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Guided learning journeys that build knowledge step by step.
category · Learning · slug · learning · 7812 Paths
7812 Paths · page 414 / 782
This learning path equips GIS developers with the knowledge and skills to design, query, and manage spatial databases. Starting with foundational database and spatial concepts, it progresses through spatial data types, indexing, and querying, culminating in practical applications using PostGIS.
A comprehensive learning path for developers in IoT and finance to understand and work with time-series databases. It covers data models, popular systems like InfluxDB and Prometheus, compression, downsampling, and retention.
A learning path for data engineers to understand and work with big data frameworks, covering HDFS, MapReduce, and Spark's architecture, RDDs, DataFrames, and Spark SQL. It builds from distributed systems and SQL fundamentals to advanced data processing concepts.
This learning path guides database developers and administrators through the internal architecture of PostgreSQL and MySQL. It covers storage management, indexing, query processing, MVCC, and replication, building from C programming and OS fundamentals to advanced system design. The path emphasizes hands-on exploration of source code and practical exercises to solidify understanding.
A hands-on, project-driven path to construct a minimal relational database management system. You will learn the internal architecture of a DBMS by implementing a SQL parser, query executor, storage engine, and transaction manager, with a strong emphasis on practical coding and system-level understanding.
A professional learning path for cloud architects to understand and design cloud-native database solutions. It covers core database concepts, cloud fundamentals, managed database services (RDS, DynamoDB, Cloud Spanner), replication, and architectural design patterns.
This advanced learning path equips data engineers with the knowledge to design, implement, and manage robust ETL pipelines. It covers data extraction, transformation, loading, data quality, and integration tools, building on foundational SQL and data warehousing concepts.
This learning path equips DBAs and developers with the skills to systematically tune and benchmark database performance. Starting from foundational SQL and DBMS internals, it progresses through performance metrics, benchmarking methodologies, and practical tuning of queries, indexes, and caches.
This advanced graduate-level path explores the theoretical underpinnings of query optimization in database systems. It covers relational algebra equivalences, cost models, join ordering, and dynamic programming, providing learners with the mathematical and algorithmic frameworks needed to analyze and design optimizers.
A graduate-level learning path covering the theoretical foundations of database transactions and isolation. Starting from ACID and serializability theory, it progresses through conflict and view serializability, weak isolation levels, snapshot isolation, and advanced concurrency control mechanisms, culminating in modern serializable snapshot isolation and research frontiers.