Alternatives to Lightstreamer

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.

StarTree Cloud is a fully-managed real-time analytics platform designed for OLAP at massive speed and scale for user-facing applications. Powered by Apache Pinot, StarTree Cloud provides enterprise-grade reliability and advanced capabilities such as tiered storage, scalable upserts, 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.

Amazon EventBridge serves as a serverless event bus that simplifies the integration of applications by utilizing data from your own systems, various Software-as-a-Service (SaaS) offerings, and AWS services. It provides a continuous flow of real-time data from event sources like Zendesk, Datadog, and PagerDuty, efficiently directing that information to targets such as AWS Lambda. By establishing routing rules, you can dictate the destination of your data, enabling the creation of application architectures that respond instantaneously to all incoming data sources. EventBridge facilitates the development of event-driven applications by managing essential aspects like event ingestion, delivery, security, authorization, and error handling on your behalf. As your applications grow increasingly interconnected through events, you may find that greater effort is required to discover and comprehend the structure of these events in order to effectively code responses to them. This can enhance the overall efficiency and responsiveness of your application ecosystem.

EMQX is the world's most scalable and reliable MQTT messaging platform designed by EMQ. It supports 100M concurrent IoT device connections per cluster while maintaining extremely high throughput and sub-millisecond latency. EMQX boasts more than 20,000 global users from over 50 countries, connecting more than 100M IoT devices worldwide, and is trusted by over 300 customers in mission-critical IoT scenarios, including well-known brands like HPE, VMware, Verifone, SAIC Volkswagen, and Ericsson. Our edge-to-cloud IoT data solutions are flexible to meet the demands of various industries towards digital transformation, including connected vehicles, Industrial IoT, oil & gas, carrier, finance, smart energy, and smart cities. EMQX Enterprise: The World’s # 1 Scalable MQTT Messaging Platform -100M concurrent MQTT connections -1M/s messages throughput under 1ms latency -Business-critical reliability, Up to 99.99% SLA -Integrate IoT data seamlessly with over 40 cloud services and enterprise systems EMQX Cloud: Fully Managed MQTT Service for IoT - Scale as you need, pay as you go - Flexible and rich IoT data integration up to 40+ choices - Run in 19 regions across AWS, GCP, and Microsoft Azure - 100% MQTT

Apache Kafka® is a robust, open-source platform designed for distributed streaming. It can scale production environments to accommodate up to a thousand brokers, handling trillions of messages daily and managing petabytes of data with hundreds of thousands of partitions. The system allows for elastic growth and reduction of both storage and processing capabilities. Furthermore, it enables efficient cluster expansion across availability zones or facilitates the interconnection of distinct clusters across various geographic locations. Users can process event streams through features such as joins, aggregations, filters, transformations, and more, all while utilizing event-time and exactly-once processing guarantees. Kafka's built-in Connect interface seamlessly integrates with a wide range of event sources and sinks, including Postgres, JMS, Elasticsearch, AWS S3, among others. Additionally, developers can read, write, and manipulate event streams using a diverse selection of programming languages, enhancing the platform's versatility and accessibility. This extensive support for various integrations and programming environments makes Kafka a powerful tool for modern data architectures.

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.

Achieve limitless data retention for Apache Kafka® with Confluent, empowering you to be infrastructure-enabled rather than constrained by outdated systems. Traditional technologies often force a choice between real-time processing and scalability, but event streaming allows you to harness both advantages simultaneously, paving the way for innovation and success. Have you ever considered how your rideshare application effortlessly analyzes vast datasets from various sources to provide real-time estimated arrival times? Or how your credit card provider monitors millions of transactions worldwide, promptly alerting users to potential fraud? The key to these capabilities lies in event streaming. Transition to microservices and facilitate your hybrid approach with a reliable connection to the cloud. Eliminate silos to ensure compliance and enjoy continuous, real-time event delivery. The possibilities truly are limitless, and the potential for growth is unprecedented.

