Alternatives to Apache Axiom

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.

Sonic XML Server™ offers a comprehensive suite of rapid processing, storage, and querying capabilities specifically designed for XML documents essential in managing the operational data of Sonic ESB. By handling XML messages in their native format, the XML Server ensures high-speed performance without imposing limitations on the XML message structure. The introduction of Extensible Markup Language (XML) marked a significant advancement as it is a versatile data format that operates independently of both hardware and software. XML's ability to convey information without being tied to specific system or application formatting rules makes it a vital technology for enabling the seamless exchange of diverse data types. Despite its advantages, this flexibility often demands substantial time and resources for processing XML structures. The Sonic XML Server addresses this challenge by delivering efficient processing and storage solutions for operational data, crucial for the effective implementation of a service-oriented architecture. Moreover, Sonic XML Server not only improves but also expands the XML message processing capabilities of Sonic ESB through its integrated native query, storage, and processing services, thereby enhancing overall system performance. Thus, users can experience a significant boost in efficiency and effectiveness when working with XML data.

Apache Xerces is a collaborative initiative focused on delivering robust, feature-rich, high-quality, and freely accessible XML parsers along with associated technologies across a diverse range of platforms and programming languages. This endeavor is driven by the collective efforts of individuals and organizations worldwide, who utilize the Internet for communication, planning, and the development of XML software and its documentation. The primary goal of Apache Xerces is to foster the adoption of XML, which we recognize as an effective framework for organizing data as information, thus enhancing the processes of exchange, transformation, and presentation of knowledge. By enabling the conversion of unrefined data into actionable information, we believe there is significant potential to enhance the efficiency and capabilities of information systems. Our mission is to develop and provide XML parsers and related technologies at no cost, ultimately aiming to drive these advancements and improvements in the field of information technology. Such efforts reflect a commitment not only to technological progress but also to the empowerment of users and developers in navigating the complexities of data management.

Anakia may be simpler to grasp than XSL while still offering comparable functionality. There's no need to wrestle with complicated <xsl:> tags; instead, you can focus on utilizing the provided Context objects, JDOM, and the straightforward directives from Velocity. Additionally, Anakia appears to deliver significantly faster performance than Xalan's XSL processor when generating web pages. For instance, it can produce 23 pages in just 7-8 seconds on a PIII 500mhz system running Win98 and JDK 1.3 with client Hotspot, whereas a similar setup using Ant's <style> task takes about 14-15 seconds, resulting in nearly double the speed. Anakia, designed to succeed Stylebook—which was originally used for creating consistent, static web pages—is particularly well-suited for documentation and project websites, exemplified by those hosted on www.apache.org and jakarta.apache.org. Although it is tailored for specific tasks, it sacrifices some of the additional capabilities found in XSL, making it an efficient choice for targeted web development needs. Ultimately, Anakia serves as an effective tool for those looking for simplicity without compromising essential features.

Apache XML Security for Java is a comprehensive library that encompasses the widely recognized JSR-105 (Java XML Digital Signature) API, featuring a robust DOM-based implementation for both XML Signature and XML Encryption, alongside a newer StAX-based (streaming) implementation for these same functions. This library provides the capability to designate a security provider when utilizing org.apache.xml.security.signature.XMLSignature. Furthermore, it now includes enhanced support for customizing the parsing of an InputStream into a DOM Document, ensuring more flexibility and control for developers. Overall, this library is valuable for anyone needing secure XML processing in their Java applications.

InterSystems IRIS, a cloud-first data platform, is a multi-model transactional database management engine, application development platform, interoperability engine and open analytics platform. InterSystems IRIS offers a variety of APIs that allow you to work with transactional persistent data simultaneously. These include key-value, relational and object, document, and multidimensional. Data can be managed by SQL, Java, node.js, .NET, C++, Python, and native server-side ObjectScript language. InterSystems IRIS features an Interoperability engine as well as modules for building AI solutions. InterSystems IRIS features horizontal scalability (sharding and ECP), and High Availability features such as Business intelligence, transaction support and backup.

OrigoDB allows you to create high-quality, mission-critical systems that deliver real-time performance while significantly reducing time and costs. This is not just empty advertising! We encourage you to continue reading for a straightforward overview of our features. Feel free to reach out with any inquiries or download and give it a try today! Operations performed in memory are significantly quicker than those conducted on disk. An individual OrigoDB engine is capable of processing millions of read transactions and thousands of write transactions per second, all while ensuring synchronous command journaling to a local SSD. This capability is the primary motivation behind the development of OrigoDB. Utilizing a single object-oriented domain model is much more efficient than managing an entire stack that encompasses a relational model, object/relational mapping, data access code, views, and stored procedures, which can lead to unnecessary complexity! Furthermore, the OrigoDB engine provides complete ACID compliance right from the start. Commands are executed sequentially, allowing the in-memory model to transition smoothly from one consistent state to another, ensuring data integrity at all times. This streamlined approach ultimately enhances overall system performance and reliability.

