Best Event Stream Processing Software in Brazil - Page 2

High-performing applications require a real-time exchange of information, exactly what TIBCO Cloud™ Messaging software provides. With multiple options, including Apache Kafka, Apache Pulsar, TIBCO Enterprise Message Service™, TIBCO FTL® and TIBCO eFTL™ software, we have you covered. Whether you need event-driven app integration; high-performance, low-latency messaging; connections for web apps to backend systems; or IoT integration, the robust yet simple TIBCO Cloud Messaging client API and cloud distribution network is the easiest way to connect. TIBCO Cloud Messaging software provides built-in fault tolerance, multi-zone data reliability, and scalable performance. It allows you to focus on application logic and not worry about deploying containers or infrastructure for your event streams. Simply connect your apps to the API and start publishing and subscribing to event messages immediately.

Turn your data into a realtime stream, making it immediately available and ready to use. Leo reduces the complexity of event sourcing by making it easy to create, visualize, monitor, and maintain your data flows. Once you unlock your data, you are no longer limited by the constraints of your legacy systems. Dramatically reduced dev time keeps your developers and stakeholders happy. Adopt microservice architectures to continuously innovate and improve agility. In reality, success with microservices is all about data. An organization must invest in a reliable and repeatable data backbone to make microservices a reality. Implement full-fledged search in your custom app. With data flowing, adding and maintaining a search database will not be a burden.

Connecting systems to scale AI initiatives is complex, expensive, and prone to fail. Pandio’s cloud-native managed solution simplifies your data pipelines to harness the power of AI. Access your data from anywhere at any time in order to query, analyze, and drive to insight. Big data analytics without the big cost. Enable data movement seamlessly. Streaming, queuing and pub-sub with unmatched throughput, latency, and durability. Design, train, and deploy machine learning models locally in less than 30 minutes. Accelerate your path to ML and democratize the process across your organization. And it doesn’t require months (or years) of disappointment. Pandio’s AI-driven architecture automatically orchestrates your models, data, and ML tools. Pandio works with your existing stack to accelerate your ML initiatives. Orchestrate your models and messages across your organization.

In the emerging digital world, billions of people, systems, and devices will interact in real-time, suggesting new and disruptive competitive advantages. How do you play there? By building distributed, stateful, rule-based event-processing systems, experimenting, learning, and quickly evolving. Data is arriving in real-time from hundreds of internal and external sources—and it has shelf-life; its value diminishes over time. With TIBCO, you can jump-start big data processing initiatives that give you the ability to sense, reason, respond, and visualize—much different and much faster and smarter than the traditional store, analyze, report, act approach. With multiple rule authoring environments, you support collaboration between IT developers and business professionals.

Responsive applications keep users engaged and developers inspired. Rise to meet these ever-increasing expectations with the DataStax Astra Streaming service platform. DataStax Astra Streaming is a cloud-native messaging and event streaming platform powered by Apache Pulsar. Astra Streaming allows you to build streaming applications on top of an elastically scalable, multi-cloud messaging and event streaming platform. Astra Streaming is powered by Apache Pulsar, the next-generation event streaming platform which provides a unified solution for streaming, queuing, pub/sub, and stream processing. Astra Streaming is a natural complement to Astra DB. Using Astra Streaming, existing Astra DB users can easily build real-time data pipelines into and out of their Astra DB instances. With Astra Streaming, avoid vendor lock-in and deploy on any of the major public clouds (AWS, GCP, Azure) compatible with open-source Apache Pulsar.

The Open, Multi-Cloud Stack for Modern Data Apps. Built on open-source Apache Cassandra™. Global-scale and 100% uptime without vendor lock-in. Deploy on multi-cloud, on-prem, open-source, and Kubernetes. Elastic and pay-as-you-go for improved TCO. Start building faster with Stargate APIs for NoSQL, real-time, reactive, JSON, REST, and GraphQL. Skip the complexity of multiple OSS projects and APIs that don’t scale. Ideal for commerce, mobile, AI/ML, IoT, microservices, social, gaming, and richly interactive applications that must scale-up and scale-down with demand. Get building modern data applications with Astra, a database-as-a-service powered by Apache Cassandra™. Use REST, GraphQL, JSON with your favorite full-stack framework Richly interactive apps that are elastic and viral-ready from Day 1. Pay-as-you-go Apache Cassandra DBaaS that scales effortlessly and affordably.

