ISO serves as a minimal image for bootstrapping new machines with essential packages. BlackArch functions as an unofficial user repository, further enriching the Arch ecosystem. It is also possible to install BlackArch Linux using the Slim medium, which boasts a user-friendly graphical installer, ensuring ease of access for users. This versatility makes BlackArch an appealing choice for those engaged in security assessments and research.

Engage in trading on the Stellar Decentralized Exchange using StellarTerm, which serves as an open-source client providing access to the Stellar network. With StellarTerm, users can effortlessly send, receive, and trade various assets within the Stellar ecosystem. It's important to note that StellarTerm operates solely as a client and does not manage the operations of the Stellar network itself. Developed by Ultra Stellar, LLC—also the creators of the LOBSTR wallet—StellarTerm maintains its independence from the Stellar Development Foundation. The software is made available under the Apache-2.0 license and is provided without any warranty or guarantees. Additionally, StellarTerm does not act as a custodian for your assets, meaning that it does not retain any tokens, cryptocurrencies, or private keys on your behalf. As with any cryptocurrency investment, users should be aware of the inherent market risks and volatility, as previous performance does not guarantee future outcomes. Always conduct thorough research before engaging with trading platforms and understand the potential risks involved.

MariaDB Platform is an enterprise-level open-source database solution. It supports transactional, analytical, and hybrid workloads, as well as relational and JSON data models. It can scale from standalone databases to data warehouses to fully distributed SQL, which can execute millions of transactions per second and perform interactive, ad-hoc analytics on billions upon billions of rows. MariaDB can be deployed on prem-on commodity hardware. It is also available on all major public cloud providers and MariaDB SkySQL, a fully managed cloud database. MariaDB.com provides more information.

Pyglet is a versatile and user-friendly library designed for Python, enabling the creation of games and visually engaging applications across various operating systems, including Windows, Mac OS X, and Linux. It offers a comprehensive range of features such as window management, event handling for user interfaces, support for joysticks, OpenGL graphics, image and video loading, as well as sound and music playback. The library boasts a user-friendly Pythonic API that is straightforward to grasp, ensuring a smooth development experience. Licensed under the BSD open-source license, pyglet allows for both commercial use and contributions to other open-source projects with minimal restrictions. It requires no external dependencies or complex installation processes, as it operates solely on Python, which streamlines both distribution and installation. This simplicity makes it convenient to bundle your project using tools like PyInstaller. Additionally, pyglet facilitates the use of genuine platform-native windows, giving developers the ability to leverage multiple windows and accommodate multi-monitor setups efficiently. With such capabilities, pyglet stands out as an excellent choice for developers looking to create rich multimedia applications in Python.

Arch Linux is a self-sufficient, x86-64 general-purpose GNU/Linux distribution that aims to deliver the most current stable software versions through a rolling-release approach. Its standard installation offers a bare-minimum base system, allowing users to customize their setup by installing only the necessary components. The philosophy of Arch Linux emphasizes simplicity, defined as the absence of unnecessary enhancements or alterations. The distribution provides software as originally released by upstream developers, minimizing downstream modifications, and avoiding patches that are not accepted upstream; any changes made are predominantly backported bug fixes that will be addressed in the next release. Furthermore, Arch includes the configuration files from upstream, with changes limited to specific distribution needs, such as modifying file paths within the system. Notably, Arch does not incorporate automation features like automatically enabling services upon package installation, thereby maintaining user control over their environment. This approach allows users to tailor their systems closely to their needs, fostering a deeper understanding and appreciation of their operating system.