Alternatives to Azure Event Hubs

Event Grid simplifies event-based apps. It is a single service that manages all events from any source to any destination. Event Grid is designed to be highly available, consistent in performance, and dynamically scale. This allows you to focus on your app logic, rather than infrastructure. Eliminate polling and the associated cost- and latency. Event Grid allows event publishers to be decoupled with event subscribers through a pub/sub model. This allows you to create scalable, serverless, microservices and distributed systems. You can gain massive scale dynamically while receiving near-real-time notifications about any changes that you are interested in. Reactive programming allows you to build better and more reliable applications, taking advantage of guaranteed event delivery and high availability in the cloud. Connect multiple sources and destinations of events to create richer applications.

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.

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.

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.

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.

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

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.

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.

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.

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.

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.

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.

You can analyze, query, and then act at lightning speed on IoT data and other streaming data. Intelligent applications allow you to take real-time operations and analytics up a notch with fast deployments that can be used to quickly take action based on new models and decisions. TIBCO®, Streaming software provides enterprise-grade streaming analytics that can be used in the cloud to quickly build real-time applications. It is much less expensive than other options and has a lower risk.

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.

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.

Apache Kafka®, is an open-source distributed streaming platform.

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.

Conduktor is the all-in one interface that allows you to interact with the Apache Kafka ecosystem. You can confidently develop and manage Apache Kafka. Conduktor DevTools is the all-in one Apache Kafka desktop client. You can manage Apache Kafka confidently and save time for your whole team. Apache Kafka can be difficult to learn and use. Conduktor is loved by developers for its best-in-class user interface. Conduktor is more than an interface for Apache Kafka. Conduktor gives you and your team control over your entire data pipeline thanks to its integration with many technologies around Apache Kafka. It gives you and your team the most comprehensive tool for Apache Kafka.

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.

It is difficult, costly, and risky to connect systems to scale AI projects. Pandio's cloud native managed solution simplifies data pipelines to harness AI's power. You can access your data from any location at any time to query, analyze, or drive to insight. Big data analytics without the high cost Enable data movement seamlessly. Streaming, queuing, and pub-sub with unparalleled throughput, latency and durability. In less than 30 minutes, you can design, train, deploy, and test machine learning models locally. Accelerate your journey to ML and democratize it across your organization. It doesn't take months or years of disappointment. Pandio's AI driven architecture automatically orchestrates all your models, data and ML tools. Pandio can be integrated with your existing stack to help you accelerate your ML efforts. Orchestrate your messages and models across your organization.

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.

IBM® Event Streams, an event-streaming platform built on Apache Kafka open-source software, is a smart app that reacts to events as they occur. Event Streams is based upon years of IBM operational experience running Apache Kafka stream events for enterprises. Event Streams is ideal for mission-critical workloads. You can extend the reach and reach of your enterprise assets by connecting to a variety of core systems and using a scalable RESTAPI. Disaster recovery is made easier by geo-replication and rich security. Use the CLI to take advantage of IBM productivity tools. Replicate data between Event Streams deployments during a disaster-recovery scenario.

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.

In-Memory Computing Platform. Digital world is different. Microseconds are important. The world's most important organizations rely on us for powering their most sensitive applications at scale. If they meet the current requirement for immediate access, new data-enabled apps can transform your business. Hazelcast solutions can be used to complement any database and deliver results that are much faster than traditional systems of record. Hazelcast's distributed architecture ensures redundancy and continuous cluster up-time, as well as always available data to support the most demanding applications. The capacity grows with demand without compromising performance and availability. The cloud delivers the fastest in-memory data grid and third-generation high speed event processing.

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.

You can manage your data from the edge to the cloud with a simple, no-code approach to creating sophisticated streaming applications.

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.

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.

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.

Cloud Foundry and Kubernetes support microservice-based streaming and batch processing. Spring Cloud Data Flow allows you to create complex topologies that can be used for streaming and batch data pipelines. The data pipelines are made up of Spring Boot apps that were built using the Spring Cloud Stream and Spring Cloud Task microservice frameworks. Spring Cloud Data Flow supports a variety of data processing use cases including ETL, import/export, event streaming and predictive analytics. Spring Cloud Data Flow server uses Spring Cloud Deployer to deploy data pipelines made from Spring Cloud Stream and Spring Cloud Task applications onto modern platforms like Cloud Foundry or Kubernetes. Pre-built stream and task/batch starter applications for different data integration and processing scenarios allow for experimentation and learning. You can create custom stream and task apps that target different middleware or services using the Spring Boot programming model.

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.

