Make the most of your ColumnStore columnar analytics engine! Deep dive into best practices for columnar engines in general, what are the best use cases for columnar, and tips and trick for both ColumnStore and other analytics engines.
Redundancy and high availability are the basis for all production deployments. With MongoDB this can be achieved by deploying a replica set. In this talk, we'll explore how MongoDB replication works and what the components are of a replica set.
We store data with an intention to use it: search, retrieve, group, sort... To do it effectively, the MySQL Optimizer uses index statistics when it compiles the query execution plan. This approach works excellently unless your data distribution is not even.
PostgreSQL is undoubtedly the second most popular open source RDBMS and it is within the top five most popular DB engines as per db-engines.com. Why not take a rest from your favorite database server for a while, start learning some more about it, and aim for another logo on your resume?
Running an analytical (OLAP) workload on top of MySQL can be slow and painful. A specifically designed storage format ("Column Store") can significantly improve analytical queries' performance. There are a number of opensource column store databases around.
When it comes to choosing a distributed streaming platform for real-time data pipelines, everyone knows the answer: Apache Kafka! And when it comes to deploying applications at scale without needing to integrate different pieces of infrastructure yourself, the answer nowadays is increasingly Kubernetes.
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