In-Memory Computing Platform. The digital world is different. Microseconds matter. That's why the world's largest organizations rely on us to power their most time-sensitive applications at scale. New data-enabled applications can deliver transformative business power – if they meet today’s requirement of immediacy. Hazelcast solutions complement virtually any database to deliver results that are significantly faster than a traditional system of record. Hazelcast’s distributed architecture provides redundancy for continuous cluster up-time and always available data to serve the most demanding applications. Capacity grows elastically with demand, without compromising performance or availability. The fastest in-memory data grid, combined with third-generation high-speed event processing, delivered through the cloud.

TIBCO ComputeDB™ is a memory optimized database based on Apache Spark. It delivers very high throughput, low latency, and high concurrency for unified analytic workloads that may combine streaming, interactive analytics and artificial intelligence in a single, easy to manage distributed cluste

Easily collect, process, and analyze video and data streams in real time. Amazon Kinesis makes it easy to collect, process, and analyze real-time, streaming data so you can get timely insights and react quickly to new information. Amazon Kinesis offers key capabilities to cost-effectively process streaming data at any scale, along with the flexibility to choose the tools that best suit the requirements of your application. With Amazon Kinesis, you can ingest real-time data such as video, audio, application logs, website clickstreams, and IoT telemetry data for machine learning, analytics, and other applications. Amazon Kinesis enables you to process and analyze data as it arrives and respond instantly instead of having to wait until all your data is collected before the processing can begin. Amazon Kinesis enables you to ingest, buffer, and process streaming data in real-time, so you can derive insights in seconds or minutes instead of hours or days.

Analyze, continuously query, and act on IoT and other streaming data at lightning fast speeds. Take real-time operations and analytics to the next level with intelligent applications that deploy quickly for taking action based on new decisions and models, all without extra overhead. TIBCO® Streaming software is enterprise-grade, cloud-ready streaming analytics for quickly building real-time applications at a fraction of the cost and risk of alternatives.

AI-powered Informatica Data Engineering Streaming enables data engineers to ingest, process, and analyze real-time streaming data for actionable insights. Advanced serverless deployment option​ with integrated metering dashboard cuts admin overhead. Rapidly build intelligent data pipelines with CLAIRE®-powered automation, including automatic change data capture (CDC). Ingest thousands of databases and millions of files, and streaming events. Efficiently ingest databases, files, and streaming data for real-time data replication and streaming analytics. Find and inventory all data assets throughout your organization. Intelligently discover and prepare trusted data for advanced analytics and AI/ML projects.

Streaming data from operations, transactions, sensors and IoT devices is valuable – when it's well-understood. Event stream processing from SAS includes streaming data quality and analytics – and a vast array of SAS and open source machine learning and high-frequency analytics for connecting, deciphering, cleansing and understanding streaming data – in one solution. No matter how fast your data moves, how much data you have, or how many data sources you’re pulling from, it’s all under your control via a single, intuitive interface. You can define patterns and address scenarios from all aspects of your business, giving you the power to stay agile and tackle issues as they arise.

Build professional applications to automate workflows, continuously monitor operations, and control processes in real-time. Your solutions run 24/7 on servers in the cloud and on the edge. Thanks to the spreadsheet user interface, you do not have to be a software developer. Instead of writing program code, you drag-and-drop data, fill cells with formulas, and design charts in a way you already know. Find all necessary protocols on board that you need to connect to sensors, and machines like MQTT, REST, and OPC UA. Streamsheets is native to stream data processing like MQTT and kafka. Pick up a topic stream, transform it and blast it back out into the endless streaming world. REST opens you the world, Streamsheets let you connect to any web service or let them connect to you. Streamsheets run in the cloud, on your servers, but also on edge devices like a Raspberry Pi.

Built on open-source Apache Kafka, IBM® Event Streams is an event-streaming platform that helps you build smart apps that can react to events as they happen. Event Streams is based on years of IBM operational expertise gained from running Apache Kafka event streams for enterprises. This makes Event Streams ideal for mission-critical workloads. With connectors to a wide range of core systems and a scalable REST API, you can extend the reach of your existing enterprise assets. Rich security and geo-replication aids disaster recovery. Take advantage of IBM productivity tools and use the CLI to ensure best practices. Replicate data between Event Streams deployments in a disaster-recovery situation.