IBM Event Streams is a comprehensive event streaming service based on Apache Kafka, aimed at assisting businesses in managing and reacting to real-time data flows. It offers features such as machine learning integration, high availability, and secure deployment in the cloud, empowering organizations to develop smart applications that respond to events in real time. The platform is designed to accommodate multi-cloud infrastructures, disaster recovery options, and geo-replication, making it particularly suitable for critical operational tasks. By facilitating the construction and scaling of real-time, event-driven solutions, IBM Event Streams ensures that data is processed with speed and efficiency, ultimately enhancing business agility and responsiveness. As a result, organizations can harness the power of real-time data to drive innovation and improve decision-making processes.

Aiven takes the reins on your open-source data infrastructure hosted in the cloud, allowing you to focus on what you excel at: developing applications. While you channel your energy into innovation, we expertly handle the complexities of managing cloud data infrastructure. Our solutions are entirely open source, providing the flexibility to transfer data between various clouds or establish multi-cloud setups. You will have complete visibility into your expenses, with a clear understanding of costs as we consolidate networking, storage, and basic support fees. Our dedication to ensuring your Aiven software remains operational is unwavering; should any challenges arise, you can count on us to resolve them promptly. You can launch a service on the Aiven platform in just 10 minutes and sign up without needing to provide credit card information. Simply select your desired open-source service along with the cloud and region for deployment, pick a suitable plan—which includes $300 in free credits—and hit "Create service" to begin configuring your data sources. Enjoy the benefits of maintaining control over your data while leveraging robust open-source services tailored to your needs. With Aiven, you can streamline your cloud operations and focus on driving your projects forward.

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

StreamNative transforms the landscape of streaming infrastructure by combining Kafka, MQ, and various other protocols into one cohesive platform, which offers unmatched flexibility and efficiency tailored for contemporary data processing requirements. This integrated solution caters to the varied demands of streaming and messaging within microservices architectures. By delivering a holistic and intelligent approach to both messaging and streaming, StreamNative equips organizations with the tools to effectively manage the challenges and scalability of today’s complex data environment. Furthermore, Apache Pulsar’s distinctive architecture separates the message serving component from the message storage segment, creating a robust cloud-native data-streaming platform. This architecture is designed to be both scalable and elastic, allowing for quick adjustments to fluctuating event traffic and evolving business needs, and it can scale up to accommodate millions of topics, ensuring that computation and storage remain decoupled for optimal performance. Ultimately, this innovative design positions StreamNative as a leader in addressing the multifaceted requirements of modern data streaming.

Utilize Service Bus for a highly dependable cloud messaging solution that facilitates communication between applications and services, even during offline periods. This comprehensive managed service is accessible in all Azure regions, relieving you of the complexities associated with server management and licensing concerns. Enhance the interaction between clients and servers by employing asynchronous operations, which also support structured first-in, first-out (FIFO) messaging and publish/subscribe functionalities. By harnessing asynchronous messaging patterns, you can effectively scale your enterprise applications with reliability. Service Bus messaging allows for seamless integration with cloud resources like Azure SQL Database, Azure Storage, and Web Apps, ensuring smooth performance during fluctuating loads and providing the resilience needed to withstand intermittent outages. You can boost availability by creating intricate messaging topologies with advanced routing features, enabling messages to be sent to multiple recipients while efficiently distributing message delivery to downstream systems on a larger scale. This approach not only enhances operational efficiency but also ensures that your messaging infrastructure can adapt to the dynamic needs of your applications.

Amazon MQ is a cloud-based managed message broker service that utilizes Apache ActiveMQ, simplifying the process of establishing and running message brokers. These brokers facilitate communication and information exchange between various software systems, which may be built with different programming languages and operate on distinct platforms. By managing the provisioning, setup, and upkeep of ActiveMQ, a widely-used open-source message broker, Amazon MQ significantly eases your operational burden. Integrating your existing applications with Amazon MQ is straightforward, as it supports industry-standard APIs and messaging protocols such as JMS, NMS, AMQP, STOMP, MQTT, and WebSocket. This adherence to standards often eliminates the need to alter existing messaging code when transitioning to AWS. With just a few clicks in the Amazon MQ Console, you can provision your broker while ensuring compatibility with version upgrades, allowing you to utilize the latest version supported by Amazon MQ. After the broker is set up, your applications will be able to seamlessly produce and consume messages, streamlining your workflow and enhancing overall efficiency. Additionally, this service provides scalability, allowing you to adjust resources based on your application's needs, ensuring optimal performance at all times.

