It is difficult for most businesses to effectively use numerous data of information since enterprise data analysis and management is becoming more difficult and complex. With the growing chances of failure and higher stakes at risk, businesses need to choose the proper software application or software tool that will extract insights from the inside information and manage the database of their enterprise.
What is DBVisualizer?
DBVisualizer is designed as a universal database tool to be used by data analysts, database administrators, and software developers. This software application offers a straightforward and all-in-one UI or user interface for enterprise database management. It comes in both a paid professional edition that provides a wider variation of features and a free edition.
Is DBVisualizer an open-source application?
No, it is a proprietary software application.
Will DBVisualizer run on both Linux and Windows?
DBVisualizer is also dubbed as the universal database tool. It implies that it is capable of running on all of the major operating systems. Hence, the DBVisualizer SQL editor runs smoothly on Windows, Linux/UNIX, and macOS.
Which technical roles would use DBVisualizer most?
Technical roles that deal with databases regularly such as database administrators, developers, and analysts require specific aspects that can be of help to make their work easier. With DBVisualizer, developers can access the advanced DBVisualizer SQL editor that includes smart features that are needed in writing queries, avoiding errors, and speeding up the coding process. For analysts, it will be easier and quicker for them to understand and access the data with the insight feature. They can also easily manage and create the database visually. Lastly, database administrators can be assured that data is secured and preserved during sessions with the autosave feature of DBVisualizer. The software application is also highly optimized and customized to fit the workflow of the user.
Databases or databases types that the DBVisualizer supports
Microsoft SQL Server
IBM DB2 LUW
Databases that are accessible with JDBC (Java Database Connectivity) driver is capable of working or running with DBVisualizer. You can also see DBVisualizer’s official website that some users have successfully used the software with other non-official database systems such as IBM DB2 iSeries, Firebird, Teradata, and Hive. Aside from that, you can also see the list of other databases that will soon be supported by DBVisualizer.
What are the most essential DBVisualizer documentation links?
Here are the following links that can cover the basic downloads to the application and basic information.
The business landscape of today is controlled and influenced by big data and it is also getting bigger and bigger as time goes by. Since the amount of data that is needed to be stored and organized is massive, data workers use SQL to access the information in a relational database. Software applications such as SQL clients can let users create SQL queries, access the database’s information, and view the models of relational databases. One of the most famous and sought out option for SQL clients is the SQuirreL SQL Client.
What is SQuirreL SQL?
It is a client for examining and retrieving SQL databases via a user-friendly and simple graphical user interface (GUI). It can run on any computer that has a Java Virtual Machine (JVM) since SQuirreL SQL is a programming language written in Java. You can download the SQuirreL SQL editor for free and is available in different languages such as English, Chinese, German, Russian, Portuguese, French, and Spanish.
Which technical roles would use SQuirreL SQL most?
SQuirreL SQL is useful and convenient for anyone who works on SQL databases regularly such as software developers, database administrators, application administrators, software testers, etc. For application administrators, they can use SQuirreL SQL to fix a bug at the level of the database. Aside from that, correcting and scanning for incorrect values in a table is easy using SQuirreL SQL. It can also help database administrators in overseeing huge varieties of relational databases, checking problems in tables, manage databases using commands, and viewing metadata.
Is it an open-source application?
SQuirreL SQL Client is a single, open-source graphical front end, Java-written program that enables you to issue SQL commands, perform SQL functions, and view the contents of a database. JDBC-compliant databases are supported by the built graphical front end. It also uses the most popular choice for the open-source software which is the GNU General Public License v2.0.
Will SQuirreL SQL run on both Linux and Windows?
SQuirreL is available under an open-source license and a popular Java written SQL database client. It runs under Microsoft Windows, Linux, and macOS.
Here are the supported databases of SQuirreL SQL:
Axion Java RDBMS
Ingres (also OpenIngres)
IBM DB2 for Windows, Linux, and OS/400
Microsoft SQL Server
Microsoft Access with the JDBC/ODBC bridge
Mckoi SQL Database
Oracle Database 8i, 9i, 10g, 11g
PostgreSQL 7.1.3 and higher
Sunopsis XML Driver (JDBC Edition)
Vertica Analytic Database
Firebird with JayBird JCA/JDBC Driver
What are the most essential SQuirreL SQL documentation links?
