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Learn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark™, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWData StreamingReal-time analytics, ML and applications made simpleGet startedWatch demoThe 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 fasterUse 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 toolingEasily 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 cloudsUnity 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.How does it work?Streaming data ingestion and transformationReal-time analytics, ML and applicationsAutomated operational toolingNext-generation stream processing engineUnified governance and storageStreaming data ingestion and transformationSimplify 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.“More business units are using the platform in a self-service manner that was not possible before. I can’t say enough about the positive impact that Databricks has had on Columbia.”— Lara Minor, Senior Enterprise Data Manager, Columbia SportswearLearn moreReal-time analytics, ML and applicationsWith 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 TechLearn moreAutomated operational toolingAs 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.Learn moreNext-generation stream processing engineSpark 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.Learn moreUnified governance and storageData 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.IntegrationsProvide maximum flexibility to your data teams — leverage Partner Connect and an ecosystem of technology partners to seamlessly integrate with popular data streaming tools.Data StreamingCustomer Stories“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“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&TDiscover moreDelta Live TablesDatabricks WorkflowsUnity CatalogDelta LakeSpark Structured StreamingRelated contenteBooks and demosRise of the Data Lakehouse by Bill Inmon, father of the data warehouseData, Analytics and AI governanceThe Data Team’s Guide to the Databricks Lakehouse PlatformDelta Live Tables Streaming DemosEventsTackle Data Transformation With Delta Live TablesHassle-Free Data Ingestion Webinar SeriesData + AI Summit 2022Data +AI World Tour 2022BlogsLow-Latency Streaming Data Pipelines With Delta Live Tables and Apache KafkaSimplifying Streaming Data Ingestion Into Delta LakeReal-Time Insights: The Top Three Reasons Why Customers Love Data Streaming with DatabricksProject Lightspeed: Faster and Simpler Stream Processing With Apache SparkAn Overview of All the New Structured Streaming Features Developed in 2021 for Databricks and Apache Spark — The Databricks BlogReady to get started?Try for freeJoin the communityProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers
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