HiveMQ is the most trusted enterprise MQTT platform, purpose-built to connect anything via MQTT, communicate reliably, and control IoT data. The platform can be deployed anywhere, on-premise or in the cloud, giving developers the flexibility and freedom they need to evolve as their IoT deployment grows. HiveMQ is reliable under real-world stress, scales without limits, and provides enterprise-grade security to meet the needs of organizations at any stage of digital transformation. The extensible platform provides seamless connectivity to the leading data streaming, databases, and data analytics platforms, plus offers a custom SDK for a perfect fit in any stack.

TIBCO provides robust solutions designed to fulfill your requirements for performance, throughput, reliability, and scalability, while also offering diverse technology and deployment alternatives to ensure real-time data accessibility in critical areas. The TIBCO Platform integrates a continuously developing array of your TIBCO solutions, regardless of their hosting environment—be it cloud-based, on-premises, or at the edge—into a cohesive, single experience that simplifies management and monitoring. By doing so, TIBCO supports the creation of solutions vital for the success of major enterprises around the globe, enabling them to thrive in a competitive landscape. This commitment to innovation positions TIBCO as a key player in the digital transformation journey of businesses.

Google Cloud Pub/Sub offers a robust solution for scalable message delivery, allowing users to choose between pull and push modes. It features auto-scaling and auto-provisioning capabilities that can handle anywhere from zero to hundreds of gigabytes per second seamlessly. Each publisher and subscriber operates with independent quotas and billing, making it easier to manage costs. The platform also facilitates global message routing, which is particularly beneficial for simplifying systems that span multiple regions. High availability is effortlessly achieved through synchronous cross-zone message replication, coupled with per-message receipt tracking for dependable delivery at any scale. With no need for extensive planning, its auto-everything capabilities from the outset ensure that workloads are production-ready immediately. In addition to these features, advanced options like filtering, dead-letter delivery, and exponential backoff are incorporated without compromising scalability, which further streamlines application development. This service provides a swift and dependable method for processing small records at varying volumes, serving as a gateway for both real-time and batch data pipelines that integrate with BigQuery, data lakes, and operational databases. It can also be employed alongside ETL/ELT pipelines within Dataflow, enhancing the overall data processing experience. By leveraging its capabilities, businesses can focus more on innovation rather than infrastructure management.

Nussknacker allows domain experts to use a visual tool that is low-code to help them create and execute real-time decisioning algorithm instead of writing code. It is used to perform real-time actions on data: real-time marketing and fraud detection, Internet of Things customer 360, Machine Learning inferring, and Internet of Things customer 360. A visual design tool for decision algorithm is an essential part of Nussknacker. It allows non-technical users, such as analysts or business people, to define decision logic in a clear, concise, and easy-to-follow manner. With a click, scenarios can be deployed for execution once they have been created. They can be modified and redeployed whenever there is a need. Nussknacker supports streaming and request-response processing modes. It uses Kafka as its primary interface in streaming mode. It supports both stateful processing and stateless processing.

A managed service facilitates two-way communication between IoT devices and Azure, ensuring secure and dependable interaction between your IoT application and its managed devices. With Azure IoT Hub, you have access to a cloud-based backend that can connect almost any device seamlessly. Moreover, you can enhance your solution from the cloud to edge devices through features like per-device authentication, integrated device management, and scalable provisioning options. By utilizing telemetry data from devices to the cloud, you can gain insights into device status and establish message pathways to other Azure services effortlessly, without the need for coding. For cloud-to-device messages, you can reliably send commands and alerts to your connected devices while monitoring message delivery via acknowledgment receipts. The system also allows for automatic resending of messages to address any connectivity issues that may arise. Azure IoT Central goes beyond just proof of concept; it empowers you to create top-tier solutions using a comprehensive hosted IoT application platform, thus fostering innovation in your projects. This combination of features positions Azure as a leading choice for IoT communication solutions.

