StreamFlux Integrations

Google Cloud is a cloud-based service that allows you to create anything from simple websites to complex applications for businesses of all sizes. New customers get $300 in free credits to run, test, and deploy workloads. All customers can use 25+ products for free, up to monthly usage limits. Use Google's core infrastructure, data analytics & machine learning. Secure and fully featured for all enterprises. Tap into big data to find answers faster and build better products. Grow from prototype to production to planet-scale, without having to think about capacity, reliability or performance. From virtual machines with proven price/performance advantages to a fully managed app development platform. Scalable, resilient, high performance object storage and databases for your applications. State-of-the-art software-defined networking products on Google’s private fiber network. Fully managed data warehousing, batch and stream processing, data exploration, Hadoop/Spark, and messaging.

BigQuery is a serverless, multicloud data warehouse that simplifies the process of working with all types of data so you can focus on getting valuable business insights quickly. At the core of Google’s data cloud, BigQuery allows you to simplify data integration, cost effectively and securely scale analytics, share rich data experiences with built-in business intelligence, and train and deploy ML models with a simple SQL interface, helping to make your organization’s operations more data-driven.

MongoDB is a general purpose, document-based, distributed database built for modern application developers and for the cloud era. No database is more productive to use. Ship and iterate 3–5x faster with our flexible document data model and a unified query interface for any use case. Whether it’s your first customer or 20 million users around the world, meet your performance SLAs in any environment. Easily ensure high availability, protect data integrity, and meet the security and compliance standards for your mission-critical workloads. An integrated suite of cloud database services that allow you to address a wide variety of use cases, from transactional to analytical, from search to data visualizations. Launch secure mobile apps with native, edge-to-cloud sync and automatic conflict resolution. Run MongoDB anywhere, from your laptop to your data center.

Whether you're looking for compute power, database storage, content delivery, or other functionality, AWS has the services to help you build sophisticated applications with increased flexibility, scalability and reliability. Amazon Web Services (AWS) is the world’s most comprehensive and broadly adopted cloud platform, offering over 175 fully featured services from data centers globally. Millions of customers—including the fastest-growing startups, largest enterprises, and leading government agencies—are using AWS to lower costs, become more agile, and innovate faster. AWS has significantly more services, and more features within those services, than any other cloud provider–from infrastructure technologies like compute, storage, and databases–to emerging technologies, such as machine learning and artificial intelligence, data lakes and analytics, and Internet of Things. This makes it faster, easier, and more cost effective to move your existing applications to the cloud.

Microsoft's Azure is a cloud computing platform that allows for rapid and secure application development, testing and management. Azure. Invent with purpose. Turn ideas into solutions with more than 100 services to build, deploy, and manage applications—in the cloud, on-premises, and at the edge—using the tools and frameworks of your choice. Continuous innovation from Microsoft supports your development today, and your product visions for tomorrow. With a commitment to open source, and support for all languages and frameworks, build how you want, and deploy where you want to. On-premises, in the cloud, and at the edge—we’ll meet you where you are. Integrate and manage your environments with services designed for hybrid cloud. Get security from the ground up, backed by a team of experts, and proactive compliance trusted by enterprises, governments, and startups. The cloud you can trust, with the numbers to prove it.

Keras is an API designed for human beings, not machines. Keras follows best practices for reducing cognitive load: it offers consistent & simple APIs, it minimizes the number of user actions required for common use cases, and it provides clear & actionable error messages. It also has extensive documentation and developer guides. Keras is the most used deep learning framework among top-5 winning teams on Kaggle. Because Keras makes it easier to run new experiments, it empowers you to try more ideas than your competition, faster. And this is how you win. Built on top of TensorFlow 2.0, Keras is an industry-strength framework that can scale to large clusters of GPUs or an entire TPU pod. It's not only possible; it's easy. Take advantage of the full deployment capabilities of the TensorFlow platform. You can export Keras models to JavaScript to run directly in the browser, to TF Lite to run on iOS, Android, and embedded devices. It's also easy to serve Keras models as via a web API.

Elastic is a search company. As the creators of the Elastic Stack (Elasticsearch, Kibana, Beats, and Logstash), Elastic builds self-managed and SaaS offerings that make data usable in real time and at scale for search, logging, security, and analytics use cases. Elastic's global community has more than 100,000 members across 45 countries. Since its initial release, Elastic's products have achieved more than 400 million cumulative downloads. Today thousands of organizations, including Cisco, eBay, Dell, Goldman Sachs, Groupon, HP, Microsoft, Netflix, The New York Times, Uber, Verizon, Yelp, and Wikipedia, use the Elastic Stack, and Elastic Cloud to power mission-critical systems that drive new revenue opportunities and massive cost savings. Elastic has headquarters in Amsterdam, The Netherlands, and Mountain View, California; and has over 1,000 employees in more than 35 countries around the world.

The Apache Cassandra database is the right choice when you need scalability and high availability without compromising performance. Linear scalability and proven fault-tolerance on commodity hardware or cloud infrastructure make it the perfect platform for mission-critical data. Cassandra's support for replicating across multiple datacenters is best-in-class, providing lower latency for your users and the peace of mind of knowing that you can survive regional outages.

