Alternatives to TIBCO Streaming

Azure Stream Analytics is an easy-to-use, real time analytics service that's designed for mission-critical workloads. In just a few steps, you can create an end-to-end streaming pipeline that is serverless in just a few clicks. SQL--easily extensible and customizable with custom code, built-in machine learning capabilities and more advanced scenarios. You can run the most complex workloads with confidence knowing that your SLA is financially backed.

Data integration for hybrid clouds Modern, reliable data integration across both your private cloud and public cloud. All this in real-time, with change data capture and streams. Striim was developed by the executive and technical team at GoldenGate Software. They have decades of experience in mission critical enterprise workloads. Striim can be deployed in your environment as a distributed platform or in the cloud. Your team can easily adjust the scaleability of Striim. Striim is fully secured with HIPAA compliance and GDPR compliance. Built from the ground up to support modern enterprise workloads, whether they are hosted in the cloud or on-premise. Drag and drop to create data flows among your sources and targets. Real-time SQL queries allow you to process, enrich, and analyze streaming data.

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

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 Cloudera DataFlow, Confluent, and DeltaStream.

AI-powered Informatica Data Engineering streaming allows data engineers to ingest and process real-time streaming data in order to gain actionable insights.

Cumulocity IoT, the #1 low-code, self service IoT platform, is pre-integrated and includes all the tools you need to get fast results: device connectivity, management, application enablement, integration, streaming, and predictive analytics. Your business can no longer depend on proprietary technology. You can connect any "thing" to the IoT platform because it is completely open. You can bring your own hardware and tools and choose the components that fit you best. In minutes, you can be up and running with the IoT. Connect a device to view its data. Create a real-time interactive dashboard. You can create rules to monitor and respond to events. All of this can be done without requiring IT or writing code. You can easily integrate new IoT data into the core enterprise systems, apps and processes that have been running your business for years, again without having to code - for a fluid flow data. You will have more context to make smarter decisions.

In the field of IoT stream processing and analytics, SQLstream ranks #1 according to ABI Research. Used by Verizon, Walmart, Cisco, and Amazon, our technology powers applications on premises, in the cloud, and at the edge. SQLstream enables time-critical alerts, live dashboards, and real-time action with sub-millisecond latency. Smart cities can reroute ambulances and fire trucks or optimize traffic light timing based on real-time conditions. Security systems can detect hackers and fraudsters, shutting them down right away. AI / ML models, trained with streaming sensor data, can predict equipment failures. Thanks to SQLstream's lightning performance -- up to 13 million rows / second / CPU core -- companies have drastically reduced their footprint and cost. Our efficient, in-memory processing allows operations at the edge that would otherwise be impossible. Acquire, prepare, analyze, and act on data in any format from any source. Create pipelines in minutes not months with StreamLab, our interactive, low-code, GUI dev environment. Edit scripts instantly and view instantaneous results without compiling. Deploy with native Kubernetes support. Easy installation includes Docker, AWS, Azure, Linux, VMWare, and more

Apache Kafka®, with Confluent, has an infinite retention. Be infrastructure-enabled, not infrastructure-restricted Legacy technologies require you to choose between being real-time or highly-scalable. Event streaming allows you to innovate and win by being both highly-scalable and real-time. Ever wonder how your rideshare app analyses massive amounts of data from multiple sources in order to calculate real-time ETA. Wondering how your credit card company analyzes credit card transactions from all over the world and sends fraud notifications in real time? Event streaming is the answer. Microservices are the future. A persistent bridge to the cloud can enable your hybrid strategy. Break down silos to demonstrate compliance. Gain real-time, persistent event transport. There are many other options.

Oracle Stream Analytics makes it possible to analyze and process large amounts of real-time data using complex correlation patterns, enrichment and machine learning. It provides real-time, actionable business insight from streaming data and automates actions to drive agile businesses of today.

IBM Streams analyzes a wide range of streaming data, including unstructured text, video and audio, and geospatial and sensor data. This helps organizations to spot opportunities and risks, and make decisions in real-time.

Streaming data from operations and transactions is valuable when it is well-understood. SAS Event stream processing includes streaming data quality, analytics, and a vast array SAS and open-source machine learning and high frequency analytics for connecting to, deciphering and cleansing streaming data. It doesn't matter how fast your data moves or how many sources you pull from, all of it is under your control through a single, intuitive interface. You can create patterns and address situations from any aspect of your business, giving the ability to be agile and deal with issues as they arise.