IBM® MQ on Cloud represents the pinnacle of enterprise messaging solutions, ensuring secure and dependable communication both on-premises and across various cloud environments. By utilizing IBM MQ on Cloud as a managed service, organizations can benefit from IBM's management of upgrades, patches, and numerous operational tasks, which allows teams to concentrate on integrating it with their applications. For instance, if your company operates a mobile application in the cloud to streamline e-commerce transactions, IBM MQ on Cloud can effectively link the on-premises inventory management system with the consumer-facing app, offering users immediate updates regarding product availability. While your core IT infrastructure is located in San Francisco, the processing of packages occurs in a facility situated in London. IBM MQ on Cloud ensures that messages are transmitted reliably between these two locations. It enables the London office to securely encrypt and send data regarding each package that requires tracking, while allowing the San Francisco office to receive and manage that information with enhanced security measures. Both locations can confidently rely on the integrity of the information exchanged, ensuring that it remains intact and accessible. This level of communication is crucial for maintaining operational efficiency and trust across global business functions.

Flume is a dependable and distributed service designed to efficiently gather, aggregate, and transport significant volumes of log data. Its architecture is straightforward and adaptable, centered on streaming data flows, which enhances its usability. The system is built to withstand faults and includes various mechanisms for recovery and adjustable reliability features. Additionally, it employs a simple yet extensible data model that supports online analytic applications effectively. The Apache Flume team is excited to announce the launch of Flume version 1.8.0, which continues to enhance its capabilities. This version further solidifies Flume's role as a reliable tool for managing large-scale streaming event data efficiently.

Google Cloud's Managed Service for Apache Kafka is an efficient and scalable solution that streamlines the deployment, oversight, and upkeep of Apache Kafka clusters. By automating essential operational functions like provisioning, scaling, and patching, it allows developers to concentrate on application development without the burdens of managing infrastructure. The service guarantees high reliability and availability through data replication across various zones, thus mitigating the risks of potential outages. Additionally, it integrates effortlessly with other Google Cloud offerings, enabling the creation of comprehensive data processing workflows. Security measures are robust, featuring encryption for both stored and transmitted data, along with identity and access management, and network isolation to keep information secure. Users can choose between public and private networking setups, allowing for diverse connectivity options that cater to different requirements. This flexibility ensures that businesses can adapt the service to meet their specific operational needs efficiently.

VeloDB, which utilizes Apache Doris, represents a cutting-edge data warehouse designed for rapid analytics on large-scale real-time data. It features both push-based micro-batch and pull-based streaming data ingestion that occurs in mere seconds, alongside a storage engine capable of real-time upserts, appends, and pre-aggregations. The platform delivers exceptional performance for real-time data serving and allows for dynamic interactive ad-hoc queries. VeloDB accommodates not only structured data but also semi-structured formats, supporting both real-time analytics and batch processing capabilities. Moreover, it functions as a federated query engine, enabling seamless access to external data lakes and databases in addition to internal data. The system is designed for distribution, ensuring linear scalability. Users can deploy it on-premises or as a cloud service, allowing for adaptable resource allocation based on workload demands, whether through separation or integration of storage and compute resources. Leveraging the strengths of open-source Apache Doris, VeloDB supports the MySQL protocol and various functions, allowing for straightforward integration with a wide range of data tools, ensuring flexibility and compatibility across different environments.

Navigating the challenges of your organization may seem daunting, but creating a solution doesn't have to be complicated. 3forge offers a highly adaptable, low-code platform designed to accelerate enterprise application development like never before. Need reliability? Absolutely. Looking for scalability? You got it. What about rapid deliverability? That's also guaranteed, even with intricate workflows and extensive data sets. With 3forge, you can seamlessly unify data integration, virtualization, processing, visualization, and workflows in a single solution, effectively tackling some of the most intricate real-time streaming data challenges faced today. This award-winning technology from 3forge empowers developers to launch mission-critical applications swiftly and efficiently. Discover the transformative power of real-time data coupled with zero latency, as 3forge prioritizes seamless data integration, virtualization, processing, and visualization for optimal performance. As a result, you can focus on innovation rather than getting bogged down in technical difficulties.

