Best Streaming Analytics Platforms in Australia - Page 2

Event Hubs serves as a fully managed service for real-time data ingestion, offering simplicity, reliability, and scalability. It enables the streaming of millions of events per second from diverse sources, facilitating the creation of dynamic data pipelines that allow for immediate responses to business obstacles. In times of emergencies, you can continue processing data thanks to its geo-disaster recovery and geo-replication capabilities. The service integrates effortlessly with other Azure offerings, unlocking valuable insights. Additionally, existing Apache Kafka clients and applications can connect to Event Hubs without the need for code modifications, providing a managed Kafka experience without the burden of handling your own clusters. You can enjoy both real-time data ingestion and microbatching within the same stream, allowing you to concentrate on extracting insights from your data rather than managing infrastructure. With Event Hubs, you can construct real-time big data pipelines and swiftly tackle business challenges as they arise, ensuring your organization remains agile and responsive in a fast-paced environment.

KX Insights serves as a cloud-native platform that provides essential real-time performance analytics and actionable intelligence continuously. By utilizing advanced techniques such as complex event processing, rapid analytics, and machine learning interfaces, it facilitates swift decision-making and automates responses to events in mere fractions of a second. The migration to the cloud encompasses not only storage and computational flexibility but also includes a comprehensive array of elements: data, tools, development, security, connectivity, operations, and maintenance. KX empowers organizations to harness this cloud capability, enabling them to make more informed and insightful decisions by seamlessly integrating real-time analytics into their operational frameworks. Additionally, KX Insights adheres to industry standards, promoting openness and interoperability with diverse technologies, which accelerates the delivery of insights in a cost-effective manner. Its architecture is based on microservices, designed for efficiently capturing, storing, and processing high-volume and high-velocity data utilizing established cloud standards, services, and protocols, ensuring optimal performance and scalability. This innovative approach not only enhances operational efficiency but also positions businesses to adapt swiftly to changing market dynamics.

KX Streaming Analytics offers a comprehensive solution for ingesting, storing, processing, and analyzing both historical and time series data, ensuring that analytics, insights, and visualizations are readily accessible. To facilitate rapid productivity for your applications and users, the platform encompasses the complete range of data services, which includes query processing, tiering, migration, archiving, data protection, and scalability. Our sophisticated analytics and visualization tools, which are extensively utilized in sectors such as finance and industry, empower you to define and execute queries, calculations, aggregations, as well as machine learning and artificial intelligence on any type of streaming and historical data. This platform can be deployed across various hardware environments, with the capability to source data from real-time business events and high-volume inputs such as sensors, clickstreams, radio-frequency identification, GPS systems, social media platforms, and mobile devices. Moreover, the versatility of KX Streaming Analytics ensures that organizations can adapt to evolving data needs and leverage real-time insights for informed decision-making.

Introducing revolutionary data streaming features that enable unparalleled customer experiences. The Kafka API and its ecosystem are fully compatible with Redpanda, which boasts predictable low latencies and ensures zero data loss. Redpanda is designed to outperform Kafka by up to ten times, offering enterprise-level support and timely hotfixes. It also includes automated backups to S3 or GCS, providing a complete escape from the routine operations associated with Kafka. Additionally, it supports both AWS and GCP environments, making it a versatile choice for various cloud platforms. Built from the ground up for ease of installation, Redpanda allows for rapid deployment of streaming services. Once you witness its incredible capabilities, you can confidently utilize its advanced features in a production setting. We take care of provisioning, monitoring, and upgrades without requiring access to your cloud credentials, ensuring that sensitive data remains within your environment. Your streaming infrastructure will be provisioned, operated, and maintained seamlessly, with customizable instance types available to suit your specific needs. As your requirements evolve, expanding your cluster is straightforward and efficient, allowing for sustainable growth.

Insigna - The complete Platform for Real-time Analytics and Data Management. Insigna offers integration, automated processing, transformation, data preparation and real-time analytics to derive and deliver intelligence to various stakeholders. Insigna enables connectivity with the most popular network communication protocols, data stores, enterprise applications, and cloud platforms. Coupled with a rich set of out-of-the-box data transformation capabilities, enterprises greatly benefit from the opportunities offered by operations data generated in real-time.