Tealium EventStream is a lightweight data collection solution that can be used on mobile, IoT, and connected devices. It can also be used on desktop and the web for those who need to work efficiently. It allows you to easily connect all of your cloud-based (server side) data to one central hub that can be used to orchestrate customer experience data.

Allow everyone to view and discover streaming data. Up to 95% of productivity can be increased by sharing, documenting, and cataloging data. Next, create apps for production use cases using the data. To address privacy concerns and cover all the gaps in open source technology, apply a data-centric security approach. Secure and low-code data pipeline capabilities. All darkness is eliminated and data and apps can be viewed with unparalleled visibility. Unify your data technologies and data meshes and feel confident using open source production. Independent third-party reviews have rated Lenses the best product for real time stream analytics. We have built features to allow you to focus on what is driving value from real-time data. This was based on feedback from our community as well as thousands of engineering hours. You can deploy and run SQL-based real-time applications over any Kafka Connect, Kubernetes or Kubernetes infrastructure, including AWS EKS.

You can quickly collect, process, analyze, and analyze video and data streams. Amazon Kinesis makes it easy for you to quickly and easily collect, process, analyze, and interpret streaming data. Amazon Kinesis provides key capabilities to process streaming data at any scale cost-effectively, as well as the flexibility to select the tools that best fit your application's requirements. Amazon Kinesis allows you to ingest real-time data, including video, audio, website clickstreams, application logs, and IoT data for machine learning, analytics, or other purposes. Amazon Kinesis allows you to instantly process and analyze data, rather than waiting for all the data to be collected before processing can begin. Amazon Kinesis allows you to ingest buffer and process streaming data instantly, so you can get insights in seconds or minutes, instead of waiting for hours or days.

Amazon MSK is a fully managed service that makes coding and running applications that use Apache Kafka for streaming data processing easy. Apache Kafka is an open source platform that allows you to build real-time streaming data applications and pipelines. Amazon MSK allows you to use native Apache Kafka APIs for populating data lakes, stream changes between databases, and to power machine learning or analytics applications. It is difficult to set up, scale, and manage Apache Kafka clusters in production. Apache Kafka clusters can be difficult to set up and scale on your own.

Digital businesses need to design applications that enable them to be proactive, not reactive. This requires the ability of processing large amounts of data in real-time to identify meaningful events and allow for the business to influence the outcome. TIBCO Cloud™, Events service is a cloud-native tool for improving business results by detecting key events, and automating the next most effective action. You can create declarative rules without having to worry about the plumbing. Identify and capture key business conditions and automate actions. The execution and matching of relevant data is handled by TIBCO Cloud Event service.

Unified stream and batch data processing that is serverless, fast, cost-effective, and low-cost. Fully managed data processing service. Automated provisioning of and management of processing resource. Horizontal autoscaling worker resources to maximize resource use Apache Beam SDK is an open-source platform for community-driven innovation. Reliable, consistent processing that works exactly once. Streaming data analytics at lightning speed Dataflow allows for faster, simpler streaming data pipeline development and lower data latency. Dataflow's serverless approach eliminates the operational overhead associated with data engineering workloads. Dataflow allows teams to concentrate on programming and not managing server clusters. Dataflow's serverless approach eliminates operational overhead from data engineering workloads, allowing teams to concentrate on programming and not managing server clusters. Dataflow automates provisioning, management, and utilization of processing resources to minimize latency.

DeltaStream is an integrated serverless streaming processing platform that integrates seamlessly with streaming storage services. Imagine it as a compute layer on top your streaming storage. It offers streaming databases and streaming analytics along with other features to provide an integrated platform for managing, processing, securing and sharing streaming data. DeltaStream has a SQL-based interface that allows you to easily create stream processing apps such as streaming pipelines. It uses Apache Flink, a pluggable stream processing engine. DeltaStream is much more than a query-processing layer on top Kafka or Kinesis. It brings relational databases concepts to the world of data streaming, including namespacing, role-based access control, and enables you to securely access and process your streaming data, regardless of where it is stored.