Scale from zero to millions of events per second effortlessly. Arroyo is delivered as a single, compact binary, allowing for local development on MacOS or Linux, and seamless deployment to production environments using Docker or Kubernetes. As a pioneering stream processing engine, Arroyo has been specifically designed to simplify real-time processing, making it more accessible than traditional batch processing. Its architecture empowers anyone with SQL knowledge to create dependable, efficient, and accurate streaming pipelines. Data scientists and engineers can independently develop comprehensive real-time applications, models, and dashboards without needing a specialized team of streaming professionals. By employing SQL, users can transform, filter, aggregate, and join data streams, all while achieving sub-second response times. Your streaming pipelines should remain stable and not trigger alerts simply because Kubernetes has chosen to reschedule your pods. Built for modern, elastic cloud infrastructures, Arroyo supports everything from straightforward container runtimes like Fargate to complex, distributed setups on Kubernetes, ensuring versatility and robust performance across various environments. This innovative approach to stream processing significantly enhances the ability to manage data flows in real-time applications.

IBM® Messages for RabbitMQ on IBM Cloud® serves as a versatile broker that accommodates various messaging protocols, enabling users to efficiently route, track, and queue messages with tailored persistence levels, delivery configurations, and publish confirmations. With the integration of infrastructure-as-code tools like IBM Cloud Schematics utilizing Terraform and Red Hat® Ansible®, users can achieve global scalability without incurring additional costs. IBM® Key Protect allows customers to use their own encryption keys, ensuring enhanced security. Each deployment features support for private networking, in-database auditing, and various other functionalities. The Messages for RabbitMQ service enables independent scaling of both disk space and RAM to meet specific needs, allowing for seamless growth that is just an API call away. It is fully compatible with RabbitMQ APIs, data formats, and client applications, making it an ideal drop-in replacement for existing RabbitMQ setups. The standard setup incorporates three data members configured for optimal high availability, and deployments are strategically distributed across multiple availability zones to enhance reliability and performance. This comprehensive solution ensures that businesses can effectively manage their messaging needs while maintaining flexibility and security.

Facilitates seamless data exchange among components within microservice architectures. When utilized as a communication method for microservices, it not only streamlines integration but also enhances reliability and scalability. The system allows for reading and writing data in nearly real-time, while providing the flexibility to set data throughput and storage durations according to specific requirements. Users can finely configure resources for processing data streams, accommodating anything from small streams of 100 KB/s to more substantial ones at 100 MB/s. Additionally, Yandex Data Transfer enables the delivery of a single stream to various targets with distinct retention policies. Data is automatically replicated across multiple availability zones that are geographically distributed, ensuring redundancy and accessibility. After the initial setup, managing data streams can be done centrally through either the management console or the API, offering convenient oversight. It also supports continuous data collection from diverse sources, including website browsing histories and application logs, making it a versatile tool for real-time analytics. Overall, Yandex Data Streams stands out for its robust capabilities in handling various data ingestion needs across different platforms.

The Hitachi Streaming Data Platform (SDP) is engineered for real-time processing of extensive time-series data as it is produced. Utilizing in-memory and incremental computation techniques, SDP allows for rapid analysis that circumvents the typical delays experienced with conventional stored data processing methods. Users have the capability to outline summary analysis scenarios through Continuous Query Language (CQL), which resembles SQL, thus enabling adaptable and programmable data examination without requiring bespoke applications. The platform's architecture includes various components such as development servers, data-transfer servers, data-analysis servers, and dashboard servers, which together create a scalable and efficient data processing ecosystem. Additionally, SDP’s modular framework accommodates multiple data input and output formats, including text files and HTTP packets, and seamlessly integrates with visualization tools like RTView for real-time performance monitoring. This comprehensive design ensures that users can effectively manage and analyze data streams as they occur.

Streamline your event-driven applications with Event Grid, a unified service that efficiently handles the routing of events from any source to any endpoint. Built for exceptional availability, reliable performance, and flexible scalability, Event Grid allows you to concentrate on your application's functionality instead of the underlying infrastructure. It removes the need for polling, thereby cutting down on both costs and delays. Utilizing a pub/sub architecture with straightforward HTTP-based event transmission, Event Grid separates event producers from consumers, enabling the creation of scalable serverless solutions, microservices, and distributed architectures. You can achieve significant scalability on demand while receiving almost instantaneous notifications about the changes that matter to you. Enhance your application development with reactive programming principles, leveraging assured event delivery and the robust uptime provided by cloud technologies. Furthermore, you can create more complex application scenarios by integrating a variety of potential event sources and destinations, enhancing the overall capability of your solutions. Ultimately, Event Grid empowers developers to innovate and respond to changing requirements swiftly and efficiently.

