2022 Database Monitoring Storage 
Percona
MARCH 17, 2023
2022 was an exciting year for Percona Monitoring and Management (PMM). These updates are designed to keep databases running at peak performance and simplify database operations. PMM2 uses VictoriaMetrics (VM) as its metrics storage engine. We have tested PMM version 2.33.0
Percona
JANUARY 5, 2023
In PostgreSQL, vacuuming is a maintenance task that helps to optimize database performance and reclaim space. PostgreSQL and other database management systems use MVCC to ensure consistent reads and prevent data loss from concurrent updates. It is essential to run a vacuum to keep the database running smoothly periodically.
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Dynatrace
FEBRUARY 2, 2023
To establish the necessary monitoring, the observability team typically must be granted new setup permissions. For example, to monitor non-compute resources in Azure, many solutions require special components configured separately or even hosted by the customer. This process is often slow because component setup takes time.
Percona
JUNE 22, 2023
To make data count and to ensure cloud computing is unabated, companies and organizations must have highly available databases. A basic high availability database system provides failover (preferably automatic) from a primary database node to redundant nodes within a cluster. HA is sometimes confused with “fault tolerance.”
Percona
MARCH 30, 2023
The use of open source databases has increased steadily in recent years. Past trepidation — about perceived vulnerabilities and performance issues — has faded as decision makers realize what an “open source database” really is and what it offers. What is an open source database?
Dynatrace
FEBRUARY 16, 2023
To solve this problem, Dynatrace launched Grail, its causational data lakehouse , in 2022. Grail combines the big-data storage of a data warehouse with the analytical flexibility of a data lake. This unified approach enables Grail to vault past the limitations of traditional databases.
Percona
JULY 3, 2023
Partitioning is the concept of splitting large tables logically into smaller pieces for better performance of the database. However, a rule of thumb is that the size of the table should exceed the physical memory of the database server. The exact point at which a table will benefit from partitioning depends on the application.
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