It seems like only yesterday that Navicat Monitor 2.0 was released, adding great new features to an already stellar product. Now, version 3.0 is introducing yet more outstanding features, including:
- Support monitoring PostgreSQL instances.
- Support SQL Profiler for PostgreSQL instances.
- Enhanced Query Analyzer.
- Enhanced Long Running Queries.
- Many other new features and improvements.
Of course, all of Navicat Monitor's existing functionality remains in place, including:
- Agentless Architecture
- Real-time Performance Monitoring
- See how your instances are currently functioning easily
- Advanced root cause analysis
- Set custom alert thresholds
- Get notifications via email, SMS or SNMP
- Replication Monitoring
- Powerful Query Analyzer
- and more...
In today's blog, we'll be taking a look at the brand new Navicat Monitor 3.0 with the emphasis being on the new features listed above.
Table Names
Naming conventions are a set of rules (written or unwritten) that should be utilized in order to increase the readability of the data model. You may apply these rules when naming anything inside the database, including tables, columns, primary and foreign keys, stored procedures, functions, views, etc. You need not apply rules to all database objects. For instance, it would be perfectly fine to limit naming convention rules to tables and column names. It's really your decision, as using a naming convention is not mandatory, but beneficial nonetheless. This three part series will present some commonly used naming conventions and provide some tips for formulating your own. Part 1 will cover Table names, while Part 2 will focus on column names. Finally, Part 3 will address Naming Conventions for other database objects such as Foreign Keys, Procedures, Functions, and Views.
It's official: the age of Artificial Intelligence (AI) has arrived! Until our new overlords decide to use us to power their machines, let's take the time to fully enjoy all the benefits they provide and the myriad of ways that they make our lives easier. Case in point, the AI-driven chatbot, ChatGPT, by OpenAI, has been lauded for its ability to produce tremendously spot-on answers to questions across a broad range of topics. And, although ChatGPT may not be making our jobs obsolete just yet, it has proven to be amazingly adept at working with data sets, much like a DBMS. In today's blog, we'll explore how ChatGPT could be utilized to supplement a professional database development and administration tool like Navicat.
Subqueries can be categorized into two types:
- A non-correlated (simple) subquery obtains its results independently of its containing (outer) statement.
- A correlated subquery references values from its outer query in order to execute.
When a non-correlated subquery executes (independently of the outer query), the subquery executes first, and then passes its results to the outer query. Meanwhile, a correlated subquery typically obtains values from its outer query before it executes. When the subquery returns, it passes its results to the outer query.
Now that we know the difference between a correlated subquery and its non-correlated counterpart, this blog will cover how to write a correlated subquery in Navicat Premium 16.
As you are no doubt aware, updating text values in the database is a commonplace occurrence. Nonetheless, it is a rare database administrator (DBA) that doesn't feel some trepidation upon executing batch updates against production tables. In today's blog, we'll learn how to use the SQL REPLACE() function to replace either a complete or partial string in a table column.
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