#Razorsql vs dbeaver update#
If you can tolerate periodic update of the remote data to the local database, the performance benefit can be substantial. If you receive this error, check the In the Databases menu, click New Connection. Click Add ruleÂ, For port range, Enter the database port Eg: 3306 for MySQL, 5432 for PostgreSQL. > Sort (cost=1154.76 rows=88459 width=32) (actual time=1431.589.1431.591 rows=10 loops=1) Enter the following command to connect to a PostgreSQL database. SELECT word FROM words ORDER BY word 'caterpiler' LIMIT 10 > Index Only Scan using wrd_word on wrd (cost=0.42.4.44 rows=1 width=0) (actual time=0.039.0.039 rows=0 loops=1)Įither way, the word is spelled wrong, so let's look for what we might have wanted. If the materialized view is used instead, the query is much faster:Īggregate (cost=4.44.4.45 rows=1 width=0) (actual time=0.042.0.042 rows=1 loops=1) Sum(invoice_amt)::numeric(13,2) as sales_amt If people want to be able to quickly graph historical sales data, they might want to summarize, and they may not care about the incomplete data for the current date:ĬREATE MATERIALIZED VIEW sales_summary AS
Invoice_amt numeric(13,2) - amount of sale While access to the data stored in a materialized view is often much faster than accessing the underlying tables directly or through a view, the data is not always current yet sometimes current data is not needed.
When a materialized view is referenced in a query, the data is returned directly from the materialized view, like from a table the rule is only used for populating the materialized view. So for the parser, a materialized view is a relation, just like a table or a view. The information about a materialized view in the PostgreSQL system catalogs is exactly the same as it is for a table or view.
#Razorsql vs dbeaver drivers#
The main differences between:ĬREATE MATERIALIZED VIEW mymatview AS SELECT * FROM mytab ĬREATE TABLE mymatview AS SELECT * FROM mytab Īre that the materialized view cannot subsequently be directly updated and that the query used to create the materialized view is stored in exactly the same way that a view's query is stored, so that fresh data can be generated for the materialized view with: There are a couple different drivers that can be used to connect to Amazon's Redshift database that runs on the AWS platform. Materialized views in PostgreSQL use the rule system like views do, but persist the results in a table-like form.