Business Software for Google Cloud Dataflow

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.

DataBuck is an AI-powered data validation platform that automates risk detection across dynamic, high-volume, and evolving data environments. DataBuck empowers your teams to: ✅ Enhance trust in analytics and reports, ensuring they are built on accurate and reliable data. ✅ Reduce maintenance costs by minimizing manual intervention. ✅ Scale operations 10x faster compared to traditional tools, enabling seamless adaptability in ever-changing data ecosystems. By proactively addressing system risks and improving data accuracy, DataBuck ensures your decision-making is driven by dependable insights. Proudly recognized in Gartner’s 2024 Market Guide for #DataObservability, DataBuck goes beyond traditional observability practices with its AI/ML innovations to deliver autonomous Data Trustability—empowering you to lead with confidence in today’s data-driven world.

There are an estimated 25 million engineers in the world across dozens of distinct functions. As every company becomes a software company, engineers are using New Relic to gather real-time insights and trending data about the performance of their software so they can be more resilient and deliver exceptional customer experiences. Only New Relic provides an all-in-one platform that is built and sold as a unified experience. With New Relic, customers get access to a secure telemetry cloud for all metrics, events, logs, and traces; powerful full-stack analysis tools; and simple, transparent usage-based pricing with only 2 key metrics. New Relic has also curated one of the industry’s largest ecosystems of open source integrations, making it easy for every engineer to get started with observability and use New Relic alongside their other favorite applications.

Cloud IoT Core is a fully managed service that allows you to easily and securely connect, manage, and ingest data from millions of globally dispersed devices. Cloud IoT Core, in combination with other services on Cloud IoT platform, provides a complete solution for collecting, processing, analyzing, and visualizing IoT data in real time to support improved operational efficiency. Cloud IoT Core, using Cloud Pub/Sub underneath, can aggregate dispersed device data into a single global system that integrates seamlessly with Google Cloud data analytics services. Use your IoT data stream for advanced analytics, visualizations, machine learning, and more to help improve operational efficiency, anticipate problems, and build rich models that better describe and optimize your business. Securely connect a few or millions of your globally dispersed devices through protocol endpoints that use automatic load balancing and horizontal scaling to ensure smooth data ingestion under any condition.

Sedai is an autonomous cloud management platform powered by AI/ML delivering continuous optimization for cloud operations teams to maximize cloud cost savings, performance and availability at scale. Sedai enables teams to shift from static rules and threshold-based automation to modern ML-based autonomous operations. Using Sedai, organizations can reduce cloud cost by up to 50%, improve performance by up to 75%, reduce failed customer interactions (FCIs) by 75% and multiply SRE productivity by up to 6X for their modern applications. Sedai can perform work equivalent to a team of cloud engineers working behind the scenes to optimize resources and remediate issues, so organizations can focus on innovation.

Google Cloud's Dataplex is an intelligent data fabric that enables organizations to centrally discover, manage, monitor, and govern data across data lakes, data warehouses, and data marts with consistent controls, providing access to trusted data and powering analytics and AI at scale. Dataplex offers a unified interface for data management, allowing users to automate data discovery, classification, and metadata enrichment of structured, semi-structured, and unstructured data stored in Google Cloud and beyond. It facilitates the logical organization of data into business-specific domains using lakes and data zones, simplifying data curation, tiering, and archiving. Centralized security and governance features enable policy management, monitoring, and auditing across data silos, supporting distributed data ownership with global oversight. Additionally, Dataplex provides built-in data quality and lineage capabilities, automating data quality assessments and capturing data lineage.

Our platform allows businesses to use data—including its application in advanced analytics, machine learning, and AI—to do great things without worrying about putting customers, employees, or intellectual property at risk. The Protegrity Data Protection Platform doesn't just secure data—it simultaneously classifies and discovers data while protecting it. You can't protect what you don't know you have. Our platform first classifies data, allowing users to categorize the type of data that can mostly be in the public domain. With those classifications established, the platform then leverages machine learning algorithms to discover that type of data. Classification and discovery finds the data that needs to be protected. Whether encrypting, tokenizing, or applying privacy methods, the platform secures the data behind the many operational systems that drive the day-to-day functions of business, as well as the analytical systems behind decision-making.

CData Connect Your organization depends on real-time business and operational data to deliver actionable insights and drive growth. CData Connect is the missing link in your data value chain. CData Connect enables direct connectivity from any application that supports standard database connectivity, including popular cloud BI and ETL applications, such as: - Amazon Glue - Amazon QuickSight - Domo - Google Apps Script - Google Cloud Data Flow - Google Cloud Data Studio - Looker - Microsoft Power Apps - Microsoft Power Query - MicroStrategy Cloud - Qlik Sense Cloud - SAP Analytics Cloud - SAS Cloud - SAS Viya - Tableau Online ... and many more! CData Connect acts like a data gateway, translating SQL, and securely proxying API requests.

Understanding the performance of production systems is notoriously difficult. Attempting to measure performance in test environments usually fails to replicate the pressures on a production system. Micro benchmarking parts of your application are sometimes feasible, but it also typically fails to replicate the workload and behavior of a production system. Continuous profiling of production systems is an effective way to discover where resources like CPU cycles and memory are consumed as a service operates in its working environment. But profiling adds an additional load on the production system: in order to be an acceptable way to discover patterns of resource consumption, the additional load of profiling must be small. Cloud Profiler is a statistical, low-overhead profiler that continuously gathers CPU usage and memory-allocation information from your production applications. It attributes that information to the source code that generated it.