The Apache Xalan Project is responsible for creating and managing libraries and applications that convert XML documents through the use of XSLT standard stylesheets. Our various subprojects employ Java and C++ programming languages to develop the XSLT libraries. In April 2014, we released version 2.7.2 of Xalan-Java. Developers can download this latest version, Xalan-Java 2.7.2, for their projects. Ongoing development updates are available in our subversion repository. This recent release addresses a security vulnerability that was identified in version 2.7.1. Although the previous distributions of Xalan-J 2.7.1 can still be accessed through the Apache Archives, our project is considered mature and stable. Discussions regarding potential support for XPath-2 have been initiated, and we welcome your involvement in this significant overhaul of the library. You are encouraged to engage with us by following our progress and sharing your insights on the Java users and developers mailing lists, where your contributions would be greatly appreciated.

StyleVision simplifies the intricacies of XSLT programming by enabling users to create reports and forms through a visual interface. With a straightforward drag-and-drop method, you can design intricate layouts for displaying XML, XBRL, or database information across various channels. The process of crafting XSLT stylesheets for report generation in StyleVision is both versatile and user-friendly, enhanced by smart menus and assistance windows. Utilizing advanced stylesheet capabilities, users can establish conditional templates, perform automatic calculations, and apply rich formatting to inputs, among other features. This tool is particularly well-suited for the creation of multi-channel or multi-format business report publications. No matter if your goal is to publish XML, database, or XBRL content—or a blend of these formats—you can effortlessly craft complex reports utilizing the intuitive drag-and-drop functionality of StyleVision. Additionally, you have the option to automate your multi-channel report publishing tasks through the produced XSL stylesheets or by leveraging the efficient capabilities of StyleVision Server, enhancing productivity further. In this way, StyleVision not only streamlines the design process but also boosts efficiency in report generation and publication.

Altova XMLSpy stands out as the top-selling editor globally for JSON and XML, offering an array of tools for modeling, editing, transforming, and debugging these technologies. With its advanced graphical schema designer, code generation capabilities, file converters, and debugging tools, XMLSpy equips developers with everything they need to create complex applications, supporting formats such as XSD, XSLT, XQuery, XBRL, and SOAP. Developers often seek a JSON and XML editor that goes beyond mere bracket matching and basic validation, and XMLSpy delivers a robust feature set including graphical views, intuitive code generators, wizards, and intelligent editing functionalities that significantly enhance productivity. By simplifying the editing process for XML and associated technologies, XMLSpy features an easy-to-navigate interface enriched with diverse views and options. No matter your preference for a text-based or graphical XML viewer, XMLSpy is designed to provide smart assistance throughout the editing experience, ensuring a seamless workflow. Ultimately, XMLSpy transforms the way developers interact with JSON and XML, making it an indispensable tool in their toolkit.

Sedna is an open-source native XML database that offers a comprehensive suite of fundamental database functionalities, such as persistent storage, ACID transactions, security measures, indexing, and hot backups. It boasts adaptable XML processing capabilities, featuring a W3C XQuery implementation that is seamlessly integrated with full-text search options and a node-level update syntax. Users can access several straightforward examples that are executable directly from the command line, alongside detailed instructions on how to execute the provided examples with Sedna. The distribution of Sedna includes a set of examples centered around the XMark XML benchmark, which facilitates easy exploration of Sedna's features. Among these examples are processes for bulk loading a sample XML document and executing various sample XQuery queries and updates on it. In the following section, we will demonstrate how to execute one of these examples effectively. Additionally, this user-friendly approach ensures that both beginners and experienced users can quickly grasp the functionalities available within Sedna.

TEXTML Server serves as a specialized database system specifically created for the effective storage and retrieval of XML documents, in addition to various other formats such as PDFs and images. This system acts as a fundamental component for applications that require the management of extensive XML data or for those dealing with loosely structured information that conventional relational databases struggle to accommodate efficiently. Its core design focusing on XML grants TEXTML Server significant adaptability, making it an excellent fit for a broad range of applications. Users can implement it independently or in conjunction with traditional relational databases, enhancing its utility. The system is compatible with both two-tier and n-tier architectures, facilitating browser-based applications as well. Moreover, client applications that utilize the TEXTML SDK can operate seamlessly on Windows as well as multiple distributions of Linux. For comprehensive details regarding system requirements, users are encouraged to consult the TEXTML Server Installation Guide, ensuring a smooth setup process. Overall, TEXTML Server stands out as a powerful tool for developers needing to handle complex data structures efficiently.

