Google Cloud Bigtable 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. Gemini in BigQuery offers AI-driven tools for assistance and collaboration, such as code suggestions, visual data preparation, and smart recommendations designed to boost efficiency and reduce costs. BigQuery delivers an integrated platform featuring SQL, a notebook, and a natural language-based canvas interface, catering to data professionals with varying coding expertise. This unified workspace streamlines the entire analytics process.

Consume data from any database, organize it into consistent metrics, and use it with every app. Build your Data and Reporting APIs faster with automated SQL generation, query optimization, access control, consistent metrics definitions, and API design. It takes only days to wrap any data source with a single reference Data API and simplify access to reporting and analytics data across your teams. Make it easy for data engineers and application developers to access the data from any source in a streamlined manner. - The single schema-less Data API endpoint - Review and configure metrics and dimensions in one place via UI - Data model visualization to make faster decisions - Data Export management scheduling AP Ready-to-use Report Builder and JavaScript components for charting libraries (Highcharts, BizCharts, Chart.js, etc.) makes it easy to embed data-rich functionality into your products. And you will not have to make custom report queries anymore!

Infometry Google Connectors enable native integration of Google Applications with Informatica Cloud IDMC (Formerly known as IICS). Infometry’s Google Sheets Connectors are 100% Informatica Certified and provide native interfaces. Infometry’s Connectors enable seamless integration and real-time Data Analytics. Infometry’s Google Connector for Informatica enables easy application integration, data extraction for downstream applications, and ETL for Enterprise Data Warehouse. Informatica Cloud Connector Customers are leveraging Google Sheets to store data sets such as Sales Forecast, Goals, Product Master, SKU, Lab Results, Headcount estimates, OpEx Budgets, etc which needs to be further loaded into Enterprise Data Warehouse, Cloud Applications, and Data Lake. Infometry built a Google Sheet connector using Informatica’s native interface, which supports all the API operations including reading, Writing, Update, Delete, Range, Search…etc.

InfluxDB is a purpose-built data platform designed to handle all time series data, from users, sensors, applications and infrastructure — seamlessly collecting, storing, visualizing, and turning insight into action. With a library of more than 250 open source Telegraf plugins, importing and monitoring data from any system is easy. InfluxDB empowers developers to build transformative IoT, monitoring and analytics services and applications. InfluxDB’s flexible architecture fits any implementation — whether in the cloud, at the edge or on-premises — and its versatility, accessibility and supporting tools (client libraries, APIs, etc.) make it easy for developers at any level to quickly build applications and services with time series data. Optimized for developer efficiency and productivity, the InfluxDB platform gives builders time to focus on the features and functionalities that give their internal projects value and their applications a competitive edge.

You can now augment your market research using Auris - an AI-powered consumer insights platform. Auris' deep learning models act on streaming data to provide invaluable insights. Think infinitely larger sample size, real time results at a fraction of the cost. Auris uses alternative data, which is already out there in the form of consumer conversations, feedback, reviews and so forth. This unstructured data needs cleaning for noise reduction, enrichment for various attributes. Auris enables that. The results is that you get great insights, in a very short period of time, in the manner you'd like. Rely on Auris for empowering your marketing strategy and execution. Listen to everything that you value: your brand, your product, and your areas of interest. This includes social media, review boards, news streams, influential blogs, even your competition! With Artificial Intelligence and Neuro-Linguistic Programming on your side, give form and structure to this raw data.

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.

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.

Now anyone can find insights hidden in their company data in seconds. Use search to analyze your data and get automated insights when you need them. ThoughtSpot lets anyone ask any questions, find insights, and drill infinitely into their company data in seconds. Stop waiting for custom reports from data experts and instantly answer ad-hoc data questions on the fly. Empower non-technical people to answer their own data questions, while you build a single source of truth with security and governance at scale. Maximize the value of your cloud data warehouse and accelerate speed-to-insight for everyone across your business. Democratize access to insights in minutes and transform the way your company uses data. See how the most innovative organizations use ThoughtSpot to get more value from their data. Deploy as SaaS or software in your virtual private cloud. AI-driven insights so you know sooner.

IntelliPay — Cloud-Based Payment Processing & Recurring Billing. PCI DSS Level 1-certified payment platform for SaaS, subscription, healthcare, government, and service-based businesses. Operating since 2004, IntelliPay processes billions annually across thousands of U.S. organizations. Features: Online, virtual, EMV, mobile, ACH/eCheck, recurring billing, installment plans, text-to-pay, IVR, kiosk, and custom branded payment portals — all from one dashboard. No-Cost Processing: Keep 100% of every sale by shifting card fees to the cardholder via dual pricing, surcharging, or convenience fee models. Traditional processing also available. Integrations: REST API, QuickBooks Online, and prebuilt plugins for most platforms. Why IntelliPay: 20+ years in payments 70+ years combined team experience Google Cloud-hosted, end-to-end encryption Transparent interchange-plus pricing, no hidden fees U.S.-based support

VPC Service Controls. Managed networking functionality for your Google Cloud resources. New customers get $300 in free credits to spend on Google Cloud during the first 90 days. All customers get free usage (up to monthly limits) of select products, including BigQuery and Compute Engine. Mitigate exfiltration risks by isolating multi-tenant services. Ensure sensitive data can only be accessed from authorized networks. Restrict resource access to allowed IP addresses, identities, and trusted client devices. Control which Google Cloud services are accessible from a VPC network. Enforce a security perimeter with VPC Service Controls to isolate resources of multi-tenant Google Cloud services—reducing the risk of data exfiltration or data breach. Configure private communication between cloud resources from VPC networks spanning cloud and on-premises hybrid deployments. Take advantage of fully managed tools like Cloud Storage, Bigtable, and BigQuery.

