With the latest release of Vertabelo in 2021, we have overhauled the UI for a better experience in database modeling. We’ve also added a lot of new features requested by our customers.
We’re happy to announce we now support the latest versions of PostgreSQL and MS SQL Server. You can now define partitions, specify data types for sequences, and add identity columns in PostgreSQL. Similarly, you can create DDLs for the latest versions of MS SQL Server.
This article tells you how to enable some of the new features for the newly supported PostgreSQL versions. Please note the newer versions of PostgreSQL and MS SQL Server are available for all of Vertabelo plans: Basic, Premium, and Team. See the details on Vertabelo’s PRICING page.
First, let’s look at the much-awaited
PARTITION BY clause, which is a tremendous help during the database design process. Select the table you want to add or modify the partitions for. Go to the right-hand panel and navigate to “Additional properties”. You’ll see the following three fields grayed out, among other things:
To enable any of these options, just toggle the Set option on the side of the text box.
There are two ways to partition in PostgreSQL. You can use a
PARTITION BY clause, providing the name of the field you want to partition the table by as shown in the SQL script below:
CREATE TABLE catalog ( id not null primary key, isbn varchar(32) not null, title varchar(64) not null, authors json not null, release_date date not null, ) PARTITION BY RANGE (release_date);
Alternatively, you can use a combination of
PARTITION OF and
PARTITION BOUND fields.
CREATE TABLE catalog_y2002m02 PARTITION OF catalog FOR VALUES FROM ('2002-02-01') TO ('2002-03-01');
Using any of the above-mentioned additional properties, you can partition your PostgreSQL tables and cruise through your database modeling journey smoothly.
PostgreSQL, like other database engines, allows for an auto-increment column called
IDENTITY. You can have multiple identity columns for the same table. You can also use identity columns as primary keys.
With Vertabelo’s latest release, you can now set the identity column in the column properties of any column of the table. To do so, toggle the three dots adjacent to the delete icon in front of the column. Once you do that, you’ll see the “Identity” and “Identity options” fields you can use in the DDL.
Vertabelo supports all the PostgreSQL data types, even the minor ones. In the newest version, the Macaddr8 data type has been added.
It is so rarely used, and you may not see it in the “choose column type” popup. To use this data type in Vertabelo, you have to specify it manually. Vertabelo will validate the name of the data type; it will not throw any warnings or errors at you.
You can now specify the data type for a sequence. This is done by using the additional property “Data type” in the sequence properties panel (see screenshot below).
When this property is set, the "
AS ” statement is generated in the final DDL as shown in the example code below:
CREATE SEQUENCE my_sequence NO MINVALUE NO MAXVALUE NO CYCLE AS bigint ;
Support for MS SQL Server 2017 and 2019 has been added to Vertabelo. However, you may not need to make any changes to your DDL even if you upgrade to a newer version since there are no substantial changes to the generated DDLs. While Vertabelo supports the latest versions, we also continue to support older versions of MS SQL Server, such as 2012, 2014, and 2016.
As a reminder, database engine versions are used in Vertabelo Modeler in three places.
The Vertabelo team works tirelessly to bring the latest database modeling features to you. Of course, we always strive to support all the popular database and data warehouse engines you need for working with data models. Vertabelo already supports some of the most widely used data warehouse platforms, such as SNOWFLAKE, REDSHIFT, and GOOGLE BIGQUERY.
To keep fulfilling our pledge, we are rolling out support for MySQL 8.0, MariaDB 10.0, and Oracle 19c as well as 21c in 2022. Vertabelo provides the most up-to-date capabilities in an ERD tool while continuing to support older database versions.
Original article source at: https://www.vertabelo.com/
SQL stands for Structured Query Language. SQL is a scripting language expected to store, control, and inquiry information put away in social databases. The main manifestation of SQL showed up in 1974, when a gathering in IBM built up the principal model of a social database. The primary business social database was discharged by Relational Software later turning out to be Oracle.
Models for SQL exist. In any case, the SQL that can be utilized on every last one of the major RDBMS today is in various flavors. This is because of two reasons:
1. The SQL order standard is genuinely intricate, and it isn’t handy to actualize the whole standard.
2. Every database seller needs an approach to separate its item from others.
Right now, contrasts are noted where fitting.
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This is part 3 of “MS SQL Server- Zero to Hero” and in this article, we will be discussing about the SCHEMAS in SQL SERVER. Before getting into this article, please consider to visit previous articles in this series from below,
In part one, we learned the basics of data, database, database management system, and types of DBMS and SQL.
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When installing Machine Learning Services in SQL Server by default few Python Packages are installed. In this article, we will have a look on how to get those installed python package information.
When we choose Python as Machine Learning Service during installation, the following packages are installed in SQL Server,
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When you develop large chunks of T-SQL code with the help of the SQL Server Management Studio tool, it is essential to test the “Live” behavior of your code by making sure that each small piece of code works fine and being able to allocate any error message that may cause a failure within that code.
The easiest way to perform that would be to use the T-SQL debugger feature, which used to be built-in over the SQL Server Management Studio tool. But since the T-SQL debugger feature was removed completely from SQL Server Management Studio 18 and later editions, we need a replacement for that feature. This is because we cannot keep using the old versions of SSMS just to support the T-SQL Debugger feature without “enjoying” the new features and bug fixes that are released in the new SSMS versions.
If you plan to wait for SSMS to bring back the T-SQL Debugger feature, vote in the Put Debugger back into SSMS 18 to ask Microsoft to reintroduce it.
As for me, I searched for an alternative tool for a T-SQL Debugger SSMS built-in feature and found that Devart company rolled out a new T-SQL Debugger feature to version 6.4 of SQL – Complete tool. SQL Complete is an add-in for Visual Studio and SSMS that offers scripts autocompletion capabilities, which help develop and debug your SQL database project.
The SQL Debugger feature of SQL Complete allows you to check the execution of your scripts, procedures, functions, and triggers step by step by adding breakpoints to the lines where you plan to start, suspend, evaluate, step through, and then to continue the execution of your script.
You can download SQL Complete from the dbForge Download page and install it on your machine using a straight-forward installation wizard. The wizard will ask you to specify the installation path for the SQL Complete tool and the versions of SSMS and Visual Studio that you plan to install the SQL Complete on, as an add-in, from the versions that are installed on your machine, as shown below:
Once SQL Complete is fully installed on your machine, the dbForge SQL Complete installation wizard will notify you of whether the installation was completed successfully or the wizard faced any specific issue that you can troubleshoot and fix easily. If there are no issues, the wizard will provide you with an option to open the SSMS tool and start using the SQL Complete tool, as displayed below:
When you open SSMS, you will see a new “Debug” tools menu, under which you can navigate the SQL Debugger feature options. Besides, you will see a list of icons that will be used to control the debug mode of the T-SQL query at the leftmost side of the SSMS tool. If you cannot see the list, you can go to View -> Toolbars -> Debugger to make these icons visible.
During the debugging session, the SQL Debugger icons will be as follows:
The functionality of these icons within the SQL Debugger can be summarized as:
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Since the release of SQL Server 2017 for Linux, Microsoft has pretty much changed the entire game. It enabled a whole new world of possibilities for their famous relational database, offering what was only available in the Windows space until then.
I know that a purist DBA would tell me right away that the out of the box SQL Server 2019 Linux version has several differences, in terms of features, in regards to its Windows counterpart, such as:
However, I got curious enough to think “what if they can be compared, at least to some extent, against things that both can do?” So, I pulled the trigger on a couple of VMs, prepared some simple tests, and collected data to present to you. Let’s see how things turn out!
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