BaseX is a powerful and efficient XML database engine, featuring a fully compliant XQuery 3.1 processor that adheres to W3C Update and Full Text extensions. This platform is ideal for creating intricate, data-heavy web applications and provides user-friendly interfaces, both desktop and web-based, that enhance your understanding of the data. As an entirely open-source solution, BaseX encourages users to join its mailing lists for continuous updates. The company behind BaseX, BaseX GmbH, offers expert support, custom software solutions, and training on XML technologies to help users maximize their experience. If you appreciate BaseX and wish to contribute to its open-source growth, consider making a donation. Additionally, BaseX is lightweight, user-friendly, and designed to function seamlessly right after installation, making it accessible for developers of all levels. It's no wonder that many users are drawn to BaseX for their XML database needs.

DiffDog offers an array of advanced features that enable users to compare and merge various types of text files, accommodating formats like Unicode, ASCII, and MBCS among others. It provides the ability to perform bi-directional merges and allows for direct editing of the files being compared. Additionally, DiffDog ensures that a backup of each file is generated automatically, which permits users to easily revert to the original version from the server or disk whenever necessary. The tool's XML differencing and editing capabilities leverage Altova’s established reputation as the developer of XMLSpy, a leading solution in XML development. With essential functionalities such as well-formedness checks, validation, code completion, and DTD/schema entry aids, DiffDog stands out as an indispensable tool for web and software developers who work with XML. Its user-friendly interface further enhances the experience, making complex tasks more manageable.

MissionKit provides a comprehensive suite of enterprise-level tools for XML, JSON, SQL, and UML, tailored for information architects and application developers. This suite features renowned products like Altova XMLSpy, MapForce, and StyleVision, which are designed to facilitate the creation of modern software solutions. The integrated nature of the Altova MissionKit tools allows users to enhance efficiency in development processes, resulting in both time savings and reduced costs. By selecting MissionKit, you can acquire all the listed products for a fraction of the individual purchase prices—specifically, seven powerful tools for less than the cost of just two!* Among its offerings, the Altova XMLSpy stands out as the leading graphical editor for both JSON and XML, equipped with a sophisticated schema designer, code generation capabilities, file conversion tools, debugging and profiling features, comprehensive database integration, and support for a variety of standards including XSLT, XPath, XQuery, WSDL, SOAP, XBRL, and Open XML (OOXML). Furthermore, it seamlessly integrates with popular development environments such as Visual Studio and Eclipse, thereby providing a robust solution for developers.

By completing a single installation step, you gain access to all the necessary tools at once. This eliminates the hassle of configuring various system components separately. The platform is fully equipped with features, enabling the development of sophisticated applications with ease. Utilizing XML throughout all layers renders mapping technologies unnecessary and boosts overall productivity. Additionally, every version of eXist-db is Open Source, making it suitable for academic, non-commercial, and commercial use alike. This flexibility ensures that developers can leverage its capabilities across a wide range of projects.

Unlock the potential of your data, expedite insightful decision-making, and attain agility in data management securely with the MarkLogic data platform. This platform allows you to merge your data with all relevant metadata within a unified service, leading to quicker and more informed decision-making. Experience a reliable and efficient approach to securely link data and metadata, derive meaningful insights, and access high-quality contextualized information throughout your organization using the MarkLogic data platform. Gain real-time insights into your customers to deliver relevant and seamless interactions, uncover new opportunities to drive innovation, and facilitate compliant access within a single data framework. With MarkLogic, you have a solid foundation that supports your essential business and technical goals both now and in the future, ensuring you stay ahead in a dynamic market.

Engaging applications captivate users while motivating developers to innovate. To meet the growing demands of the digital landscape, consider utilizing the DataStax Astra Streaming service platform. This cloud-native platform for messaging and event streaming is built on the robust foundation of Apache Pulsar. With Astra Streaming, developers can create streaming applications that leverage a multi-cloud, elastically scalable architecture. Powered by the advanced capabilities of Apache Pulsar, this platform offers a comprehensive solution that encompasses streaming, queuing, pub/sub, and stream processing. Astra Streaming serves as an ideal partner for Astra DB, enabling current users to construct real-time data pipelines seamlessly connected to their Astra DB instances. Additionally, the platform's flexibility allows for deployment across major public cloud providers, including AWS, GCP, and Azure, thereby preventing vendor lock-in. Ultimately, Astra Streaming empowers developers to harness the full potential of their data in real-time environments.

