December 2024
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Unlock the power of real-time data and analytics by watching this insightful roundtable discussion featuring experts from MongoDB, CrateDB, Decodable, and GridGain. Get practical strategies for implementing real-time data and analytics
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Watch this webinar to learn why CrateDB is a perfect [Rockset] replacement for real-time analytics and hybrid search.
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Watch how TGW, a global leader in logistics automation, digitally transformed warehouse operations using Azure.
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Watch this recorded webinar where we explore the dynamic field of Artificial Intelligence. Discover how you can leverage CrateDB as a vector store using native SQL, to create a knowledge assistant powered by Generative AI.
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In this recorded webinar, you will dive into the dynamic world of time series data and discover how to solve most problems faced when analyzing time series data.
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Discover and learn more about CrateDB, the hyper-fast distributed database for all types of data, combining the simplicity of SQL and scalability of NoSQL.
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CrateDB Workshop is a hands-on learning experience that introduces the fundamental concepts of CrateDB, a distributed SQL database. This workshop is designed for everyone interested in learning about CrateDB features and how it can be used to store, query and analyze large amounts of data.
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This demo offers a step-by-step guide on leveraging Debezium and Kafka to replicate data from different databases into CrateDB.
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In this interactive live demo, learn, step-by-step, how to use Prometheus and Grafana with CrateDB Cloud.
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In this live demo, our speakers show how easy it is to import data to CrateDB Cloud, connect to a third-party tool and visualize the data for whatever purpose.
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To develop a real-time monitoring solution, O-CELL needed a scalable and fault tolerant database with a flexible data schema storage upgrades and ease of use for deploying additional resources. Being their database since an early stage, CrateDB has adapted to O-CELL business needs, offering scalability, reliability and speed, essential for real-time monitoring.
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Time-series data and analysis can help businesses understand patterns, trends, and causes over time. This is crucial for business success. In this webinar, Crate.io’s Solution Engineering team will guide you through the implementation steps of a time-series use case - from table layout to querying.
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SPGo! By PETROMIN, has developed a system that allows monitoring mining material conveyor belts with more than 40,000 sensors in real-time and 760 million records per day.
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In this joint webinar with Bitmovin our speakers will share Bitmovin’s experience, challenges, and why they chose CrateDB as the best solution for their business.
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In this joint German webinar with TGW Logistics, Alexander Mann explains why they chose CrateDB after trying multiple database systems.
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After trying multiple database systems, TGW Logistics moved to CrateDB for its ability to aggregate different data formats and ability to query this information without much hassle.
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In this webinar, we had a hands-on look at how to leverage the CrateDB 4.8 enhancements when importing data and using Logical Replication to move data between CrateDB clusters to make it available where it is needed.
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Learn how Gantner relied on CrateDB to analyze the large amount of data generated by the project in real-time and to improve the processes through machine learning.
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In this webinar, we will discuss how to use different visualization options in Superset coupled with a SQL interface to derive interesting insights and findings from the time-series dataset.
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In this joint German webinar with Microsoft, we share the use case of a leading CPG manufacturer and how they reduced their costs with CrateDB and Azure.
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First-hand insights from Thomas Concrete Group about the advantages of working with CrateDB for different use cases with real-time IoT data.
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Learn why it’s important to be an early adopter of industrial loT practices and how projects can successfully be monitored, measured and optimized using the right database.
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The IIoT can cause a new manufacturing revolution... But in order to succeed, it requires the right tools.
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Best practices for working with time-series data fast, with horizontal scalability, and with SQL.