Cumulocity IoT stands out as the premier low-code, self-service IoT platform, uniquely offering pre-integration with essential tools for rapid outcomes, including device connectivity and management, application enablement, integration, and advanced analytics for both streaming and predictive insights. Break free from restrictive proprietary technology ecosystems, as this platform is entirely open, allowing you to connect any device today or in the future. Customize your setup by bringing your own hardware and selecting the components that suit your needs best. You can quickly jump into the IoT world within minutes by connecting a device, monitoring its data, and crafting an interactive dashboard in real-time. Additionally, you can establish rules to oversee and respond to events—all without needing IT assistance or writing any code! Effortlessly integrate fresh IoT data into the existing core enterprise systems, applications, and processes that have supported your business for years, again without the need for coding, ensuring seamless data flow. This capability enhances your understanding, providing you with richer context to make informed decisions and improve overall business outcomes.

Tealium Customer Data hub is an advanced platform that unifies, manages, and activates customer data across multiple touchpoints and channels. It allows businesses to create a real-time, cohesive view of their customers by integrating data from mobile apps, websites, and other digital sources. This centralized data center empowers organizations to deliver customized experiences, optimize marketing strategy, and enhance customer interaction. Tealium Customer Data Hub offers robust features such as data collection, audience segmentation and real-time orchestration of data. This allows businesses to transform raw data into actionable insight, driving more effective interactions with customers and improved business outcomes.

Apache Spark™ serves as a comprehensive analytics engine designed for extensive data processing tasks. It delivers exceptional performance for both batch and streaming workloads, utilizing an advanced Directed Acyclic Graph (DAG) scheduler, a sophisticated query optimizer, and an efficient physical execution engine. With over 80 high-level operators available, Spark simplifies the development of parallel applications. Additionally, users can interact with it through various shells, such as Scala, Python, R, and SQL. Spark supports a robust ecosystem of libraries, including SQL and DataFrames, MLlib for machine learning, GraphX for graph processing, and Spark Streaming for real-time data processing, allowing for seamless integration of these libraries within a single application. The platform is versatile, capable of running on multiple environments like Hadoop, Apache Mesos, Kubernetes, standalone setups, or cloud services. Furthermore, it can connect to a wide array of data sources, enabling access to information stored in HDFS, Alluxio, Apache Cassandra, Apache HBase, Apache Hive, and hundreds of other systems, thus providing flexibility to meet various data processing needs. This extensive functionality makes Spark an essential tool for data engineers and analysts alike.

Effortlessly gather, manage, and evaluate video and data streams on the fly. Amazon Kinesis simplifies the collection, processing, and analysis of streaming data in real-time, allowing you to gain valuable insights swiftly and respond to emerging information without delay. With its essential features, Amazon Kinesis provides a cost-effective way to handle streaming data at any scale while offering the adaptability to select the optimal tools tailored to your application's needs. You can utilize Amazon Kinesis to ingest real-time data types, including video, audio, application logs, website clickstreams, and IoT telemetry data, for various purposes such as machine learning and analytics. This platform allows you to process and analyze incoming data immediately, eliminating the need to wait for complete data collection before starting the processing phase. Furthermore, Amazon Kinesis supports the ingestion, buffering, and processing of streaming data instantaneously, enabling you to uncover insights within seconds or minutes instead of prolonging the wait for hours or days. The ability to act quickly based on live data enhances decision-making and operational efficiency across diverse industries.