The all-in-one platform that connects your services and APIs in the most agile way. Empower busy development teams to build complex integrations that no-code tools cannot solve. The power of code is limitless, If you know how to code, with JavaScript you can create much more in less time. Review & audit code changes, audit credentials creation and use, check execution logs, etc. Use opened data streams, transactions, cache's, errors management, logging, multiple environments support, and reusable functions. Start executions on demand, in a scheduled approach, or using a webhook. Easy integration in your systems infrastructure in minutes. Reuse your business logic with JS modules, a friendly source code editor, powerful integrations, and libraries. On-premise Kubernetes deployment is an option. External identity providers and enhanced audit and logging. Write your scripts in a web browser and run them directly in the YepCode cloud.

The Apache Hadoop software library is a framework that allows for the distributed processing of large data sets across clusters of computers using simple programming models. It is designed to scale up from single servers to thousands of machines, each offering local computation and storage. Rather than rely on hardware to deliver high-availability, the library itself is designed to detect and handle failures at the application layer, so delivering a highly-available service on top of a cluster of computers, each of which may be prone to failures. A wide variety of companies and organizations use Hadoop for both research and production. Users are encouraged to add themselves to the Hadoop PoweredBy wiki page. Apache Hadoop 3.3.4 incorporates a number of significant enhancements over the previous major release line (hadoop-3.2).

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.

JanusGraph is a scalable graph database optimized for storing and querying graphs containing hundreds of billions of vertices and edges distributed across a multi-machine cluster. JanusGraph is a project under The Linux Foundation, and includes participants from Expero, Google, GRAKN.AI, Hortonworks, IBM and Amazon. Elastic and linear scalability for a growing data and user base. Data distribution and replication for performance and fault tolerance. Multi-datacenter high availability and hot backups. All functionality is totally free. No need to buy commercial licenses. JanusGraph is fully open source under the Apache 2 license. JanusGraph is a transactional database that can support thousands of concurrent users executing complex graph traversals in real time. Support for ACID and eventual consistency. In addition to online transactional processing (OLTP), JanusGraph supports global graph analytics (OLAP) with its Apache Spark integration.

With TIMi, companies can capitalize on their corporate data to develop new ideas and make critical business decisions faster and easier than ever before. The heart of TIMi’s Integrated Platform. TIMi’s ultimate real-time AUTO-ML engine. 3D VR segmentation and visualization. Unlimited self service business Intelligence. TIMi is several orders of magnitude faster than any other solution to do the 2 most important analytical tasks: the handling of datasets (data cleaning, feature engineering, creation of KPIs) and predictive modeling. TIMi is an “ethical solution”: no “lock-in” situation, just excellence. We guarantee you a work in all serenity and without unexpected extra costs. Thanks to an original & unique software infrastructure, TIMi is optimized to offer you the greatest flexibility for the exploration phase and the highest reliability during the production phase. TIMi is the ultimate “playground” that allows your analysts to test the craziest ideas!

At the intersection of data governance, privacy, and security, Privacera’s unified data access governance platform maximizes the value of data by providing secure data access control and governance across hybrid- and multi-cloud environments. The hybrid platform centralizes access and natively enforces policies across multiple cloud services—AWS, Azure, Google Cloud, Databricks, Snowflake, Starburst and more—to democratize trusted data enterprise-wide without compromising compliance with regulations such as GDPR, CCPA, LGPD, or HIPAA. Trusted by Fortune 500 customers across finance, insurance, retail, healthcare, media, public and the federal sector, Privacera is the industry’s leading data access governance platform that delivers unmatched scalability, elasticity, and performance. Headquartered in Fremont, California, Privacera was founded in 2016 to manage cloud data privacy and security by the creators of Apache Ranger™ and Apache Atlas™.

OpenTSDB consists of a Time Series Daemon (TSD) as well as set of command line utilities. Interaction with OpenTSDB is primarily achieved by running one or more of the independent TSDs. There is no master, no shared state so you can run as many TSDs as required to handle any load you throw at it. Each TSD uses the open source database HBase or hosted Google Bigtable service to store and retrieve time-series data. The data schema is highly optimized for fast aggregations of similar time series to minimize storage space. Users of the TSD never need to access the underlying store directly. You can communicate with the TSD via a simple telnet-style protocol, an HTTP API or a simple built-in GUI. The first step in using OpenTSDB is to send time series data to the TSDs. A number of tools exist to pull data from various sources into OpenTSDB.

Heroic is an open-source monitoring system originally built at Spotify to address problems faced with large scale gathering and near real-time analysis of metrics. Heroic uses a small set of components which are responsible for very specific things. Indefinite retention, as long as you have the hardware spend. Federation support to connect multiple Heroic clusters into a global interface. Heroic uses a small set of components which are responsible for very specific things. Consumers are the component responsible for consuming metrics. When building Heroic it was quickly realized that navigating hundreds of millions of time series without context is hard. Heroic has support for federating requests, which allows multiple independent Heroic clusters to serve clients through a single global interface. This can be used to reduce the amount of geographical traffic by allowing one cluster to operate completely isolated within its zone.

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.

Excel and Google Sheets are extremely fragile and prone to error while collaboration usually involves a lot of manual and repetitive work. Important files break all the time - often unnoticed and decisions are made on wrong data. Countless hours are wasted on dull and repetitive tasks by highly paid employees. Workflows need to be monitored manually, absorbing valuable mental capacity. Share only parts of your file - from cell ranges to entire tabs. Let Layer take care of all recurring tasks. All changes are highlighted so you don’t have to look for them. A complete history of changes, spreadsheet versions and communication. We are reinventing teamwork for spreadsheets by introducing a productivity layer on top of Excel and Google Sheets. Honestly, we are tired of the standard benefits companies offer nowadays.