Apache Doris serves as a cutting-edge data warehouse tailored for real-time analytics, enabling exceptionally rapid analysis of data at scale. It features both push-based micro-batch and pull-based streaming data ingestion that occurs within a second, alongside a storage engine capable of real-time upserts, appends, and pre-aggregation. With its columnar storage architecture, MPP design, cost-based query optimization, and vectorized execution engine, it is optimized for handling high-concurrency and high-throughput queries efficiently. Moreover, it allows for federated querying across various data lakes, including Hive, Iceberg, and Hudi, as well as relational databases such as MySQL and PostgreSQL. Doris supports complex data types like Array, Map, and JSON, and includes a Variant data type that facilitates automatic inference for JSON structures, along with advanced text search capabilities through NGram bloomfilters and inverted indexes. Its distributed architecture ensures linear scalability and incorporates workload isolation and tiered storage to enhance resource management. Additionally, it accommodates both shared-nothing clusters and the separation of storage from compute resources, providing flexibility in deployment and management.

Ably is the definitive realtime experience platform. We power more WebSocket connections than any other pub/sub platform, serving over a billion devices monthly. Businesses trust us with their critical applications like chat, notifications and broadcast - reliably, securely and at serious scale.

RabbitMQ is a lightweight solution that can be effortlessly deployed both on-premises and in cloud environments. It is compatible with various messaging protocols, making it versatile for different use cases. Furthermore, RabbitMQ can be configured in distributed and federated setups, which cater to demanding scalability and high availability needs. With a vast user base, it stands out as one of the leading open-source message brokers available today. Organizations ranging from T-Mobile to Runtastic leverage RabbitMQ, showcasing its adaptability for both startups and large enterprises. Additionally, RabbitMQ is compatible with numerous operating systems and cloud platforms, offering a comprehensive suite of development tools for popular programming languages. Users can deploy RabbitMQ using tools like Kubernetes, BOSH, Chef, Docker, and Puppet, facilitating seamless integration into their existing workflows. Developers can also create cross-language messaging solutions using their preferred programming languages, such as Java, .NET, PHP, Python, JavaScript, Ruby, and Go, enhancing its utility across various projects.

A user-friendly, serverless service for change data capture and replication that provides access to streaming data from a variety of databases including MySQL, PostgreSQL, AlloyDB, SQL Server, and Oracle. This solution enables near real-time analytics in BigQuery, allowing for quick insights and decision-making. With a straightforward setup that includes built-in secure connectivity, organizations can achieve faster time-to-value. The platform is designed to scale automatically, eliminating the need for resource provisioning or management. Utilizing a log-based mechanism, it minimizes the load and potential disruptions on source databases, ensuring smooth operation. This service allows for reliable data synchronization across diverse databases, storage systems, and applications, while keeping latency low and reducing any negative impact on source performance. Organizations can quickly activate the service, enjoying the benefits of a scalable solution with no infrastructure overhead. Additionally, it facilitates seamless data integration across the organization, leveraging the power of Google Cloud services such as BigQuery, Spanner, Dataflow, and Data Fusion, thus enhancing overall operational efficiency and data accessibility. This comprehensive approach not only streamlines data processes but also empowers teams to make informed decisions based on timely data insights.

Transform your data into a real-time stream, ensuring it is instantly accessible and ready for utilization. Leo simplifies the complexities of event sourcing, allowing you to effortlessly create, visualize, monitor, and sustain your data streams. By unlocking your data, you free yourself from the limitations imposed by outdated systems. The significant reduction in development time leads to higher satisfaction among both developers and stakeholders alike. Embrace microservice architectures to foster continuous innovation and enhance your agility. Ultimately, achieving success with microservices hinges on effective data management. Organizations need to build a dependable and repeatable data backbone to turn microservices into a tangible reality. You can also integrate comprehensive search functionality into your custom application, as the continuous flow of data makes managing and updating a search database a seamless task. With these advancements, your organization will be well-positioned to leverage data more effectively than ever before.