Data processing that integrates both streaming and batch operations while being serverless, efficient, and budget-friendly. It offers a fully managed service for data processing, ensuring seamless automation in the provisioning and administration of resources. With horizontal autoscaling capabilities, worker resources can be adjusted dynamically to enhance overall resource efficiency. The innovation is driven by the open-source community, particularly through the Apache Beam SDK. This platform guarantees reliable and consistent processing with exactly-once semantics. Dataflow accelerates the development of streaming data pipelines, significantly reducing data latency in the process. By adopting a serverless model, teams can devote their efforts to programming rather than the complexities of managing server clusters, effectively eliminating the operational burdens typically associated with data engineering tasks. Additionally, Dataflow’s automated resource management not only minimizes latency but also optimizes utilization, ensuring that teams can operate with maximum efficiency. Furthermore, this approach promotes a collaborative environment where developers can focus on building robust applications without the distraction of underlying infrastructure concerns.

Informatica's AI-driven Data Engineering Streaming empowers data engineers to efficiently ingest, process, and analyze real-time streaming data, offering valuable insights. The advanced serverless deployment feature, coupled with an integrated metering dashboard, significantly reduces administrative burdens. With CLAIRE®-enhanced automation, users can swiftly construct intelligent data pipelines that include features like automatic change data capture (CDC). This platform allows for the ingestion of thousands of databases, millions of files, and various streaming events. It effectively manages databases, files, and streaming data for both real-time data replication and streaming analytics, ensuring a seamless flow of information. Additionally, it aids in the discovery and inventorying of all data assets within an organization, enabling users to intelligently prepare reliable data for sophisticated analytics and AI/ML initiatives. By streamlining these processes, organizations can harness the full potential of their data assets more effectively than ever before.

Esper Enterprise Edition offers a robust platform designed for both linear and elastic scalability, as well as reliable event processing that can withstand faults. It comes equipped with an EPL editor and debugger, supports hot deployment, and provides comprehensive reporting on metrics and memory usage, including detailed breakdowns per EPL. Additionally, it features Data Push capabilities for seamless multi-tier delivery from CEP to browsers and manages both logical and physical subscribers and their subscriptions effectively. Its web-based user interface allows users to oversee various distributed engine instances using JavaScript and HTML5, while also enabling the creation of composable and interactive displays for visualizing distributed event streams through charts, gauges, timelines, and grids. Furthermore, it includes JDBC-compliant client and server endpoints to ensure interoperability across systems. Notably, Esper Enterprise Edition is a proprietary commercial product developed by EsperTech, with source code accessibility granted solely for the support of customers. Such versatility and functionality make it a robust choice for enterprises seeking efficient event processing solutions.

Evam's Continuous Intelligence Platform integrates various products aimed at the processing and visualization of real-time data streams. It operates machine learning models in real time while enhancing the data with an advanced in-memory caching system. By doing so, EVAM allows companies in telecommunications, financial services, retail, transportation, and travel sectors to fully leverage their business potential. This platform's machine learning capabilities facilitate the processing of live data, enabling the visual design and orchestration of customer journeys through sophisticated analytical models and AI algorithms. Furthermore, EVAM helps businesses connect with their customers across various channels, including legacy systems, in real time. With the ability to collect and process billions of events instantaneously, companies can gain valuable insights into each customer’s preferences, allowing them to attract, engage, and retain clients more efficiently. The effectiveness of such a system not only enhances operational capabilities but also fosters deeper customer relationships.

Oracle Stream Analytics empowers users to handle and evaluate vast amounts of real-time data through advanced correlation techniques, enrichment capabilities, and machine learning integration. This platform delivers immediate, actionable insights for businesses dealing with streaming information, facilitating automated responses that support the needs of modern agile enterprises. It features Visual GEOProcessing with GEOFence relationship spatial analytics, enhancing location-based decision-making. Additionally, the introduction of a new Expressive Patterns Library encompasses various categories, such as Spatial, Statistical, General industry, and Anomaly detection, alongside streaming machine learning functionalities. With an intuitive visual interface, users can seamlessly explore live streaming data, enabling effective in-memory analytics that enhance real-time business strategies. Overall, this powerful tool significantly improves operational efficiency and decision-making processes in fast-paced environments.

