Data Streaming

Real-time analytics, ML and applications made simple

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The Databricks Lakehouse Platform dramatically simplifies data streaming to deliver real-time analytics, machine learning and applications on one platform.

Enable your data teams to build streaming data workloads with the languages and tools they already know. Simplify development and operations by automating the production aspects associated with building and maintaining real-time data workloads. Eliminate data silos with a single platform for streaming and batch data.

Build streaming pipelines and applications faster

Use the languages and tools you already know with unified batch and streaming APIs in SQL and Python. Unlock real-time analytics, ML and applications for the entire organization.

Simplify operations with automated tooling

Easily deploy and manage your real-time pipelines and applications in production. Automated tooling simplifies task orchestration, fault tolerance/recovery, automatic checkpointing, performance optimization, and autoscaling.

Unify governance for all your real-time data across clouds

Unity Catalog gives your lakehouse one consistent governance model for all your streaming and batch data, simplifying how you discover, access and share real-time data.

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Streaming data ingestion and transformation

Real-time analytics, ML and applications

Automated operational tooling

Next-generation stream processing engine

Unified governance and storage

Streaming data ingestion and transformation

Simplify data ingestion and ETL for streaming data pipelines with Delta Live Tables. Leverage a simple declarative approach to data engineering that empowers your teams with the languages and tools they already know, like SQL and Python. Build and run your batch and streaming data pipelines in one place with controllable and automated refresh settings, saving time and reducing operational complexity. No matter where you plan to send your data, building streaming data pipelines on the Databricks Lakehouse Platform ensures you don’t lose time between raw and cleaned data.

"예전에는 불가능했던 셀프 서비스 방식으로 플랫폼을 사용하는 사업부가 점점 늘어났습니다. Databricks가 Columbia에 일으킨 긍정적 영향은 입이 닳도록 말해도 모자랍니다."

— Lara Minor, Senior Enterprise Data Manager, Columbia Sportswear

자세히

Data Ingestion

Analytic

Real-time analytics, ML and applications

With streaming data, immediately improve the accuracy and actionability of your analytics and AI. Your business benefits from real-time insights as a downstream impact of streaming data pipelines. Whether you’re performing SQL analytics and BI reporting, training your ML models or building real-time operational applications, give your business the freshest data possible to unlock real-time insights, more accurate predictions and faster decision-making to stay ahead of the competition.

“We must always deliver the most current and accurate data to our business partners, otherwise they’ll lose confidence in the insights . . . Databricks Lakehouse has made what was previously impossible extremely easy.”

— Guillermo Roldán, Head of Architecture, LaLiga Tech

자세히

Automated operational tooling

As you build and deploy streaming data pipelines, Databricks automates many of the complex operational tasks required for production. This includes automatically scaling the underlying infrastructure, orchestrating pipeline dependencies, error handling and recovery, performance optimization and more. Enhanced Autoscaling optimizes cluster utilization by automatically allocating compute resources for each unique workload. These capabilities along with automatic data quality testing and exception management help you spend less time on building and maintaining operational tooling so you can focus on getting value from your data.

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Automated

Next Generation Stream

Next-generation stream processing engine

Spark Structured Streaming is the core technology that unlocks data streaming on the Databricks Lakehouse Platform, providing a unified API for batch and stream processing. The Databricks Lakehouse Platform is the best place to run your Apache Spark workloads with a managed service that has a proven track record of 99.95% uptime. Your Spark workloads are further accelerated by Photon, the next-generation lakehouse engine compatible with Apache Spark APIs delivering record-breaking performance-per-cost while automatically scaling to thousands of nodes.

자세히

Unified governance and storage

Data streaming on Databricks means you benefit from the foundational components of the Lakehouse Platform — Unity Catalog and Delta Lake. Your raw data is optimized with Delta Lake, the only open source storage framework designed from the ground up for both streaming and batch data. Unity Catalog gives you fine-grained, integrated governance for all your data and AI assets with one consistent model to discover, access and share data across clouds. Unity Catalog also provides native support for Delta Sharing, the industry’s first open protocol for simple and secure data sharing with other organizations.

차세대 데이터 처리 엔진

Live Tables
Lakehouse Plateform
Workflows

통합

Provide maximum flexibility to your data teams — leverage Partner Connect and an ecosystem of technology partners to seamlessly integrate with popular data streaming tools.

Data Streaming

고객 사례

“We use Databricks for high-speed data in motion. It really helps us transform the speed at which we can respond to our patients’ needs either in-store or online. We have about a dozen initiatives right now and all of those are served out of the data in Databricks.”

— Sashi Venkatesan, Director of Product Engineering, Walgreens
walgreens

“Now that our fraud detection is real time, we can outwit fraudsters and stay ahead of their efforts in areas like fraudsters gaming the system, illegal unlocks, robocalls and robotexts, and identity theft.”

— Kate Hopkins, Vice President, AT&T

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