Berkeley DB encompasses a suite of embedded key-value database libraries that deliver scalable and high-performance data management functionalities for various applications. Its products utilize straightforward function-call APIs for accessing and managing data efficiently. With Berkeley DB, developers can create tailored data management solutions that bypass the typical complexities linked with custom projects. The library offers a range of reliable building-block technologies that can be adapted to meet diverse application requirements, whether for handheld devices or extensive data centers, catering to both local storage needs and global distribution, handling data volumes that range from kilobytes to petabytes. This versatility makes Berkeley DB a preferred choice for developers looking to implement efficient data solutions.

Red Hat® OpenShift® Streams for Apache Kafka is a cloud-managed service designed to enhance the developer experience for creating, deploying, and scaling cloud-native applications, as well as for modernizing legacy systems. This service simplifies the processes of creating, discovering, and connecting to real-time data streams, regardless of their deployment location. Streams play a crucial role in the development of event-driven applications and data analytics solutions. By enabling seamless operations across distributed microservices and handling large data transfer volumes with ease, it allows teams to leverage their strengths, accelerate their time to value, and reduce operational expenses. Additionally, OpenShift Streams for Apache Kafka features a robust Kafka ecosystem and is part of a broader suite of cloud services within the Red Hat OpenShift product family, empowering users to develop a diverse array of data-driven applications. With its powerful capabilities, this service ultimately supports organizations in navigating the complexities of modern software development.

SelectDB is an innovative data warehouse built on Apache Doris, designed for swift query analysis on extensive real-time datasets. Transitioning from Clickhouse to Apache Doris facilitates the separation of the data lake and promotes an upgrade to a more efficient lake warehouse structure. This high-speed OLAP system handles nearly a billion query requests daily, catering to various data service needs across multiple scenarios. To address issues such as storage redundancy, resource contention, and the complexities of data governance and querying, the original lake warehouse architecture was restructured with Apache Doris. By leveraging Doris's capabilities for materialized view rewriting and automated services, it achieves both high-performance data querying and adaptable data governance strategies. The system allows for real-time data writing within seconds and enables the synchronization of streaming data from databases. With a storage engine that supports immediate updates and enhancements, it also facilitates real-time pre-polymerization of data for improved processing efficiency. This integration marks a significant advancement in the management and utilization of large-scale real-time data.

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.

The continuous integration tool known as Apache Gump was the inaugural project created by the Apache Software Foundation. Developed in Python, it offers comprehensive support for build tools like Apache Ant and Apache Maven (versions 1.x to 3.x). What sets Gump apart is its capability to build and compile software against the most recent development iterations of various projects. This functionality enables Gump to identify potentially breaking changes to software just hours after they are committed to the version control system. Upon detecting such changes, it promptly alerts the project team, providing access to more extensive reports online for further investigation. While you can install and operate Gump on your personal computer to manage your own projects, it is predominantly recognized for its role in building numerous Apache projects and their respective dependencies. To facilitate this, the Gump initiative maintains a dedicated server specifically for its operations, ensuring efficiency and reliability in continuous integration processes. Gump's commitment to early detection of issues greatly enhances the overall software development cycle.

IBM Db2 encompasses a suite of data management solutions, prominently featuring the Db2 relational database. These offerings incorporate AI-driven functionalities designed to streamline the management of both structured and unstructured data across various on-premises and multicloud settings. By simplifying data accessibility, the Db2 suite empowers businesses to leverage the advantages of AI effectively. Most components of the Db2 family are integrated within the IBM Cloud Pak® for Data platform, available either as additional features or as built-in data source services, ensuring that nearly all data is accessible across hybrid or multicloud frameworks to support AI-driven applications. You can easily unify your transactional data repositories and swiftly extract insights through intelligent, universal querying across diverse data sources. The multimodel functionality helps reduce expenses by removing the necessity for data replication and migration. Additionally, Db2 offers enhanced flexibility, allowing for deployment on any cloud service provider, which further optimizes operational agility and responsiveness. This versatility in deployment options ensures that businesses can adapt their data management strategies as their needs evolve.

In contemporary enterprises, the surge of Big Data trends and XBRL requirements is generating vast and continuously expanding volumes of data in various formats such as XML, XBRL, JSON, and Avro. Fortunately, there is now a state-of-the-art, lightning-fast engine designed to validate, process, transform, and query all of this data efficiently. RaptorXML guarantees strict adherence to all pertinent XML, XBRL, and JSON standards and undergoes thorough regression and conformance testing, utilizing Altova’s extensive in-house collection of test suites along with industry-standard testing and real-world customer scenarios. As the popularity of JSON continues to grow, so does the necessity for ensuring the accuracy and validity of data transactions, which RaptorXML addresses by offering comprehensive features for JSON syntax checking, validation, and JSON Schema compliance. This engine not only streamlines data handling but also enhances reliability in data exchanges.