Instant™, Enterprise Data and Intelligence. All transaction data is visible, as it happens, from anywhere in the world. Organizations can access worldwide accounting, liquidity management, marketing, and supply chain information with just one network connection. This allows them to be empowered with enterprise intelligence. The TreasuryPay product set streams global receivables information and provides instant accountancy as well as cognitive services. It is simply the most advanced intelligence platform and insights platform available to global organizations. You can instantly provide enriched information to your entire global organization. It's easy to make the change. The Return on Investment is remarkable. With TreasuryPay Instant™, you can now access actionable intelligence and global accountancy in real-time.

Apache Flink serves as a powerful framework and distributed processing engine tailored for executing stateful computations on both unbounded and bounded data streams. It has been engineered to operate seamlessly across various cluster environments, delivering computations with impressive in-memory speed and scalability. Data of all types is generated as a continuous stream of events, encompassing credit card transactions, sensor data, machine logs, and user actions on websites or mobile apps. The capabilities of Apache Flink shine particularly when handling both unbounded and bounded data sets. Its precise management of time and state allows Flink’s runtime to support a wide range of applications operating on unbounded streams. For bounded streams, Flink employs specialized algorithms and data structures optimized for fixed-size data sets, ensuring remarkable performance. Furthermore, Flink is adept at integrating with all previously mentioned resource managers, enhancing its versatility in various computing environments. This makes Flink a valuable tool for developers seeking efficient and reliable stream processing solutions.

Apama Streaming Analytics empowers businesses to analyze and act on Internet of Things (IoT) data and other rapidly changing information in real-time, enabling them to respond intelligently to events as they occur. The Apama Community Edition serves as a freemium option provided by Software AG, allowing users to explore, develop, and deploy streaming analytics applications in a practical setting. Additionally, the Software AG Data & Analytics Platform presents a comprehensive, modular suite of advanced features designed for efficient high-speed data management and real-time analytics, complete with seamless integration capabilities for all major enterprise data sources. Users have the flexibility to select from a range of functionalities, including streaming, predictive, and visual analytics, as well as messaging tools for straightforward integration with other enterprise applications, all supported by an in-memory data store for rapid data retrieval. Furthermore, this platform allows for the integration of historical and diverse data, making it particularly useful for model development and enhancing essential customer information. By leveraging these capabilities, organizations can gain deeper insights and drive more informed decision-making.

DataHub offers a range of SDKs and APIs along with various third-party plugins, including Flume and Logstash, to facilitate seamless data importation. The platform enables efficient data ingestion into DataHub, while the DataConnector module ensures real-time synchronization of this data to downstream storage and analytical frameworks like MaxCompute, OSS, and Tablestore. It allows for the integration of diverse data types generated from applications, websites, IoT devices, or databases, all in real time. With DataHub, users can manage their data uniformly, simplifying the process of delivering it to downstream systems tailored for analysis and archiving. This capability empowers organizations to establish a robust data streaming pipeline, maximizing the value extracted from their data assets. Furthermore, the comprehensive management features of DataHub enhance operational efficiency and data utilization across various sectors.

Axual serves as a Kafka-as-a-Service tailored for DevOps teams, empowering them to gain insights and make informed decisions through our user-friendly Kafka platform. For enterprises aiming to effortlessly incorporate data streaming into their foundational IT systems, Axual presents the ultimate solution. Our comprehensive Kafka platform is crafted to remove the necessity for in-depth technical expertise, offering an out-of-the-box solution that provides all the advantages of event streaming without the complications that typically accompany it. The Axual Platform stands as a complete solution, specifically designed to streamline and improve the deployment, management, and application of real-time data streaming using Apache Kafka. By offering a diverse range of features that address the varying requirements of contemporary enterprises, the Axual Platform allows organizations to fully leverage the capabilities of data streaming while significantly reducing complexity and operational burdens. This innovative approach not only simplifies processes but also empowers teams to focus on strategic initiatives.

VIA offers enhanced visibility throughout data and various organizational barriers, fostering operational efficiency across multiple sectors. With this tool, your team can swiftly identify issues, automate responses when feasible, and mitigate the risks that could adversely affect service and customer satisfaction. Through its proactive analytic value chain and focus on customer needs, VIA not only uncovers necessary actions but also ranks them according to their potential impact on customers, allowing you to make informed decisions that enhance business outcomes. Additionally, VIA Solution Templates streamline the implementation and customization of the Platform to align with your specific business needs, facilitating a smoother transition and greater adaptability. Ultimately, leveraging VIA can lead to more responsive and effective operational strategies.