With high data volumes and complex systems, database management is becoming more in-demand in today’s economy. Aside from keeping up with the business, organizations also need to innovate new ideas to progress further in the industry. With the use of database management tools, a web interface is provided for database administrators, allowing SQL queries to run.
What is DBeaver?
DBeaver is an open-source universal management tool that can help anyone in professionally working with their data. It will help you maneuver your data similar to a typical spreadsheet, construct analytical reports of various data storage records, and convey information. Effective SQL-editor, connection sessions monitoring, many administration features, and schema and data migration capabilities are imparted with DBeaver’s user on the advanced database. Aside from its usability, it also supports a wide array of databases.
Here are the other offers of DBeaver:
Cloud data sources support
Security standard of enterprise support
Support of multiplatform
Meticulous design and implementation of user interface
Can work with other integration extensions
Will it run on both Linux and Windows?
DBeaver is downloadable for Windows 9/8/10, Mac OS X, and Linux. It requires at least Java 1.8 version, and OpenJDK 11 bundle is already included in DBeaver’s MacOS and Windows installer.
Main features of DBeaver
DBeaver main features include:
Various data sources connection
Edit and view data
Built-in SQL editor
Builds the visual query
Compares several database structures
And generates schema/database ER diagrams.
Which databases or database types does DBeaver support?
More than 80 databases are supported by DBeaver, and it includes some of the well-known databases such as:
denodo 7.0 saves some manual coding when building the ‘Base Views’ by performing some initial data type conversions from ANSI SQL type to denodo Virtual DataPort data types. So, where is a quick reference mapping to show to what the denodo Virtual DataPort Data Type mappings are:
ANSI SQL types To Virtual DataPort Data types Mapping
ANSI SQL Type
Virtual DataPort Type
BIT VARYING (n)
CHARACTER VARYING (n)
DECIMAL (n, m)
NUMERIC (n, m)
TIMESTAMP WITH TIME ZONE
VARCHAR ( MAX )
ANSI SQL Type Conversion Notes
The function CAST truncates the output when converting a value to a text, when these two conditions are met:
You specify a SQL type with a length for the target data type. E.g. VARCHAR(20).
And, this length is lower than the length of the input value.
When casting a boolean to an integer, true is mapped to 1 and false to 0.
While investigating a recent Infosphere Information Server (IIS), Datastage, Essbase Connect error I found the explanations of the probable causes of the error not to be terribly meaningful. So, now that I have run our error to ground, I thought it might be nice to jot down a quick note of the potential cause of the ‘Client Commands are Currently Not Being Accepted’ error, which I gleaned from the process.
Error Message Id
An error occurred while processing the request on the server. The error information is 1051544 (message on contacting or from application:[<<DateTimeStamp>>]Local////3544/Error(1013204) Client Commands are Currently Not Being Accepted.
Possible Causes of The Error
This Error is a problem with access to the Essbase object or accessing the security within the Essbase Object. This can be a result of multiple issues, such as:
Object doesn’t exist – The Essbase object didn’t exist in the location specified,
Communications – the location is unavailable or cannot be reached,
Path Security – Security gets in the way to access the Essbase object location
Essbase Security – Security within the Essbase object does not support the user or filter being submitted. Also, the Essbase object security may be corrupted or incomplete.
Essbase Object Structure – the Essbase object was not properly structured to support the filter or the Essbase filter is malformed for the current structure.
IBM Knowledge Center, InfoSphere Information Server 11.7.0, Connecting to data sources, Enterprise applications, IBM InfoSphere Information Server Pack for Hyperion Essbase
While chasing an error to which only applied to join type stages, I thought it might be nice to identify what the InfoSphere Information Server DataStage / QualityStage are. There are three of them, as you can see from the picture above, which are the:
And, Merge Stage.
All three stages that join data based on the values of identified keycolumns.
IBM Knowledge Center, InfoSphere Information Server 11.7.0, InfoSphere DataStage and QualityStage, Developing parallel jobs, Processing Data, Lookup Stage
When you are controlling a chain of sequences in the job stream and taking advantage of reusable (multiple instances) jobs it is useful to be able to pass the Invocation ID from the master controlling sequence and have it passed down and assigned to the job run. This can easily be done with needing to manual enter the values in each of the sequences, by leveraging the DSJobInvocationId variable. For this to work:
The job must have ‘Allow Multiple Instance’ enabled
The Invocation Id must be provided in the Parent sequence must have the Invocation Name entered
The receiving child sequence will have the invocation variable entered
At runtime, a DataStage invocation id instance of the multi-instance job will generate with its own logs.
