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.
Percona XtraDB Cluster 8.0 (PXC-8.0) is the latest addition to PXC family. Starting MySQL/PS-8.0 upstream has done a lot of significant changes including atomic DDL, replication channel, locking algorithm changes, security/ encryption, etc....
During this talk, I explain how Group Replication replication works. This is a theoretical talk in which I explain in details what replication is and how it works.
I discuss what certification is and how it's done. What is XCOM and GCS?
In this session, we will discuss how we build Immutable infrastructure for databases.
Yahoo! JAPAN is the largest web portal in Japan. We have about 90 million unique browser accesses per month.
Indexes are a basic feature of relational databases, and PostgreSQL offers a rich collection of options to developers and designers.
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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