BlackLynx's accelerators provide essential analytical capabilities exactly where they're needed, eliminating the necessity for specialized expertise. Regardless of the components of your analytics framework, you can enhance your data-driven enterprise through efficient and user-friendly heterogeneous computing. The integration of BlackStack's software and electronics significantly boosts processing speeds for sensors utilized in ground, naval, aerial, or space-based operations. Our software facilitates the rapid acceleration of pertinent AI/ML algorithms and various computational tasks, concentrating on real-time sensor processing, which encompasses signal detection, video analytics, missile tracking, radar interpretation, thermal imaging, and other object detection functionalities. By employing BlackStack software, organizations can greatly enhance the speed of processing for real-time data analytics. We empower our clients to delve into large-scale unstructured data that changes rapidly, enabling them to collect, filter, and systematically organize vast volumes of intelligence or cybersecurity forensic information, creating a more agile and responsive analytical environment. This approach not only streamlines data handling but also enhances decision-making processes across various sectors.

Explore Azure Stream Analytics, a user-friendly service for real-time analytics tailored for essential workloads. With just a few clicks, you can create a comprehensive serverless streaming pipeline. Transition from concept to production in mere minutes using SQL, which can be seamlessly enhanced with custom code and integrated machine learning features for more complex needs. Confidently execute your heaviest workloads, backed by a robust financial SLA that ensures reliability and performance. This powerful tool is ideal for organizations seeking to harness the power of real-time data processing.

Cloudera DataFlow for the Public Cloud (CDF-PC) is a versatile, cloud-based data distribution solution that utilizes Apache NiFi, enabling developers to seamlessly connect to diverse data sources with varying structures, process that data, and deliver it to a wide array of destinations. This platform features a flow-oriented low-code development approach that closely matches the preferences of developers when creating, developing, and testing their data distribution pipelines. CDF-PC boasts an extensive library of over 400 connectors and processors that cater to a broad spectrum of hybrid cloud services, including data lakes, lakehouses, cloud warehouses, and on-premises sources, ensuring efficient and flexible data distribution. Furthermore, the data flows created can be version-controlled within a catalog, allowing operators to easily manage deployments across different runtimes, thereby enhancing operational efficiency and simplifying the deployment process. Ultimately, CDF-PC empowers organizations to harness their data effectively, promoting innovation and agility in data management.

Xeotek accelerates the development and exploration of data applications and streams for businesses through its robust desktop and web applications. The Xeotek KaDeck platform is crafted to cater to the needs of developers, operations teams, and business users equally. By providing a shared platform for business users, developers, and operations, KaDeck fosters a collaborative environment that minimizes misunderstandings, reduces the need for revisions, and enhances overall transparency for the entire team. With Xeotek KaDeck, you gain authoritative control over your data streams, allowing for significant time savings by obtaining insights at both the data and application levels during projects or routine tasks. Easily export, filter, transform, and manage your data streams in KaDeck, simplifying complex processes. The platform empowers users to execute JavaScript (NodeV4) code, create and modify test data, monitor and adjust consumer offsets, and oversee their streams or topics, along with Kafka Connect instances, schema registries, and access control lists, all from a single, user-friendly interface. This comprehensive approach not only streamlines workflow but also enhances productivity across various teams and projects.

Hitachi is a Japan company and produces a software product named Hitachi Streaming Data Platform. Hitachi Streaming Data Platform is a type of Real-Time data streaming software, and provides features like data enrichment, data wrangling / data prep, multiple data source support, process automation, real-time analysis / reporting, and visualization dashboards. Hitachi Streaming Data Platform includes training through documentation. Hitachi Streaming Data Platform includes phone support support. Some alternatives to Hitachi Streaming Data Platform are Azure Stream Analytics, Amazon Kinesis, and Informatica Data Engineering Streaming.