The digital age will see billions of people, devices, and systems interact in real time, creating new and disruptive competitive advantages. How can you play there? You can experiment, learn, and rapidly evolve by building distributed, stateful, rule based event-processing platforms. Data is constantly arriving from hundreds of sources, both internal and external. It has a shelf-life and its value decreases over time. TIBCO allows you to jump-start big data processing projects that allow you to sense, reason and respond. This is a different approach than the traditional store analysis, report, act approach. Multiple rule authoring environments allow for collaboration between IT professionals and business professionals.

Streaming service is a streaming service that allows developers and data scientists to stream real-time events. It is serverless and Apache Kafka compatible. Streaming can be integrated with Oracle Cloud Infrastructure, Database, GoldenGate, Integration Cloud, and Oracle Cloud Infrastructure (OCI). The service provides integrations for hundreds third-party products, including databases, big data, DevOps, and SaaS applications. Data engineers can easily create and manage big data pipelines. Oracle manages all infrastructure and platform management, including provisioning, scaling and security patching. Streaming can provide state management to thousands of consumers with the help of consumer groups. This allows developers to easily create applications on a large scale.

Event Hubs is a fully managed, real time data ingestion service that is simple, reliable, and scalable. Stream millions of events per minute from any source to create dynamic data pipelines that can be used to respond to business problems. Use the geo-disaster recovery or geo-replication features to continue processing data in emergencies. Integrate seamlessly with Azure services to unlock valuable insights. You can allow existing Apache Kafka clients to talk to Event Hubs with no code changes. This allows you to have a managed Kafka experience, without the need to manage your own clusters. You can experience real-time data input and microbatching in the same stream. Instead of worrying about infrastructure management, focus on gaining insights from your data. Real-time big data pipelines are built to address business challenges immediately.

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

Solace is a specialist in Event-Driven-Architecture (EDA), with two decades of experience providing enterprises with highly reliable, robust and scalable data movement technology based on the publish & subscribe (pub/sub) pattern. Solace technology enables the real-time data flow behind many of the conveniences you take for granted every day such as immediate loyalty rewards from your credit card, the weather data delivered to your mobile phone, real-time airplane movements on the ground and in the air, and timely inventory updates to some of your favourite department stores and grocery chains, not to mention that Solace technology also powers many of the world's leading stock exchanges and betting houses. Aside from rock solid technology, stellar customer support is one of the biggest reasons customers select Solace, and stick with them.

StreamSets DataOps Platform. An end-to-end data integration platform to build, run, monitor and manage smart data pipelines that deliver continuous data for DataOps.

ScaleOut Digital Twin Streaming Service™ Easily create and deploy real-time twins for streaming analytics Connect with many data sources with Azure & AWS IoT Hubs, Kafka, etc. Maximize situational awareness through live, aggregate analytics. A breakthrough cloud service that simultaneously tracks telemetry across millions of data sources, with "real-time digital twins" -- enabling deep, immediate introspection and state-tracking for thousands of devices. The powerful UI makes deployment easy and displays aggregate analytics in real-time to maximize situational awareness. Ideal for a wide variety of applications, including the Internet of Things, real-time intelligent monitoring and logistics, financial services, and financial services. Simple pricing makes it easy to get started. The ScaleOut Digital Twin Builder software and ScaleOut Digital Twin Streaming Service enable the next generation of stream processing.

InfinyOn has created a programmable continuous Intelligence platform for data in motion. Infinyon Cloud, unlike other event streaming platforms built on Java is built on Rust. It delivers industry-leading scale and security for real time applications. Ready-to-use programmable connectors to shape data events in real time. Intelligent analytics pipelines can be created that automatically refine, protect, and corroborate events. To notify stakeholders and dispatch events, attach programmable connectors. Each connector can be used to either import or export data. Connectors can be deployed in one way: as a Managed Connector in which Fluvio cluster provision and manages the connector, or as a local connector in which you manually launch it as a Docker container wherever you want it. Connectors are conceptually divided into four stages, each with its own responsibilities.

Azure Data Explorer provides fast, fully managed data analytics services for real-time analysis of large amounts of data streaming from websites, applications, IoT devices, etc. Ask questions and iteratively analyze data on the fly to improve products and customer experiences, monitor devices, boost operations, and increase profits. Identify patterns, anomalies, or trends quickly in your data. Find answers to your questions quickly and easily by exploring new topics. The optimized cost structure allows you to run as many queries as needed. You can explore new possibilities with your data efficiently. With the fully managed, easy-to-use data analytics service, you can focus on insights and not infrastructure. Rapidly respond to rapidly changing and fast-flowing data. Azure Data Explorer simplifies analytics for all types of streaming data.