Amazon Managed Streaming for Apache Kafka (Amazon MSK) simplifies the process of creating and operating applications that leverage Apache Kafka for handling streaming data. As an open-source framework, Apache Kafka enables the construction of real-time data pipelines and applications. Utilizing Amazon MSK allows you to harness the native APIs of Apache Kafka for various tasks, such as populating data lakes, facilitating data exchange between databases, and fueling machine learning and analytical solutions. However, managing Apache Kafka clusters independently can be quite complex, requiring tasks like server provisioning, manual configuration, and handling server failures. Additionally, you must orchestrate updates and patches, design the cluster to ensure high availability, secure and durably store data, establish monitoring systems, and strategically plan for scaling to accommodate fluctuating workloads. By utilizing Amazon MSK, you can alleviate many of these burdens and focus more on developing your applications rather than managing the underlying infrastructure.

Flexter is an entirely automated solution that eliminates the need for coding skills, allowing users to efficiently un-silo industry-standard XML data and transform it into a format suitable for database use. Regardless of the industry, data is often stored in formats that require careful extraction and interpretation to be useful, creating challenges for effective analysis. What sets Flexter apart in the realm of data management and warehousing is its capability to fully automate the data conversion process. This issue is particularly prevalent in sectors like insurance, finance, healthcare, travel, and retail, where conventional methods for accessing and analyzing vital data can be slow, tedious, and costly. Such inefficiencies hinder the timely flow of information that data analysts require, ultimately affecting crucial decision-making at higher organizational levels. By streamlining this process, Flexter allows businesses to allocate more time and resources toward delivering value while ensuring that critical data is swiftly converted into a format that is both readable and ready for analysis, thereby enhancing overall productivity and decision-making capabilities. In today’s fast-paced environment, the ability to quickly access and analyze data is essential for maintaining a competitive edge.

Apache DataFusion is a versatile and efficient query engine crafted in Rust, leveraging Apache Arrow for its in-memory data representation. It caters to developers engaged in creating data-focused systems, including databases, data frames, machine learning models, and real-time streaming applications. With its SQL and DataFrame APIs, DataFusion features a vectorized, multi-threaded execution engine that processes data streams efficiently and supports various partitioned data sources. It is compatible with several native formats such as CSV, Parquet, JSON, and Avro, and facilitates smooth integration with popular object storage solutions like AWS S3, Azure Blob Storage, and Google Cloud Storage. The architecture includes a robust query planner and an advanced optimizer that boasts capabilities such as expression coercion, simplification, and optimizations that consider distribution and sorting, along with automatic reordering of joins. Furthermore, DataFusion allows for extensive customization, enabling developers to incorporate user-defined scalar, aggregate, and window functions along with custom data sources and query languages, making it a powerful tool for diverse data processing needs. This adaptability ensures that developers can tailor the engine to fit their unique use cases effectively.

An open-source, comprehensive microservice framework offers high performance right out of the box, ensuring compatibility with widely used ecosystems and supporting multiple programming languages. It guarantees service contracts via OpenAPI and features one-click scaffolding to expedite the development of microservice applications. This solution enables the ecological extension for various programming languages, including Java, Golang, PHP, and NodeJS. Apache ServiceComb serves as a robust open-source microservices framework, comprising several components that can be tailored to diverse scenarios through strategic combinations. This guide is designed to help newcomers swiftly get acquainted with Apache ServiceComb, making it an ideal starting point for beginners. Additionally, the framework allows for a separation between programming and communication models, enabling developers to integrate any desired communication model as needed. Consequently, application developers can prioritize API development while effortlessly adapting their communication strategies during deployment. With this flexibility, the framework enhances productivity and streamlines the microservice application lifecycle.

WarpStream serves as a data streaming platform that is fully compatible with Apache Kafka, leveraging object storage to eliminate inter-AZ networking expenses and disk management, while offering infinite scalability within your VPC. The deployment of WarpStream occurs through a stateless, auto-scaling agent binary, which operates without the need for local disk management. This innovative approach allows agents to stream data directly to and from object storage, bypassing local disk buffering and avoiding any data tiering challenges. Users can instantly create new “virtual clusters” through our control plane, accommodating various environments, teams, or projects without the hassle of dedicated infrastructure. With its seamless protocol compatibility with Apache Kafka, WarpStream allows you to continue using your preferred tools and software without any need for application rewrites or proprietary SDKs. By simply updating the URL in your Kafka client library, you can begin streaming immediately, ensuring that you never have to compromise between reliability and cost-effectiveness again. Additionally, this flexibility fosters an environment where innovation can thrive without the constraints of traditional infrastructure.