RabbitMQ is lightweight and easy to deploy on-premises and in the cloud. It supports multiple messaging protocols. RabbitMQ can be deployed in distributed and federated configurations to meet high-scale, high-availability requirements. With tens of thousands of users, RabbitMQ is one of the most popular open-source message brokers. From T-Mobile to Runtastic, RabbitMQ is used worldwide at small startups and large enterprises. RabbitMQ is lightweight and easy to deploy on-premises and in the cloud. It supports multiple messaging protocols. RabbitMQ can be deployed in distributed and federated configurations to meet high-scale, high-availability requirements. RabbitMQ runs on many operating systems and cloud environments and provides a wide range of developer tools for most popular languages. Deploy with Kubernetes, BOSH, Chef, Docker and Puppet. Develop cross-language messaging with favorite programming languages such as Java, .NET, PHP, Python, JavaScript, Ruby, Go, etc.

There are billions of devices in homes, factories, oil wells, hospitals, cars, and thousands of other places. With the proliferation of devices, you increasingly need solutions to connect them, and collect, store, and analyze device data. AWS has broad and deep IoT services, from the edge to the cloud. AWS IoT is the only cloud vendor to bring together data management and rich analytics in easy-to-use services designed for noisy IoT data. AWS IoT offers services for all layers of security, including preventive security mechanisms, like encryption and access control to device data, and service to continuously monitor and audit configurations. AWS brings AI and IoT together to make devices more intelligent. You can create models in the cloud and deploy them to devices where they run 2x faster compared to other offerings. Optimize operations by easily creating digital twins of real-world systems. Run analytics on volumes of IoT data easily—without building an analytics platform.

The Apache Hive data warehouse software facilitates reading, writing, and managing large datasets residing in distributed storage using SQL. Structure can be projected onto data already in storage. A command line tool and JDBC driver are provided to connect users to Hive. Apache Hive is an open source project run by volunteers at the Apache Software Foundation. Previously it was a subproject of Apache® Hadoop®, but has now graduated to become a top-level project of its own. We encourage you to learn about the project and contribute your expertise. Traditional SQL queries must be implemented in the MapReduce Java API to execute SQL applications and queries over distributed data. Hive provides the necessary SQL abstraction to integrate SQL-like queries (HiveQL) into the underlying Java without the need to implement queries in the low-level Java API.

Apache Kafka® is an open-source, distributed streaming platform. Scale production clusters up to a thousand brokers, trillions of messages per day, petabytes of data, hundreds of thousands of partitions. Elastically expand and contract storage and processing. Stretch clusters efficiently over availability zones or connect separate clusters across geographic regions. Process streams of events with joins, aggregations, filters, transformations, and more, using event-time and exactly-once processing. Kafka’s out-of-the-box Connect interface integrates with hundreds of event sources and event sinks including Postgres, JMS, Elasticsearch, AWS S3, and more. Read, write, and process streams of events in a vast array of programming languages.

Apache Spark™ is a unified analytics engine for large-scale data processing. Apache Spark achieves high performance for both batch and streaming data, using a state-of-the-art DAG scheduler, a query optimizer, and a physical execution engine. Spark offers over 80 high-level operators that make it easy to build parallel apps. And you can use it interactively from the Scala, Python, R, and SQL shells. Spark powers a stack of libraries including SQL and DataFrames, MLlib for machine learning, GraphX, and Spark Streaming. You can combine these libraries seamlessly in the same application. Spark runs on Hadoop, Apache Mesos, Kubernetes, standalone, or in the cloud. It can access diverse data sources. You can run Spark using its standalone cluster mode, on EC2, on Hadoop YARN, on Mesos, or on Kubernetes. Access data in HDFS, Alluxio, Apache Cassandra, Apache HBase, Apache Hive, and hundreds of other data sources.

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

100% compatible with Netezza. Single command-line upgrade path. Available on premises, on cloud or hybrid. IBM® Netezza® Performance Server for IBM Cloud Pak® for Data is an advanced data warehouse and analytics platform available both on premises and on cloud. With enhancements to in-database analytics capabilities, this next generation of Netezza enables you to do data science and machine learning with data volumes scaling into the petabytes. Failure detection and fast failure recovery. Single command-line upgrade to existing systems. Ability to query many systems as one. Choose the data center or availability zone closest to you, set the number of compute units and amount of storage required to run, and go. IBM® Netezza® Performance Server for IBM Cloud Pak® for Data is available on IBM Cloud®, Amazon Web Services (AWS) and Microsoft Azure. Deployable on a private cloud, Netezza is powered by IBM Cloud Pak for Data System.

Apache ActiveMQ® is the most popular open source, multi-protocol, Java-based message broker. It supports industry standard protocols so users get the benefits of client choices across a broad range of languages and platforms. Connect from clients written in JavaScript, C, C++, Python, .Net, and more. Integrate your multi-platform applications using the ubiquitous AMQP protocol. Exchange messages between your web applications using STOMP over websockets. Manage your IoT devices using MQTT. Support your existing JMS infrastructure and beyond. ActiveMQ offers the power and flexibility to support any messaging use-case. There are currently two "flavors" of ActiveMQ available - the well-known "classic" broker and the "next generation" broker code-named Artemis. Once Artemis reaches a sufficient level of feature parity with the "Classic" code-base it will become the next major version of ActiveMQ. Initial migration documentation is available as well as a development roadmap for Artemis.

Deploying multiple analytic engines means best-fit engineering, so QueryGrid lets users leverage the right tool for the job. SQL is the language of business, and QueryGrid delivers unparalleled SQL access across commercial and open source analytical engines. Built for a hybrid multi-cloud reality, Vantage solves the world’s most complex data challenges at scale. Software that delivers autonomy, visibility, and insights to keep pace with changing customer demand.