This approach allows for the reuse of job and the assignment of meaningful instance extension names, which are managed for a single point of entry in the object tree.
IBM Knowledge Center > InfoSphere Information Server 11.5.0
InfoSphere DataStage and QualityStage > Designing DataStage and QualityStage jobs > Building sequence jobs > Sequence job activities > Job Activity properties
While working with a client’s 9.1 DataStage version, I ran into a situation where they wanted to parameterize SQL where clause lists in an Oracle Connector stage, which honestly was not very straight forward to figure out. First, if the APT_OSL_PARAM_ESC_SQUOTE is not set and single quotes are used in the parameter, the job creates unquoted invalid SQL when the parameter is populated. Second, I found much of the information confusing and/or incomplete in its explanation. After some research and some trial and error, here is how I resolved the issue. I’ll endeavor to be concise, but holistic in my explanation.
When this Variable applies
This where I know this process applies, there may be other circumstances to which is this applicable, but I’m listing the ones here with which I have recent experience.
Infosphere Information Server Datastage
Versions 91, 11.3, and 11.5
Versions 11g and 12c
Here is a brief explanation of the steps I used to implement the where clause as a parameter. Please note that in this example, I am using a job parameter to populate on a portion of the where clause, you can certainly pass the entire where clause as a parameter, if it is not too long.
Configure Project Variable in Administrator
Add APT_OSL_PARAM_ESC_SQUOTE to project in Administrator
Populate the APT_OSL_PARAM_ESC_SQUOTE Variable
Create job parameter
Following your project name convention or standard practice, if you customer and/or project do not have established naming conventions, create the job parameter in the job. See jp_ItemSource parameter in the image below.
Add job parameter to Custom SQL in Select Oracle Connector Stage
On the Job parameter has been created, add the job parameter to the SQL statement of the job.
IBM Knowledge Center > InfoSphere Information Server 11.5.0
Connecting to data sources > Databases > Oracle databases > Oracle connector
Since the Infosphere, information server, repository, has to be installed manually with the scripts provided in the IBM software, sometimes you run into difficulties. So, here’s a quick script, which I have found useful in the past to identify user permissions for the IAUSER on Oracle database’s to help rundown discrepancies in user permissions.
WHERE GRANTEE = ‘iauser’
If we cannot run against the ALL_TAB_PRIVS view, then we can try the ALL_TAB_PRIVS view:
WHERE GRANTEE = ‘iauser’
oracle help Center > Database Reference > ALL_TAB_PRIVS view
If you want to describe a PureData / Netezza table in SQL, it can be done, but Netezza doesn’t have a describe command. Here is a quick SQL, which will give the basic structure of a table or a view. Honestly, if you have Aginity Generating the DDL is fast and more informative, at least to me. If you have permissions to access NZSQL you can also use the slash commands (e.g. d).
The function Substring (SUBSTR) in Netezza PureData provides the capability parse character type fields based on position within a character string. However, it is possible, with a little creativity, to substring based on the position of a character in the string. This approach give more flexibility to the substring function and makes the substring more useful in many cases. This approach works fine with either the substring or substr functions. In this example, I used the position example provide the numbers for the string command.
Example Substring SQL
Substring SQL Used In Example
,position(‘,’ in LOCATIONTEXT) as Comma_Postion_In_String
,SUBSTRING(LOCATIONTEXT,position(‘,’ in LOCATIONTEXT)) as Substring_On_Comma
—Adjusted to account for extra space
,SUBSTRING(LOCATIONTEXT,position(‘,’ in LOCATIONTEXT)+2) as Substring_On_Comma_Ajusted
,’==Breaking_Up_The_Sting==’ as Divider
— breaking up the string
,SUBSTRING(LOCATIONTEXT,1, position(‘ ‘ in LOCATIONTEXT)-1) as Beggining_of_String
,SUBSTRING(LOCATIONTEXT,position(‘ ‘ in LOCATIONTEXT)+1, position(‘ ‘ in LOCATIONTEXT)-1) as Middle_Of_String
,SUBSTRING(LOCATIONTEXT,position(‘,’ in LOCATIONTEXT)+2) as End_Of_String
The position function in Netezza is a simple enough function, it just returns the number of a specified character within a string (char, varchar, nvarchar, etc.) or zero if the character not found. The real power of this command is when you imbed it with character function, which require a numeric response, but the character may be inconsistent from row to row in a field.