Apache Sentry™ serves as a robust system for implementing detailed role-based authorization for both data and metadata within a Hadoop cluster environment. Achieving Top-Level Apache project status after graduating from the Incubator in March 2016, Apache Sentry is recognized for its effectiveness in managing granular authorization. It empowers users and applications to have precise control over access privileges to data stored in Hadoop, ensuring that only authenticated entities can interact with sensitive information. Compatibility extends to a range of frameworks, including Apache Hive, Hive Metastore/HCatalog, Apache Solr, Impala, and HDFS, though its primary focus is on Hive table data. Designed as a flexible and pluggable authorization engine, Sentry allows for the creation of tailored authorization rules that assess and validate access requests for various Hadoop resources. Its modular architecture increases its adaptability, making it capable of supporting a diverse array of data models within the Hadoop ecosystem. This flexibility positions Sentry as a vital tool for organizations aiming to manage their data security effectively.

ContentBox is a professional open-source (Apache 2 License), modular content management engine that lets you easily create websites, blogs and wikis. ContentBox is a modular, secure, flexible and scalable content management engine that can be combined with world-class support to get your projects done quickly. ContentBox CMS can be deployed to any ColdFusion/CFML or Java Servlet Container. ContentBox is built on the ColdBox Platform, an open-source MVC framework that powers ColdFusion/CFML applications. It has been used by thousands of developers around the world. Clients include NASA, ESRI and Adobe TV. ContentBox is powered by Hibernate (the de-facto standard Object Relational Mapper), and can be used in any Java environment. Our entire infrastructure was designed with cloud deployment and scalability in mind.

Access on-chain data more efficiently and at reduced costs, leveraging the trustless capabilities of ZK technology. Utilize transactions, receipts, and historical states directly within your smart contract. Axiom enables computation across the full history of Ethereum, with all operations verified on-chain through ZK proofs. Merge information from block headers, accounts, contract storage, transactions, and receipts seamlessly. Utilize the Axiom SDK to define computations across Ethereum's history using Typescript. Tap into our extensive library of ZK primitives designed for arithmetic, logic, and array functions, all of which can be verified on-chain. Axiom ensures that query outcomes are verified on-chain using ZK proofs before relaying them to your smart contract's callback. Create genuinely trustless on-chain applications with ZK-verified outcomes provided by Axiom. Evaluate and compensate protocol participants completely trustlessly, without relying on external oracles. Recognize and reward contributions to the protocol based on on-chain activity, extending even to external protocols, while also implementing penalties for misconduct according to tailored criteria. This framework fosters a more reliable and accountable decentralized ecosystem.

HtmlUnit serves as a "GUI-less browser for Java applications," designed to model HTML documents while providing an API for interactions with web pages, such as loading pages, submitting forms, and following links, which mirrors the functionality of a traditional web browser. Its JavaScript support is notably robust and continues to evolve, allowing it to effectively manage complex AJAX scenarios, and it can mimic various browsers like Chrome, Firefox, or Edge based on the chosen settings. While primarily aimed at testing or data extraction from websites, HtmlUnit is not a standalone unit testing framework; instead, it functions within larger testing frameworks like JUnit or TestNG to replicate browser behavior. This tool serves as the foundation for many open-source applications, including WebDriver, Arquillian Drone, and Serenity BDD, and is widely adopted by numerous projects focused on automated web testing, such as Apache Shiro, Apache Struts, and Quarkus. Its ability to operate without a graphical user interface makes it particularly valuable for developers seeking to automate browser interactions in a more efficient and resource-friendly manner.

Samza enables the development of stateful applications that can handle real-time data processing from various origins, such as Apache Kafka. Proven to perform effectively at scale, it offers versatile deployment choices, allowing execution on YARN or as an independent library. With the capability to deliver remarkably low latencies and high throughput, Samza provides instantaneous data analysis. It can manage multiple terabytes of state through features like incremental checkpoints and host-affinity, ensuring efficient data handling. Additionally, Samza's operational simplicity is enhanced by its deployment flexibility—whether on YARN, Kubernetes, or in standalone mode. Users can leverage the same codebase to seamlessly process both batch and streaming data, which streamlines development efforts. Furthermore, Samza integrates with a wide range of data sources, including Kafka, HDFS, AWS Kinesis, Azure Event Hubs, key-value stores, and ElasticSearch, making it a highly adaptable tool for modern data processing needs.

