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StreamSets for Google Cloud Platform

Build big data pipelines in minutes from any source to Google Cloud Platform (GCP)

Simplify Your GCP Big Data Integration

When it’s time to try the next innovation in big data analytics, AI or machine learning and you need GCP processing power and product innovation, StreamSets delivers your data fast with big data integration. 

Use the platform to design, deploy, and operate big data pipelines across the entire Google stack. A visual interface makes it easy to build and operate smart data pipelines that detect and respond to change. 

 

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Big Data Integration For Google Cloud Platform
Build smart data pipelines for streaming and batch data without hand coding
Analyze real-time data for predictive analytics with plug-in TensorFlow models
Securely detect, encrypt and mask sensitive data in motion

Native Integrations to GCP

Accelerate your Google data projects on GCP with rapid data integration

Google Cloud Storage Big Data Integration
Google Cloud Bigtable Big Data Integration
Google Cloud Pub/Sub Big Data Integration
Google BigQuery Big Data Integration
Google Cloud SQL Big Data Integration
Screenshot Of StreamSets Native Execution On GCP

Native Execution on GCP

Easily move between on-premises and multiple cloud environments with native execution on these platforms:

  • Google Cloud Engine (GCE)
  • Google Kubernetes Engine (GKE)
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Manage Your GCP Data Platforms with StreamSets

Simplify Cloud Adoption And Continuous Sync To GCP With Big Data Integration

Simplify Cloud Adoption and Continuous Sync to GCP

Simplify your migration to GCP and keep your environments in sync using StreamSets’ pre-built connectivity to 100s of data sources, powerful data transformation, change data capture (CDC), and a full lifecycle approach to data engineering.

Move Any Data To Google BigQuery With Big Data Integration

Move Any Data to Google BigQuery

StreamSets provides a single, easy-to-use platform to integrate unstructured, semi-structured, and multi-structured data to BigQuery, using both synchronous and asynchronous ingestion methods.

Scalable Brokers With Google Pub/Sub For Streaming Data Pipelines

Setup Scalable Brokers with Google Pub/Sub

Connect to the most desired data sources with Google Pub/Sub and use StreamSets to manage the streaming and transformation of new data to your business. Identify and capture the data that is most strategic for your company and make it available instantly for analytics.

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Power of Hybrid without the Complexity

Detect and Respond to Data Drift

Other tools let you do data integration into GCP. But those data pipelines break when the unexpected happens, and they are hard to move to new data processing and cloud platforms. Only StreamSets DataOps Platform features smart data pipelines with built-in data drift detection and handling, and a hybrid cloud architecture, so that your operations run smoothly despite constant change.

Watch: Avoid Data Drift in Your Cloud Data Warehouse
Smart Big Data Pipelines Respond To Data Drift

Design-Deploy-Operate Continuously

In a static data world, up-front developer productivity matters more than operations. In a continuous data world, operations is everything. Close the loop between operations and development with automation and collaboration across the design-deploy-operate lifecycle. StreamSets Control Hub monitors data in flight to detect changes and predicts downstream issues to ensure continuous data delivery without errors or data loss. 

Watch: Adopting DataOps: Trends, Techniques & Technologies
Design-deploy-operate Big Data Integration Pipelines

Go Fast and Be Confident

When your business moves fast on a traditional architecture, things break. But when you take your time, you fall behind. DataOps gives you end-to-end transparency across your data infrastructure, so you can detect emergent patterns and designs. A live data map, enforceable data performance SLAs and data protection help you focus on making data reliable as your users experiment and innovate.

Watch: Stream into Kafka Webinar Series
Go Fast And Be Confident On GCP Data Platforms

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