The Position Function’s Basic Syntax
position(<<character or Character String>> in <<CharacterFieldName>>)
Example Position Function SQL
Position Function SQL Used in Example
select LOCATIONTEXT, CITY
,’==Postion Funtion Return Values==’ as Divider
,position(‘,’ in LOCATIONTEXT) as Postion_In_Nbr_String
,position(‘-‘ in LOCATIONTEXT) as Postion_Value_Not_Found
,’==Postion Combined with Substring Function==’ as Divider2
,SUBSTRING(LOCATIONTEXT,position(‘,’ in LOCATIONTEXT)+2) as Position_Used_in_Substring_Function
FROM Blog.D_ZIPCODE where STATE = ‘MN’ AND CITY = ‘RED WING’ limit 1;
PureData System for Analytics, PureData System for Analytics 7.2.1, IBM Netezza user-defined functions, Data type helper API reference, Temporal data type helper functions, Netezza date/time data type representations
Adding a forging key to tables in Netezza / PureData is a best practice; especially, when working with dimensionally modeled data warehouse structures and with modern governance, integration (including virtualization), presentation semantics (including reporting, business intelligence and analytics).
Foreign Key (FK) Guidelines
A primary key must be defined on the table and fields (or fields) to which you intend to link the foreign key
Avoid using distribution keys as foreign keys
Foreign Key field should not be nullable
Your foreign key link field(s) must be of the same format(s) (e.g. integer to integer, etc.)
Apply standard naming conventions to constraint name:
Please note that foreign key constraints are not enforced in Netezza
Steps to add a Foreign Key
The process for adding foreign keys involves just a few steps:
Verify guidelines above
Alter table add constraint SQL command
Run statistics, which is optional, but strongly recommended
Basic Foreign Key SQL Command Structure
Here is the basic syntax for adding Foreign key:
ALTER TABLE <<Owner>>.<<NAME_OF_TABLE_BEING_ALTERED>>
ADD CONSTRAINT <<Constraint_Name>>_fk<Number>>
FOREIGN KEY (<<Field_Name or Field_Name List>>) REFERENCES <<Owner>>.<<target_FK_Table_Name>.(<<Field_Name or Field_Name List>>) <<On Update | On Delete>> action;
Example Foreign Key SQL Command
This is a simple one field example of the foreign key (FK)
ALTER TABLE Blog.job_stage_fact
ADD CONSTRAINT job_stage_fact_host_dim_fk1
FOREIGN KEY (hostid) REFERENCES Blog.host_dim(hostid) ON DELETE cascade ON UPDATE no action;
PureData System for Analytics, PureData System for Analytics 7.2.1, IBM Netezza database user documentation, Netezza SQL command reference, Alter Table, constraints
A foreign Key (FK) is a constraint that references the unique primary key (PK) of another table.
Facts About Foreign Keys
Foreign Keys act as a cross-reference between tables linking the foreign key (Child record) to the Primary key (parent record) of another table, which establishing a link/relationship between the table keys
Foreign keys are not enforced by all RDBMS
The concept of referential integrity is derived from foreign key theory
Because Foreign keys involve more than one table relationship, their implementation can be more complex than primary keys
A foreign-key constraint implicitly defines an index on the foreign-key column(s) in the child table, however, manually defining a matching index may improve join performance in some database
The SQL, normally, provides the following referential integrity actions for deletions, when enforcing foreign-keys
The deletion of a parent (primary key) record may cause the deletion of corresponding foreign-key records.
Forbids the deletion of a parent (primary key) record, if there are dependent foreign-key records. No Action does not mean to suppress the foreign-key constraint.
The deletion of a parent (primary key) record causes the corresponding foreign-key to be set to null.