Cloud Composer's managed nature and Apache Airflow compatibility allows you to focus on authoring, scheduling, and monitoring your workflows as opposed to provisioning resources. End-to-end integration with Google Cloud products including BigQuery, Dataflow, Dataproc, Datastore, Cloud Storage, Pub/Sub, and AI Platform gives users the freedom to fully orchestrate their pipeline. Author, schedule, and monitor your workflows through a single orchestration tool—whether your pipeline lives on-premises, in multiple clouds, or fully within Google Cloud. Ease your transition to the cloud or maintain a hybrid data environment by orchestrating workflows that cross between on-premises and the public cloud. Create workflows that connect data, processing, and services across clouds to give you a unified data environment.

A low-code no-code approach to data quality. SaaS for flexibility, affordability, ease of integration, and efficient support. High standards of encryption, identity management, role-based access control, data governance, and compliance standards. Advanced ML models for detecting row-value data anomalies. Models will evolve and adapt to users' business and data needs. Add any number of data sources, records, and attributes. Well-equipped for unpredictable volume spikes. Support batch and streaming processing. Data is constantly monitored to provide real-time notifications, with zero impact on pipeline performance. Seamless boarding, integration, and investigation experience. Telmai is a platform for the Data Teams to proactively detect and investigate anomalies in real time. A no-code on-boarding. Connect to your data source and specify alerting channels. Telmai will automatically learn from data and alert you when there are unexpected drifts.

Serverless and easy-to-use change data capture and replication service. Access to streaming data from MySQL, PostgreSQL, AlloyDB, SQL Server, and Oracle databases. Near real-time analytics in BigQuery. Easy-to-use setup with built-in secure connectivity for faster time-to-value. A serverless platform that automatically scales, with no resources to provision or manage. Log-based mechanism to reduce the load and potential disruption on source databases. Synchronize data across heterogeneous databases, storage systems, and applications reliably, with low latency, while minimizing impact on source performance. Get up and running fast with a serverless and easy-to-use service that seamlessly scales up or down, and has no infrastructure to manage. Connect and integrate data across your organization with the best of Google Cloud services like BigQuery, Spanner, Dataflow, and Data Fusion.

Orchestra is a Unified Control Plane for Data and AI Operations, designed to help data teams build, deploy, and monitor workflows with ease. It offers a declarative framework that combines code and GUI, allowing users to implement workflows 10x faster and reduce maintenance time by 50%. With real-time metadata aggregation, Orchestra provides full-stack data observability, enabling proactive alerting and rapid recovery from pipeline failures. It integrates seamlessly with tools like dbt Core, dbt Cloud, Coalesce, Airbyte, Fivetran, Snowflake, BigQuery, Databricks, and more, ensuring compatibility with existing data stacks. Orchestra's modular architecture supports AWS, Azure, and GCP, making it a versatile solution for enterprises and scale-ups aiming to streamline their data operations and build trust in their AI initiatives.

Google Cloud Bigtable is a fully managed, scalable NoSQL database service for large analytical and operational workloads. Fast and performant: Use Cloud Bigtable as the storage engine that grows with you from your first gigabyte to petabyte-scale for low-latency applications as well as high-throughput data processing and analytics. Seamless scaling and replication: Start with a single node per cluster, and seamlessly scale to hundreds of nodes dynamically supporting peak demand. Replication also adds high availability and workload isolation for live serving apps. Simple and integrated: Fully managed service that integrates easily with big data tools like Hadoop, Dataflow, and Dataproc. Plus, support for the open source HBase API standard makes it easy for development teams to get started.

Ternary is the world’s first native FinOps cloud cost optimization tool. Built for Google Cloud on Google Cloud. Make better decisions, spend wisely and build a culture of accountability, collaboration and trust between finance and engineering teams. FinOps is the operating model for managing the variable spend of cloud, a combination of systems, best practices, and culture that ensures companies get the most value out of every cloud dollar spent. Ternary can help you at any stage of your FinOps journey. Ternary is creating tools at the intersection of finance and engineering with features based on FinOps principles. Ternary provides the missing bridge between finance and engineering that allows for visibility and context across teams. Ternary has workflows that provide visibility, encourage collaboration and accountability in order to help you easily monitor, prioritize and track cost optimizations to completion across an organization.

Organizations continuously strive to be more data-driven, building dashboards, analytics, and data pipelines across the modern data stack. Unfortunately, most organizations struggle with data reliability issues leading to poor business decisions and lack of trust in data as an organization, directly impacting their bottom line. Resolving complex data issues is a manual and time-consuming process involving multiple teams all relying on tribal knowledge to manually reverse engineer complex data pipelines across different platforms to identify root-cause and understand the impact. Pantomath is a data pipeline observability and traceability platform for automating data operations. It continuously monitors datasets and jobs across the enterprise data ecosystem providing context to complex data pipelines by creating automated cross-platform technical pipeline lineage.