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

Event Hubs provides a fully managed service for real-time data ingestion that is easy to use, reliable, and highly scalable. It enables the streaming of millions of events every second from various sources, facilitating the creation of dynamic data pipelines that allow businesses to quickly address challenges. In times of crisis, you can continue data processing thanks to its geo-disaster recovery and geo-replication capabilities. Additionally, it integrates effortlessly with other Azure services, enabling users to derive valuable insights. Existing Apache Kafka clients can communicate with Event Hubs without requiring code alterations, offering a managed Kafka experience while eliminating the need to maintain individual clusters. Users can enjoy both real-time data ingestion and microbatching on the same stream, allowing them to concentrate on gaining insights rather than managing infrastructure. By leveraging Event Hubs, organizations can rapidly construct real-time big data pipelines and swiftly tackle business issues as they arise, enhancing their operational efficiency.

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

Axual provides a Kafka-as-a-Service tailored for DevOps teams, empowering them to extract insights and make informed decisions through our user-friendly Kafka platform. For enterprises seeking to effortlessly incorporate data streaming into their essential IT frameworks, Axual presents the perfect solution. Our comprehensive Kafka platform is crafted to remove the necessity for deep technical expertise, offering a ready-made service that allows users to enjoy the advantages of event streaming without complications. The Axual Platform serves as an all-encompassing solution, aimed at simplifying and improving the deployment, management, and use of real-time data streaming with Apache Kafka. With a robust suite of features designed to meet the varied demands of contemporary businesses, the Axual Platform empowers organizations to fully leverage the capabilities of data streaming while reducing complexity and minimizing operational burdens. Additionally, our platform ensures that your team can focus on innovation rather than getting bogged down by technical challenges.

A live data platform based on Change Data Capture (CDC) facilitates the replication of diverse databases, supports real-time data integration, and assists in constructing a real-time data warehouse. By implementing CDC to synchronize production line information stored in DB2 and Oracle with a modern database, TapData has empowered an AI-enhanced real-time dispatch application that streamlines the semiconductor manufacturing process. The availability of real-time data has enabled prompt decision-making within the RTD application, resulting in quicker turnaround times and increased production yield. As a major telecommunications provider, the client operates numerous regional systems designed to serve local users effectively. By consolidating and integrating data from multiple sources and locations into a single centralized data repository, the client successfully established an order center that aggregates orders from various applications. Additionally, TapData integrates inventory data from over 500 stores, delivering real-time insights into stock availability and customer preferences, thereby significantly boosting supply chain efficiency. This innovative approach not only enhances operational performance but also positions the client to respond swiftly to market demands.

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

Say goodbye to the complexities of low-level coding and integrating intricate systems. With SQL, you can effortlessly construct and deploy data pipelines in mere minutes. This data engineering service empowers both developers and data engineers to easily create and implement real-time data pipelines tailored for data-centric applications. The platform provides ready-made connectors for various messaging systems, storage solutions, and database engines, simplifying the process of connecting to and discovering available data. Each established connection generates a stream that facilitates data movement to or from the respective system. Utilizing Decodable, you can design your pipelines using SQL, where streams play a crucial role in transmitting data to and from your connections. Additionally, streams can be utilized to link pipelines, enabling the management of even the most intricate processing tasks. You can monitor your pipelines to ensure a steady flow of data and create curated streams for collaborative use by other teams. Implement retention policies on streams to prevent data loss during external system disruptions, and benefit from real-time health and performance metrics that keep you informed about the operation's status, ensuring everything is running smoothly. Ultimately, Decodable streamlines the entire data pipeline process, allowing for greater efficiency and quicker results in data handling and analysis.