Microservice-based streaming and batch data processing for Cloud Foundry and Kubernetes. Spring Cloud Data Flow provides tools to create complex topologies for streaming and batch data pipelines. The data pipelines consist of Spring Boot apps, built using the Spring Cloud Stream or Spring Cloud Task microservice frameworks. Spring Cloud Data Flow supports a range of data processing use cases, from ETL to import/export, event streaming, and predictive analytics. The Spring Cloud Data Flow server uses Spring Cloud Deployer, to deploy data pipelines made of Spring Cloud Stream or Spring Cloud Task applications onto modern platforms such as Cloud Foundry and Kubernetes. A selection of pre-built stream and task/batch starter apps for various data integration and processing scenarios facilitate learning and experimentation. Custom stream and task applications, targeting different middleware or data services, can be built using the familiar Spring Boot style programming model.

Spark Streaming brings Apache Spark's language-integrated API to stream processing, letting you write streaming jobs the same way you write batch jobs. It supports Java, Scala and Python. Spark Streaming recovers both lost work and operator state (e.g. sliding windows) out of the box, without any extra code on your part. By running on Spark, Spark Streaming lets you reuse the same code for batch processing, join streams against historical data, or run ad-hoc queries on stream state. Build powerful interactive applications, not just analytics. Spark Streaming is developed as part of Apache Spark. It thus gets tested and updated with each Spark release. You can run Spark Streaming on Spark's standalone cluster mode or other supported cluster resource managers. It also includes a local run mode for development. In production, Spark Streaming uses ZooKeeper and HDFS for high availability.

Heron is built with a wide array of architectural improvements that contribute to high-efficiency gains. Heron is API compatible with Apache Storm and hence no code change is required for migration. Easily debug and identify the issues in topologies, allowing faster iteration during development. Heron UI gives a visual overview of each topology to visualize hot spot locations and detailed counters for tracking progress and troubleshooting. Heron is highly scalable both in the ability to execute large number of components for each topology and the ability to launch and track large numbers of topologies.

InfinyOn has architected a programmable continuous intelligence platform for data in motion. Unlike other event streaming platforms that were built on Java, Infinyon Cloud is built on Rust and delivers industry leading scale and security for real-time applications. Ready to use programmable connectors that shape data events in real-time. Provision intelligent analytics pipelines that refine, protect, and correlate events in real-time. Attach programmable connectors to dispatch events and notify stakeholders. Each connector is either a source, which imports data, or a sink, which exports data. Connectors may be deployed in one of two ways: as a Managed Connector, in which the Fluvio cluster provisions and manages the connector; or as a Local Connector, in which you manually launch the connector as a docker container where you want it. Additionally, connectors conceptually have four stages, where each stage has distinct responsibilities.

We created Conduktor, the all-in-one friendly interface to work with the Apache Kafka ecosystem. Develop and manage Apache Kafka with confidence. With Conduktor DevTools, the all-in-one Apache Kafka desktop client. Develop and manage Apache Kafka with confidence, and save time for your entire team. Apache Kafka is hard to learn and to use. Made by Kafka lovers, Conduktor best-in-class user experience is loved by developers. Conduktor offers more than just an interface over Apache Kafka. It provides you and your teams the control of your whole data pipeline, thanks to our integration with most technologies around Apache Kafka. Provide you and your teams the most complete tool on top of Apache Kafka.

Akka is a toolkit for building highly concurrent, distributed, and resilient message-driven applications for Java and Scala. Akka Insights is intelligent monitoring and observability purpose-built for Akka. Actors and Streams let you build systems that scale up, using the resources of a server more efficiently, and out, using multiple servers. Building on the principles of The Reactive Manifesto Akka allows you to write systems that self-heal and stay responsive in the face of failures. Distributed systems without single points of failure. Load balancing and adaptive routing across nodes. Event Sourcing and CQRS with Cluster Sharding. Distributed Data for eventual consistency using CRDTs. Asynchronous non-blocking stream processing with backpressure. Fully async and streaming HTTP server and client provides a great platform for building microservices. Streaming integrations with Alpakka.

Red Hat® OpenShift® Streams for Apache Kafka is a managed cloud service that provides a streamlined developer experience for building, deploying, and scaling new cloud-native applications or modernizing existing systems. Red Hat OpenShift Streams for Apache Kafka makes it easy to create, discover, and connect to real-time data streams no matter where they are deployed. Streams are a key component for delivering event-driven and data analytics applications. The combination of seamless operations across distributed microservices, large data transfer volumes, and managed operations allows teams to focus on team strengths, speed up time to value, and lower operational costs. OpenShift Streams for Apache Kafka includes a Kafka ecosystem and is part of a family of cloud services—and the Red Hat OpenShift product family—which helps you build a wide range of data-driven solutions.