Apache Storm is a distributed computation system that is both free and open source, designed for real-time data processing. It simplifies the reliable handling of endless data streams, similar to how Hadoop revolutionized batch processing. The platform is user-friendly, compatible with various programming languages, and offers an enjoyable experience for developers. With numerous applications including real-time analytics, online machine learning, continuous computation, distributed RPC, and ETL, Apache Storm proves its versatility. It's remarkably fast, with benchmarks showing it can process over a million tuples per second on a single node. Additionally, it is scalable and fault-tolerant, ensuring that data processing is both reliable and efficient. Setting up and managing Apache Storm is straightforward, and it seamlessly integrates with existing queueing and database technologies. Users can design Apache Storm topologies to consume and process data streams in complex manners, allowing for flexible repartitioning between different stages of computation. For further insights, be sure to explore the detailed tutorial available.

It accommodates various combinations of local and remote execution, management styles, as well as imperative and declarative methodologies. Rather than imposing a specific framework, it empowers you to determine what to automate and how to achieve it, enabling you to create an automation tool tailored to your needs. Rex operates locally, even when overseeing remote connections through SSH, which facilitates immediate usability without extensive rollout procedures or needing approval from others, making it particularly suitable for gradual automation efforts. Furthermore, whenever you encounter the limits of Rex's built-in capabilities, you have access to a robust programming language and a rich module ecosystem that allows for seamless enhancements, whether through modules from CPAN or your personalized code. We are strong advocates for open-source principles, which is why Rex and all its components are distributed under the Apache 2.0 license. You are encouraged to become a part of the community to contribute to the ongoing improvement of Rex, fostering innovation and collaboration. Together, we can enhance the functionality and usability of this powerful tool even further.

SiteWhere utilizes Kubernetes for deploying its infrastructure and microservices, making it versatile for both on-premise setups and virtually any cloud service provider. The system is supported by robust configurations of Apache Kafka, Zookeeper, and Hashicorp Consul, ensuring a reliable infrastructure. Each microservice is designed to scale individually while also enabling seamless integration with others. It presents a comprehensive multitenant IoT ecosystem that encompasses device management, event ingestion, extensive event storage capabilities, REST APIs, data integration, and additional features. The architecture is distributed and developed using Java microservices that operate on Docker, with an Apache Kafka processing pipeline for efficiency. Importantly, SiteWhere CE remains open source, allowing free use for both personal and commercial purposes. Additionally, the SiteWhere team provides free basic support along with a continuous flow of innovative features to enhance the platform's functionality. This emphasis on community-driven development ensures that users can benefit from ongoing improvements and updates.

Apache OpenWhisk is a distributed, open-source Serverless platform designed to execute functions (fx) in response to various events, scaling seamlessly according to demand. By utilizing Docker containers, OpenWhisk takes care of the underlying infrastructure and server management, allowing developers to concentrate on creating innovative and efficient applications. The platform features a programming model where developers can implement functional logic (termed Actions) in any of the supported programming languages, which can be scheduled dynamically and executed in reaction to relevant events triggered by external sources (Feeds) or through HTTP requests. Additionally, OpenWhisk comes with a REST API-based Command Line Interface (CLI) and various tools to facilitate service packaging, cataloging, and deployment options for popular container frameworks. As a result of its container-based architecture, Apache OpenWhisk is compatible with numerous deployment strategies, whether locally or in cloud environments, giving developers the flexibility they need. The versatility of OpenWhisk also enables it to integrate with a wide range of services, enhancing its utility in modern application development.

TIBCO Streaming is an advanced analytics platform focused on real-time processing and analysis of fast-moving data streams, which empowers organizations to make swift, data-informed choices. With its low-code development environment found in StreamBase Studio, users can create intricate event processing applications with ease and minimal coding requirements. The platform boasts compatibility with over 150 connectors, such as APIs, Apache Kafka, MQTT, RabbitMQ, and databases like MySQL and JDBC, ensuring smooth integration with diverse data sources. Incorporating dynamic learning operators, TIBCO Streaming allows for the use of adaptive machine learning models that deliver contextual insights and enhance automation in decision-making. Additionally, it provides robust real-time business intelligence features that enable users to visualize current data alongside historical datasets for a thorough analysis. The platform is also designed for cloud readiness, offering deployment options across AWS, Azure, GCP, and on-premises setups, thereby ensuring flexibility for various organizational needs. Overall, TIBCO Streaming stands out as a powerful solution for businesses aiming to harness real-time data for strategic advantages.