Many components are required to build real-time apps or services. These components include Kafka and VPC hosting, infrastructure code, container orchestration and observability. The Quix platform handles all the moving parts. Connect your data and get started building. That's it. There are no provisioning clusters nor configuring resources. You can use Quix connectors for ingesting transaction messages from your financial processing system in a virtual private clouds or on-premise data centers. For security and efficiency, all data in transit is encrypted from the beginning and compressed using Protobuf and G-Zip. Machine learning models and rule-based algorithms can detect fraudulent patterns. You can display fraud warning messages in support dashboards or as troubleshooting tickets.

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.

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.

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.

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.

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.

RudderStack is the smart customer information pipeline. You can easily build pipelines that connect your entire customer data stack. Then, make them smarter by pulling data from your data warehouse to trigger enrichment in customer tools for identity sewing and other advanced uses cases. Start building smarter customer data pipelines today.

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.

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.

Akka is a toolkit that allows you to build highly concurrent, distributed and resilient message-driven Java and Scala applications. Akka Insights, an intelligent monitoring and observability tool, is specifically designed for Akka. Actors and streams allow you to build systems that scale up by using more server resources and out by using multiple servers. You can build systems that self-heal and remain responsive to failures by using the principles of The Reactive Manifesto Akka. Distributed systems that are resilient to failure. Load balancing across nodes and adaptive routing. Cluster Sharding is used for event sourcing and CQRS. Distributed Data to ensure eventual consistency with CRDTs Backpressure and asynchronous stream processing. A great platform for microservice development is the fully async streaming HTTP server and client. Alpakka streams integrations.

For AI and cloud analytics, you can ingest, prepare, or process data pipelines at large scale. Informatica's extensive data engineering portfolio includes everything you need to process big data engineering workloads for AI and analytics. This includes robust data integration, streamlining, masking, data preparation, and data quality.

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.

You can deliver customer experiences like never before with breakthrough data streaming capabilities Both the ecosystem and Kafka API are compatible. Redpanda BulletPredictable low latency with zero data loss. Redpanda BulletUp to 10x faster than Kafka Redpanda BulletEnterprise-grade support and hotfixes. Redpanda BulletAutomated backups for S3/GCS. Redpanda Bullet100% freedom of routine Kafka operations. Redpanda BulletSupports for AWS/GCP. Redpanda was built from the ground up to be easy to install and get running quickly. Redpanda's power will be evident once you have tried it in production. You can use the more advanced Redpanda functions. We manage all aspects of provisioning, monitoring, as well as upgrades. We do not have access to your cloud credentials. Sensitive data never leaves your environment. You can have it provisioned, operated, maintained, and updated for you. Configurable instance types. As your needs change, you can expand the cluster.

Spectra is a DataOps platform that allows you to create and manage complex data pipelines. It uses a low-code user interface and domain-specific features to deliver data solutions quickly and efficiently. Maximize your ROI by reducing costs and achieving faster time-to market and time-to value. Access to more than 50 native connectors that provide data processing functions like sort, lookup, join, transform and grouping. You can process structured, semi-structured and unstructured data in batch, or real-time streaming data. Managing data processing and pipeline efficiently will help you optimize and control your infrastructure spending. Spectra's pushdown capabilities with Snowflake Data Cloud enable enterprises to take advantage of Snowflake's high performance processing power and scalable architecture.

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.

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.

Lightbend technology allows developers to quickly build data-centric applications that can handle the most complex, distributed applications and streaming data streams. Lightbend is used by companies around the world to address the problems of distributed, real-time data to support their most important business initiatives. Akka Platform is a platform that makes it easy for businesses build, deploy, manage, and maintain large-scale applications that support digitally transformational initiatives. Reactive microservices are a way to accelerate time-to-value, reduce infrastructure costs, and lower cloud costs. They take full advantage the distributed nature cloud and are highly efficient, resilient to failure, and able to operate at any scale. Native support for encryption, data destruction, TLS enforcement and compliance with GDPR. Framework to quickly build, deploy and manage streaming data pipelines.

Apache Flink is a distributed processing engine and framework for stateful computations using unbounded and bounded data streams. Flink can be used in all cluster environments and perform computations at any scale and in-memory speed. A stream of events can be used to produce any type of data. All data, including credit card transactions, machine logs, sensor measurements, and user interactions on a website, mobile app, are generated as streams. Apache Flink excels in processing both unbounded and bound data sets. Flink's runtime can run any type of application on unbounded stream streams thanks to its precise control of state and time. Bounded streams are internal processed by algorithms and data structure that are specifically designed to process fixed-sized data sets. This results in excellent performance. Flink can be used with all of the resource managers previously mentioned.

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.