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Data Mesh Architecture: Revolutionizing Event Streaming with Striim

Striim

Data Mesh is revolutionizing event streaming architecture by enabling organizations to quickly and easily integrate real-time data, streaming analytics, and more. In this article, we will explore the advantages and limitations of data mesh, while also providing best practices for building and optimizing a data mesh with Striim.

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Top 10 MongoDB Career Options in 2024 [Job Opportunities]

Knowledge Hut

Versatility: The versatile nature of MongoDB enables it to easily deal with a broad spectrum of data types , structured and unstructured, and therefore, it is perfect for modern applications that need flexible data schemas. Designing and implementing RESTful APIs for MongoDB data access.

MongoDB 52
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3 Use Cases for Real-Time Blockchain Analytics

Rockset

However, analyzing the data generated on the blockchain by these dApps is challenging. The appeal of blockchain - namely, open access, permissionless access, privacy and transparency - renders the on-chain data relatively basic, with only simple transaction details recorded.

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AWS Glue-Unleashing the Power of Serverless ETL Effortlessly

ProjectPro

Application programming interfaces (APIs) are used to modify the retrieved data set for integration and to support users in keeping track of all the jobs. Users can schedule ETL jobs, and they can also choose the events that will trigger them. You can produce code, discover the data schema, and modify it.

AWS 98
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Large-scale User Sequences at Pinterest

Pinterest Engineering

So our user sequence real-time indexing pipeline is composed of a Flink job that reads the relevant events as they come into our Kafka streams, fetches the desired features for each event from our feature services, and stores the enriched events into our KV store system. Handles out-of-order inserts.

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Implementing the Netflix Media Database

Netflix Tech

under varying load conditions as well as a wide variety of access patterns; (b) scalability?—?persisting data access semantics that guarantee repeatable data read behavior for client applications. MDVS also serves as the storehouse and the manager for the data schema itself.

Media 94
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50 PySpark Interview Questions and Answers For 2023

ProjectPro

PySpark runs a completely compatible Python instance on the Spark driver (where the task was launched) while maintaining access to the Scala-based Spark cluster access. Their team uses Python's unittest package and develops a task for each entity type to keep things simple and manageable (e.g., sports activities). count())) df2.show(truncate=False)

Hadoop 52