KX Streaming Analytics allows you to ingest and store historical and time series data. This data can then be processed, stored, processed, and analyzed instantly to provide analytics, insights, or visualizations. The platform offers the complete lifecycle of data services to ensure that your applications and users can be productive quickly. This includes query processing, query processing, tiering and migration, archiving and data protection. Our advanced analytics and visualization tools are widely used in finance and industry. They allow you to create and execute queries, calculations, aggregations and machine learning on any streaming or historical data. Data can be used across multiple hardware environments and can come from high-volume sources such as clickstreams, radio frequency identification, GPS systems and social networking sites.

Real-time analytics on raw data. Live ingest from S3, DynamoDB, DynamoDB and more. Raw data can be accessed as SQL tables. In minutes, you can create amazing data-driven apps and live dashboards. Rockset is a serverless analytics and search engine that powers real-time applications and live dashboards. You can directly work with raw data such as JSON, XML and CSV. Rockset can import data from real-time streams and data lakes, data warehouses, and databases. You can import real-time data without the need to build pipelines. Rockset syncs all new data as it arrives in your data sources, without the need to create a fixed schema. You can use familiar SQL, including filters, joins, and aggregations. Rockset automatically indexes every field in your data, making it lightning fast. Fast queries are used to power your apps, microservices and live dashboards. Scale without worrying too much about servers, shards or pagers.

The only platform that can handle all aspects of data pipeline. Gathr was built from the ground up to support a cloud-first world. It is the only platform that can handle all your data integration needs - ingestion and ETL, ELT and CDC, streaming analytics and data preparation, machine-learning, advanced analytics, and more. Gathr makes it easy for anyone to build and deploy pipelines, regardless of their skill level. Ingestion pipelines can be created in minutes and not weeks. You can access data from any source and deliver it to any destination. A wizard-based approach allows you to quickly build applications. A templatized CDC app allows you to replicate data in real time. Native integration for all sources. All the capabilities you need to succeed today or tomorrow. You can choose between pay-per-use, free, or customized according to your needs.

Radicalbit Natural Analytics is a DataOps platform that enables Streaming Data Integration as well as Real-time Advanced Analytics. The easiest way to get data to the right people at the right time is the best. RNA offers users the latest technologies in self-service mode. It allows for real-time data processing and takes advantage of Artificial Intelligence solutions to extract value from data. It automates data analysis, which can be laborious. It also helps to communicate important insights and findings in easily understandable formats. You can respond quickly and effectively with real-time situational awareness. You can achieve new levels of efficiency, optimization, and ensure collaboration between siloed groups. You can monitor and manage your models from one central view. Then, deploy your evolving models in seconds. No downtime.

Red Hat®, OpenShift®, Streams for Apache Kafka provides a simplified developer experience for building, scaling, and modernizing cloud-native apps or upgrading existing systems. Red Hat OpenShift streams for Apache Kafka make it easy to create, discover and connect to real-time data stream no matter where they're deployed. Streams are essential for delivering event-driven or data analytics applications. The seamless operation of distributed microservices, large data transfers volumes, and managed operations allow teams to focus on their strengths, speed up value, and lower operating costs. OpenShift streams for Apache Kafka is part of the Red Hat OpenShift product range, which allows you to build a wide variety of data-driven solutions.

High-performing applications need real-time information exchange. This is exactly what TIBCO Cloud™, Messaging software offers. We offer multiple options including Apache Kafka and Apache Pulsar, TIBCO Enterprise Message Services™, TIBCO FLL® or TIBCO eFTL™ software. Whether you need event-driven application integration, high-performance, low latency messaging, connections for web apps and backend systems, or IoT integration, the simple yet robust TIBCO cloud messaging client API and cloud distribution network are the best options. TIBCO Cloud Messaging software offers fault tolerance, multi-zone reliability, and scalable performances. It allows you to concentrate on your application logic and not have to worry about infrastructure or containers being deployed for your event streams. Connect your apps to the API to immediately publish and subscribe to event messages.