The deletion of a record causes the corresponding foreign-keys be set to a default value instead of null upon deletion of a parent (primary key) record
Rebuilding Netezza view sometimes becomes necessary when the view’s source table have changed underneath the view. Rebuilding a view can be done on Netezza or in Aginity. In Aginity, it is a simple process, assume your user has permissions to create or replace a view. The process breaks down into just a few steps:
Generate the create / replace view SQL of the original view into the query window, if you don’t have it already
In the object browser:
Navigate to the Database and view you wish to rebuild
Select the view and right click
Select ‘Scripts’, then ‘DDL to Query window’
Make may updates to create / replace View SQL
This step is not always necessary, sometimes the changes which invalided the view did not actually impact the code of the view. If changes are necessary, make may updates to the SQL code.
Execute The code
This I usually do by choosing the ‘Execute as a single batch’ option. Make sure the code executes successfully.
Verify the view
To verify the simply execute a select statement and make it executes without errors and/or warning.
I found working with date literal, when working with the Infosphere SFDC Connector soql, to be counterintuitive for me. At least as I, normally, as I use SQL. I spent a little time running trials in Workbench, before I finally locked on to the ‘where clause’ criteria data pattern. So, here a quick example.
SOQL DATE String Literals Where Clause Rules
Basically, the date pattern is straight forward. The basic rules are for a soql where clause:
No Casting function, or casting for the where soql where clause to read.
Example SOQL DATE String Literals
So, here are a couple of date string literal examples in SQL:
Example SQL with Date String Literal Where Clause
From Target_and_Segmentation__c t
where t.Target_Date__c > 2014-10-31
Salesforce Developer Documentation
Home, Developer Documentation, Force.com SOQL and SOSL Reference
It is important to understand the differences between Database Management Systems (DBMS) types, since the structure of each type will influence integrations approaches, functionality, overall speed, and scalability.
The Five Types of Database Management Systems (DBMS)?
The five basic types of databases are:
Hierarchical Database (HDB)
A hierarchical database (HDB or HDBMS)is a design that uses a one-to-many relationship for data elements. Hierarchical database models use a tree structure that links several disparate elements to one “owner,” or “parent,” primary record.
Object-Oriented Database (OODB)
Object-Orientated databases (OODB or OODBM) integrate object orientation with database capabilities. Object orientation allows a more direct representation and modeling of real-world problems, and database functionality is needed to ensure persistence and concurrent sharing of information in applications.
Network Database (NDB)
Network databases (NDB or NDBMS) are quite like hierarchical databases, except it allows multiple records to be linked to the same owner file. The model can be seen as an upside down tree where the branches are the member information linked to the owner, which is the bottom of the tree. The multiple linkages which this information allows the network database model to be very flexible. In addition, the relationship that the information has in the network database model is defined as many-to-many relationship because one owner file can be linked to many member files and vice versa.
Relational Database (RDB)
In simplest terms, a relational database (RDB or RDBMS)is one that presents information in formally described tables with rows and columns. A table is referred to as a relation in the sense that it is a collection of objects of the same type (rows). Data in a table can be related per common keys or concepts, and the ability to retrieve related data from a table, which is the basis for the term relational database. Data can be accessed or reassembled in many ways without having to reorganize the database tables structure.
Flat File Database (FFDB)
A flat file database (FFDB or FFDBM) describes any of various means to encode a database model as a single file or collection of files, which can be a plain text file or a binary file. There are usually no structural relationships between the records. Each line of the text file holds one record, with fields separated by delimiters, such as commas or tabs. This is a very old database approach, but can still be found in use to, often with some relation capability enhancements,. Some example of current flat file databases are: GRAV, Jekyll, Kerby, and Monstra.
A Composite Primary key is Primary key What a primary key, which is defined by having multiple fields (columns) in it. Like a Primary Key what a composite Primary Key is depends on the database. Essentially a Composite Primary Key:
Is a combination of Fields (columns) which uniquely identifies every row.
Is an index in database systems which use indexes for optimization
Is a type of table constraint
Is applied with a data definition language (DDL) alter command
And may define parent-Child relationship between tables
In its simplest form, the convert function in Infosphere DataStage is a string replacement operation. Convert can be used to replace a specific character, a list of characters, or a unicode character (e.g. thumbs Up Sign or Grinning Face).
convert(‘<<Value to be replaced’,'<<Replacement value >>’,<<Input field>>)
Using the Convert Function to remove a list of Characters
Special Characters in DataStage Handles/converts special characters in a transformer stage, which can cause issues in XML processing and certain databases.