Streamline your tasks by employing browser bots to automate actions on any website or web application, making repetitive activities a breeze. Installation is straightforward and comes with a free trial that doesn’t require a credit card. After installation, simply pin Axiom to your Chrome Toolbar for easy access—click the icon to launch or hide the interface. Each bot can be tailored to suit your specific requirements, allowing you to create as many as necessary. Automate various actions such as clicking and typing across any site, and you can opt for manual execution, schedule them, or link with Zapier to initiate external events seamlessly. With Axiom.ai, you can achieve automation within minutes, and while a desktop application is optional, it’s essential for functions involving file uploads or downloads. This application is compatible with any subscription level and is available for Apple, PC, and Linux systems. For those on the cloud tier, Zapier can initiate Axiom operations, while Axiom can also send data to Zapier for further processing at any tier. Moreover, any tool capable of sending or receiving webhooks can be configured to integrate with Axiom, enhancing its versatility and functionality. This makes Axiom not just a tool, but a powerful ally in optimizing your web interactions.

Spark Streaming extends the capabilities of Apache Spark by integrating its language-based API for stream processing, allowing you to create streaming applications in the same manner as batch applications. This powerful tool is compatible with Java, Scala, and Python. One of its key features is the automatic recovery of lost work and operator state, such as sliding windows, without requiring additional code from the user. By leveraging the Spark framework, Spark Streaming enables the reuse of the same code for batch processes, facilitates the joining of streams with historical data, and supports ad-hoc queries on the stream's state. This makes it possible to develop robust interactive applications rather than merely focusing on analytics. Spark Streaming is an integral component of Apache Spark, benefiting from regular testing and updates with each new release of Spark. Users can deploy Spark Streaming in various environments, including Spark's standalone cluster mode and other compatible cluster resource managers, and it even offers a local mode for development purposes. For production environments, Spark Streaming ensures high availability by utilizing ZooKeeper and HDFS, providing a reliable framework for real-time data processing. This combination of features makes Spark Streaming an essential tool for developers looking to harness the power of real-time analytics efficiently.

Batch and streaming data processing can be streamlined effortlessly. With the capability to write once and run anywhere, it is ideal for mission-critical production tasks. Beam allows you to read data from a wide variety of sources, whether they are on-premises or cloud-based. It seamlessly executes your business logic across both batch and streaming scenarios. The outcomes of your data processing efforts can be written to the leading data sinks available in the market. This unified programming model simplifies operations for all members of your data and application teams. Apache Beam is designed for extensibility, with frameworks like TensorFlow Extended and Apache Hop leveraging its capabilities. You can run pipelines on various execution environments (runners), which provides flexibility and prevents vendor lock-in. The open and community-driven development model ensures that your applications can evolve and adapt to meet specific requirements. This adaptability makes Beam a powerful choice for organizations aiming to optimize their data processing strategies.

Drools serves as a comprehensive Business Rules Management System (BRMS) that includes a core Business Rules Engine (BRE) and a web-based application for authoring and managing rules, known as Drools Workbench. Additionally, it offers complete runtime support for Decision Model and Notation (DMN) models, adhering to Conformance level 3, along with an Eclipse IDE plugin to facilitate core development tasks. As an open-source solution released under the Apache License 2.0, Drools is developed entirely in pure Java™ and is compatible with any Java Virtual Machine (JVM). Furthermore, it can be readily accessed through the Maven Central repository, making it convenient for developers to integrate into their projects. This accessibility and flexibility highlight its appeal in various business environments.

Apache ServiceMix is an adaptable, open-source integration platform that consolidates the capabilities of Apache ActiveMQ, Camel, CXF, and Karaf into a robust runtime environment ideal for developing custom integration solutions. It delivers a comprehensive, enterprise-ready ESB that operates solely on OSGi technology. With Apache ActiveMQ, it ensures dependable messaging, while Apache Camel facilitates messaging, routing, and the implementation of Enterprise Integration Patterns. Furthermore, Apache CXF supports both WS and RESTful web services, and the OSGi-based server runtime is powered by Apache Karaf. Users can also leverage a BPM engine through Activiti and benefit from complete JPA support via Apache OpenJPA. For enhanced reliability, XA transaction management is managed through JTA and Apache Aries. Additionally, the platform offers legacy support for the deprecated JBI standard (post-ServiceMix 3.x series) through the Apache ServiceMix NMR, which features an extensive Event, Messaging, and Audit API. Applications tailored for ServiceMix can be constructed utilizing OSGi Blueprint, OSGi Declarative Services, and the now-legacy Spring DM framework, allowing for versatile integration possibilities. This makes Apache ServiceMix an invaluable tool for developers seeking to create sophisticated integration solutions.