Superstream Is An AI-based Engine That Reduces Your Kafka Expenses And Boosts Its Performance by 75% Without Changing a Single Component or Your Existing Kafka!

Deliver Continuous Intelligence solutions easier, faster, and cost-effectively - with less engineering effort. The Cogility Cogynt platform delivers cloud-scalable event stream processing software powered by advanced, Expert AI-based analytics. A complete, integrated toolset enables organizations to quickly, easily, and more efficiently deliver continuous intelligence solutions. The end-to-end platform streamlines deployment, constructing model logic, customizing data source intake, processing data streams, examining, visualizing and sharing intelligence findings, auditing and improving results, and integrating with other applications. Cogynt’s Authoring Tool provides a convenient, zero-code design environment for creating, updating, and deploying data models. Cogynt’s Data Management Tool makes it easy to publish your model to immediately apply to stream data processing while abstracting Flink job coding.

Scale from zero to millions of events per second. Arroyo ships as a single, compact binary. Run locally on MacOS or Linux for development, and deploy to production with Docker or Kubernetes. Arroyo is a new kind of stream processing engine, built from the ground up to make real-time easier than batch. Arroyo was designed from the start so that anyone with SQL experience can build reliable, efficient, and correct streaming pipelines. Data scientists and engineers can build end-to-end real-time applications, models, and dashboards, without a separate team of streaming experts. Transform, filter, aggregate, and join data streams by writing SQL, with sub-second results. Your streaming pipelines shouldn't page someone just because Kubernetes decided to reschedule your pods. Arroyo is built to run in modern, elastic cloud environments, from simple container runtimes like Fargate to large, distributed deployments on the Kubernetes logo Kubernetes.

Unified stream and batch data processing that's serverless, fast, and cost-effective. Fully managed data processing service. Automated provisioning and management of processing resources. Horizontal autoscaling of worker resources to maximize resource utilization. OSS community-driven innovation with Apache Beam SDK. Reliable and consistent exactly-once processing. Streaming data analytics with speed. Dataflow enables fast, simplified streaming data pipeline development with lower data latency. Allow teams to focus on programming instead of managing server clusters as Dataflow’s serverless approach removes operational overhead from data engineering workloads. Allow teams to focus on programming instead of managing server clusters as Dataflow’s serverless approach removes operational overhead from data engineering workloads. Dataflow automates provisioning and management of processing resources to minimize latency and maximize utilization.

Cloudera DataFlow for the Public Cloud (CDF-PC) is a cloud-native universal data distribution service powered by Apache NiFi ​​that lets developers connect to any data source anywhere with any structure, process it, and deliver to any destination. CDF-PC offers a flow-based low-code development paradigm that aligns best with how developers design, develop, and test data distribution pipelines. With over 400+ connectors and processors across the ecosystem of hybrid cloud services—including data lakes, lakehouses, cloud warehouses, and on-premises sources—CDF-PC provides indiscriminate data distribution. These data distribution flows can then be version-controlled into a catalog where operators can self-serve deployments to different runtimes.

Radicalbit Natural Analytics (RNA) is a DataOps platform for Streaming Data Integration and Real-time Advanced Analytics. Choose the easiest way to deliver data at the right time in the right hands. RNA provides users with the latest technologies – in self service mode – for real-time data processing, taking advantage of Artificial Intelligence solutions for extracting value from data. It automates the labor-intensive process of data analysis and helps convey important findings and insights in understandable formats. Have a Real-time situational awareness and timely insights to respond quickly and appropriately. Achieve new levels of efficiency and optimization and guarantee collaboration between siloed teams. Manage and monitor the models from a centralized view, and deploy your evolving models in seconds. No downtime.

Integrate data seamlessly from legacy systems into next-gen cloud and data platforms with one solution. Connect helps you take control of your data from mainframe to cloud. Integrate data through batch and real-time ingestion for advanced analytics, comprehensive machine learning and seamless data migration. Connect leverages the expertise Precisely has built over decades as a leader in mainframe sort and IBM i data availability and security to lead the industry in accessing and integrating complex data. Access to all your enterprise data for the most critical business projects is ensured by support for a wide range of sources and targets for all your ELT and CDC needs.