A vast number of users leverage Amazon Managed Service for Apache Flink to execute their stream processing applications. This service allows you to analyze and transform streaming data in real-time through Apache Flink while seamlessly integrating with other AWS offerings. There is no need to manage servers or clusters, nor is there a requirement to establish computing and storage infrastructure. You are billed solely for the resources you consume. You can create and operate Apache Flink applications without the hassle of infrastructure setup and resource management. Experience the capability to process vast amounts of data at incredible speeds with subsecond latencies, enabling immediate responses to events. With Multi-AZ deployments and APIs for application lifecycle management, you can deploy applications that are both highly available and durable. Furthermore, you can develop solutions that efficiently transform and route data to services like Amazon Simple Storage Service (Amazon S3) and Amazon OpenSearch Service, among others, enhancing your application's functionality and reach. This service simplifies the complexities of stream processing, allowing developers to focus on building innovative solutions.

Timeplus is an efficient, user-friendly stream processing platform that is both powerful and affordable. It comes packaged as a single binary, making it easy to deploy in various environments. Designed for data teams across diverse sectors, it enables the quick and intuitive processing of both streaming and historical data. With a lightweight design that requires no external dependencies, Timeplus offers comprehensive analytic capabilities for streaming and historical data. Its cost is just a fraction—1/10—of what similar open-source frameworks charge. Users can transform real-time market and transaction data into actionable insights seamlessly. The platform supports both append-only and key-value streams, making it ideal for monitoring financial information. Additionally, Timeplus allows the creation of real-time feature pipelines effortlessly. It serves as a unified solution for managing all infrastructure logs, metrics, and traces, which are essential for maintaining observability. Timeplus also accommodates a broad array of data sources through its user-friendly web console UI, while providing options to push data via REST API or to create external streams without the need to copy data into the platform. Overall, Timeplus offers a versatile and comprehensive approach to data processing for organizations looking to enhance their operational efficiency.

AWS IoT Core enables seamless connectivity between IoT devices and the AWS cloud, eliminating the need for server provisioning or management. Capable of accommodating billions of devices and handling trillions of messages, it ensures reliable and secure processing and routing of communications to AWS endpoints and other devices. This service empowers applications to continuously monitor and interact with all connected devices, maintaining functionality even during offline periods. Furthermore, AWS IoT Core simplifies the integration of various AWS and Amazon services, such as AWS Lambda, Amazon Kinesis, Amazon S3, Amazon SageMaker, Amazon DynamoDB, Amazon CloudWatch, AWS CloudTrail, Amazon QuickSight, and Alexa Voice Service, facilitating the development of IoT applications that collect, process, analyze, and respond to data from connected devices without the burden of infrastructure management. By utilizing AWS IoT Core, you can effortlessly connect an unlimited number of devices to the cloud and facilitate communication among them, streamlining your IoT solutions. This capability significantly enhances the efficiency and scalability of your IoT initiatives.

Effortlessly capture, modify, and transfer streaming data in real time. You can create a delivery stream, choose your desired destination, and begin streaming data with minimal effort. The system automatically provisions and scales necessary compute, memory, and network resources without the need for continuous management. You can convert raw streaming data into various formats such as Apache Parquet and dynamically partition it without the hassle of developing your processing pipelines. Amazon Data Firehose is the most straightforward method to obtain, transform, and dispatch data streams in mere seconds to data lakes, data warehouses, and analytics platforms. To utilize Amazon Data Firehose, simply establish a stream by specifying the source, destination, and any transformations needed. The service continuously processes your data stream, automatically adjusts its scale according to the data volume, and ensures delivery within seconds. You can either choose a source for your data stream or utilize the Firehose Direct PUT API to write data directly. This streamlined approach allows for greater efficiency and flexibility in handling data streams.

Luna offers a subscription service for Apache Cassandra support and expertise through DataStax, allowing users to take advantage of open-source Cassandra while benefiting from the knowledge and experience of the team that created most of its code and has supported some of the largest deployments globally. With Luna, you gain access to best practices, expert advice, and SLA-based support to ensure your Cassandra setup remains optimal. You can scale your operations without sacrificing performance or latency, effectively managing even the most demanding real-time workloads with ease. The service empowers you to create dynamic and highly-interactive customer experiences with exceptionally fast read and write capabilities. Additionally, Luna helps resolve issues and adhere to best practices in managing Cassandra clusters. The support provided encompasses the entire application life cycle, facilitating a deeper collaboration with your team throughout the implementation process, ensuring that your needs are met at every stage. Ultimately, Luna enhances your ability to harness the full potential of Cassandra for your business objectives.