IBM Cloud Pak For Integration®, a hybrid integration platform, is an automated, closed-loop system that supports multiple styles and types of integration in a single, unified experience. Connect cloud and on-premise apps to unlock business data and assets, securely move data with enterprise messaging, deliver event interactions, transfer data across all clouds, and deploy and scale with shared foundational services and cloud-native architecture. All this is done with enterprise-grade encryption and security. Automated, closed-loop, and multi-style integrations deliver the best results. Targeted innovations can be used to automate integrations. These include natural language-powered flows, AI-assisted maps and RPA. You can also use company-specific operational information to continuously improve integrations and API test generation. Workload balancing can also be achieved.

Apama Streaming Analytics enables organizations to analyze and respond to IoT and fast moving data in real time, allowing them to react intelligently to events as they occur. Apama Community Edition by Software AG is a freemium version that allows users to learn about, develop, and implement streaming analytics applications. Software AG Data & Analytics Platform offers an integrated, modular and end-to-end set of world-class capabilities that are optimized for high-speed data management. It also provides connectivity and integration to all major enterprise data sources. You can choose the capabilities that you require: streaming, predictive, and visual analytics. There is also messaging and integration with other enterprise applications. You can integrate historical and other data to create models and enrich customer data.

Materialize is a reactive database that provides incremental view updates. Our standard SQL allows developers to easily work with streaming data. Materialize connects to many external data sources without any pre-processing. Connect directly to streaming sources such as Kafka, Postgres databases and CDC or historical data sources such as files or S3. Materialize allows you to query, join, and transform data sources in standard SQL - and presents the results as incrementally-updated Materialized views. Queries are kept current and updated as new data streams are added. With incrementally-updated views, developers can easily build data visualizations or real-time applications. It is as easy as writing a few lines SQL to build with streaming data.

KX Insights, a cloud-native platform that provides critical real-time performance as well as continuous actionable intelligence, is available. It enables rapid decision-making and automated responses to incidents by combining complex event processing, high speed analytics, and machine learning interfaces. Cloud computing is not just about storage and compute elasticity. It encompasses everything: data and tools, development, security, connectivity as well as operations and maintenance. KX can help you harness that power to make better, more informed decisions by integrating real time analytics into your business operations. KX Insights uses industry standards to ensure interoperability and openness with other technologies to deliver insights faster, more cost-effectively. It uses microservices to capture, store, and process high-volume, high velocity data using cloud protocols, services, and standards.

Responsive apps keep developers motivated and users engaged. With the DataStax Astra streaming service platform, you can meet these ever-increasing demands. DataStax Astra Streaming, powered by Apache Pulsar, is a cloud-native messaging platform and event streaming platform. Astra Streaming lets you build streaming applications on top a multi-cloud, elastically scalable and event streaming platform. Apache Pulsar is the next-generation event streaming platform that powers Astra Streaming. It provides a unified solution to streaming, queuing and stream processing. Astra Streaming complements Astra DB. Astra Streaming allows existing Astra DB users to easily create real-time data pipelines from and to their Astra DB instances. Astra Streaming allows you to avoid vendor lock-in by deploying on any major public cloud (AWS, GCP or Azure) compatible with open source Apache Pulsar.

Apache Kafka is a fully managed service that offers zero vendor lock-in, as well as all the capabilities you need to build your streaming infrastructure. You can easily set up fully managed Kafka within 10 minutes using our web console, or programmatically through our API, CLI or Terraform provider. Connect it to your existing tech stack using over 30 connectors. You can feel confident in your setup thanks to the service integrations that provide logs and metrics. Fully managed distributed data streaming platform that can be deployed in any cloud. Event-driven applications, near real-time data transfer and pipelines and stream analytics are all possible uses for this platform. Aiven's Apache Kafka is hosted and managed for you. You can create clusters, migrate clouds, upgrade versions, and deploy new nodes all with a single click. All this and more through a simple dashboard.

Upsolver makes it easy to create a governed data lake, manage, integrate, and prepare streaming data for analysis. Only use auto-generated schema on-read SQL to create pipelines. A visual IDE that makes it easy to build pipelines. Add Upserts to data lake tables. Mix streaming and large-scale batch data. Automated schema evolution and reprocessing of previous state. Automated orchestration of pipelines (no Dags). Fully-managed execution at scale Strong consistency guarantee over object storage Nearly zero maintenance overhead for analytics-ready information. Integral hygiene for data lake tables, including columnar formats, partitioning and compaction, as well as vacuuming. Low cost, 100,000 events per second (billions every day) Continuous lock-free compaction to eliminate the "small file" problem. Parquet-based tables are ideal for quick queries.

