9 Integrations with Ternary

View a list of Ternary integrations and software that integrates with Ternary below. Compare the best Ternary integrations as well as features, ratings, user reviews, and pricing of software that integrates with Ternary. Here are the current Ternary integrations in 2024:

  • 1
    Google Cloud Platform
    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.
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    Starting Price: Free ($300 in free credits)
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  • 2
    Google Cloud BigQuery
    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.
    Starting Price: $0.04 per slot hour
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  • 3
    Google Compute Engine
    Compute Engine is Google's infrastructure as a service (IaaS) platform for organizations to create and run cloud-based virtual machines. Computing infrastructure in predefined or custom machine sizes to accelerate your cloud transformation. General purpose (E2, N1, N2, N2D) machines provide a good balance of price and performance. Compute optimized (C2) machines offer high-end vCPU performance for compute-intensive workloads. Memory optimized (M2) machines offer the highest memory and are great for in-memory databases. Accelerator optimized (A2) machines are based on the A100 GPU, for very demanding applications. Integrate Compute with other Google Cloud services such as AI/ML and data analytics. Make reservations to help ensure your applications have the capacity they need as they scale. Save money just for running Compute with sustained-use discounts, and achieve greater savings when you use committed-use discounts.
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  • 4
    Kubernetes

    Kubernetes

    Kubernetes

    Kubernetes (K8s) is an open-source system for automating deployment, scaling, and management of containerized applications. It groups containers that make up an application into logical units for easy management and discovery. Kubernetes builds upon 15 years of experience of running production workloads at Google, combined with best-of-breed ideas and practices from the community. Designed on the same principles that allows Google to run billions of containers a week, Kubernetes can scale without increasing your ops team. Whether testing locally or running a global enterprise, Kubernetes flexibility grows with you to deliver your applications consistently and easily no matter how complex your need is. Kubernetes is open source giving you the freedom to take advantage of on-premises, hybrid, or public cloud infrastructure, letting you effortlessly move workloads to where it matters to you.
    Starting Price: Free
  • 5
    Google Kubernetes Engine (GKE)
    Run advanced apps on a secured and managed Kubernetes service. GKE is an enterprise-grade platform for containerized applications, including stateful and stateless, AI and ML, Linux and Windows, complex and simple web apps, API, and backend services. Leverage industry-first features like four-way auto-scaling and no-stress management. Optimize GPU and TPU provisioning, use integrated developer tools, and get multi-cluster support from SREs. Start quickly with single-click clusters. Leverage a high-availability control plane including multi-zonal and regional clusters. Eliminate operational overhead with auto-repair, auto-upgrade, and release channels. Secure by default, including vulnerability scanning of container images and data encryption. Integrated Cloud Monitoring with infrastructure, application, and Kubernetes-specific views. Speed up app development without sacrificing security.
  • 6
    Google Cloud Storage
    Object storage for companies of all sizes. Store any amount of data. Retrieve it as often as you’d like. Configure your data with Object Lifecycle Management (OLM) to automatically transition to lower-cost storage classes when it meets the criteria you specify, such as when it reaches a certain age or when you’ve stored a newer version of the data. Cloud Storage has an ever-growing list of storage bucket locations where you can store your data with multiple automatic redundancy options. Whether you are optimizing for split-second response time, or creating a robust disaster recovery plan, customize where and how you store your data. Storage Transfer Service and Transfer Service for on-premises data offer two highly performant, online pathways to Cloud Storage—both with the scalability and speed you need to simplify the data transfer process. For offline data transfer our Transfer Appliance is a shippable storage server.
  • 7
    Google Cloud Dataproc
    Dataproc makes open source data and analytics processing fast, easy, and more secure in the cloud. Build custom OSS clusters on custom machines faster. Whether you need extra memory for Presto or GPUs for Apache Spark machine learning, Dataproc can help accelerate your data and analytics processing by spinning up a purpose-built cluster in 90 seconds. Easy and affordable cluster management. With autoscaling, idle cluster deletion, per-second pricing, and more, Dataproc can help reduce the total cost of ownership of OSS so you can focus your time and resources elsewhere. Security built in by default. Encryption by default helps ensure no piece of data is unprotected. With JobsAPI and Component Gateway, you can define permissions for Cloud IAM clusters, without having to set up networking or gateway nodes.
  • 8
    Google Cloud Dataflow
    Unified stream and batch data processing that's serverless, fast, and cost-effective. Fully managed data processing service. Automated provisioning and management of processing resources. Horizontal autoscaling of worker resources to maximize resource utilization. OSS community-driven innovation with Apache Beam SDK. Reliable and consistent exactly-once processing. Streaming data analytics with speed. Dataflow enables fast, simplified streaming data pipeline development with lower data latency. Allow teams to focus on programming instead of managing server clusters as Dataflow’s serverless approach removes operational overhead from data engineering workloads. Allow teams to focus on programming instead of managing server clusters as Dataflow’s serverless approach removes operational overhead from data engineering workloads. Dataflow automates provisioning and management of processing resources to minimize latency and maximize utilization.
  • 9
    Cloudera DataFlow
    Cloudera DataFlow for the Public Cloud (CDF-PC) is a cloud-native universal data distribution service powered by Apache NiFi ​​that lets developers connect to any data source anywhere with any structure, process it, and deliver to any destination. CDF-PC offers a flow-based low-code development paradigm that aligns best with how developers design, develop, and test data distribution pipelines. With over 400+ connectors and processors across the ecosystem of hybrid cloud services—including data lakes, lakehouses, cloud warehouses, and on-premises sources—CDF-PC provides indiscriminate data distribution. These data distribution flows can then be version-controlled into a catalog where operators can self-serve deployments to different runtimes.
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