Evam's Continuous Intelligence Platform is a combination of multiple products that process and visualize real-time data. It can run real-time machine-learning models on streaming data and enrich the real-time data using smart in-memory cache.

One Platform for Realtime Communication: A platform to build and operate real-time interactivity for web, mobile, AI/ML, IoT, and Edge computing applications Faster & Easier Deployments: SDK support for 50+ mobile, web, server, and IoT environments (PubNub & community supported) and more than 65 pre-built integrations with external and third-party APIs to give you the features you need regardless of programming language or tech stack. Scalability: The industry’s most scalable platform capable of supporting millions of concurrent users for rapid growth with low latency, high uptime, and without financial penalties.

BlackLynx accelerators provide analytics power where it is needed, without the need for specialized skills. No matter what analytics ecosystem you have, you can power data-driven businesses with powerful, easy to use heterogeneous computing.

Spark Streaming uses Apache Spark's language-integrated API for stream processing. It allows you to write streaming jobs in the same way as you write batch jobs. It supports Java, Scala, and Python. Spark Streaming recovers lost work as well as operator state (e.g. Without any additional code, Spark Streaming recovers both lost work and operator state (e.g. sliding windows) right out of the box. Spark Streaming allows you to reuse the same code for batch processing and join streams against historical data. You can also run ad-hoc queries about stream state by running on Spark. Spark Streaming allows you to create interactive applications that go beyond analytics. Apache Spark includes Spark Streaming. It is updated with every Spark release. Spark Streaming can be run on Spark's standalone mode or other supported cluster resource mangers. It also has a local run mode that can be used for development. Spark Streaming uses ZooKeeper for high availability in production.

Scalable Python framework designed to build real-time intelligent applications, data pipelines, and integrate AI/ML models

Google Cloud Pub/Sub: Delivery of messages in large quantities with push and pull modes. Auto-scaling, auto-provisioning, support from zero to hundreds GB/second Independent quota and billing are available for subscribers and publishers. Multi-region systems can be simplified by global message routing High availability made easy: Ensure reliable delivery at all scales with synchronous, cross-zone message replication. Auto-everything, no-planning Auto-scaling, auto-provisioning without partitions eliminates the need for planning and ensures that workloads are ready for production from day one. Advanced features built in: Filtering, dead letter delivery, and exponential backoff all help to simplify your applications

Integrate legacy systems seamlessly into the next-gen cloud or data platforms with one solution. Connect allows you to take control of your data, from mainframe to cloud. Integrate data via batch and real-time input for advanced analytics, comprehensive machinelearning and seamless data migration. Connect draws on the decades of experience Precisely has gained as a leader in mainframe sorting and IBM i data availability security. This allows the company to be a leader in the field of complex data access and integration. Access to all enterprise data is possible for critical business projects. Connect supports a wide range targets and sources for all your ELT/CDC needs.

Professional applications can be built to automate workflows, monitor operations continuously, and control processes in real time. Your solutions can run 24/7 on servers at the edge and in the cloud. The spreadsheet user interface makes it easy to create software without being a programmer. Instead of writing program code you can drag-and-drop data and fill cells with formulas to create charts in a way that you already know. You will find all the protocols you need to connect sensors and machines such as MQTT, OPC UA, and REST on board. Streamsheets is a native stream data processing tool like MQTT or kafka. You can grab a topic stream and transform it to broadcast it out into the endless streaming universe. REST gives you access to the world. Streamsheets allow you to connect to any web service, or let them connect to your site. Streamsheets can be run on your servers in the cloud, on your edge devices, or on your Raspberry Pi.

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

The Open, Multi-Cloud Stack to Modern Data Apps. Built on Apache Cassandra™, an open-source Apache Cassandra™. Global scale and 100% uptime without vendor lock in You can deploy on multi-clouds, open-source, on-prem and Kubernetes. For a lower TCO, use elastic and pay-as you-go. Stargate APIs allow you to build faster with NoSQL, reactive, JSON and REST. Avoid the complexity of multiple OSS projects or APIs that don’t scale. It is ideal for commerce, mobile and AI/ML. Get building modern data applications with Astra, a database-as-a-service powered by Apache Cassandra™. Richly interactive apps that are viral-ready and elastic using REST, GraphQL and JSON. Pay-as you-go Apache Cassandra DBaaS which scales easily and affordably