PROS:

Free, Multiplatform, Portable, Open-source:

• It can be used in any OS platform (Windows, Mac, Linux, ...), running on one of the supported Prolog interpreters.
• Moreover, portable executable applications are provided for Windows, Mac, and Linux.

Interactive:

• Based on a command line interpreter, you can play with DES submitting queries, modifying the database, and applying commands.

GUI:

• You can use the Java-based ACIDE 0.11 graphical environment (screenshot) as released in Download.
• It has been configured for Datalog syntax highlighting, command buttons and interactive console, therefore easing its use by decreasing the number of keystrokes (It applies to executable distributions).

Emacs-enabled:

• Do you like Emacs? Look for the Emacs environment by Markus Triska.

Query languages:

• Enjoy the power of deductive databases using Datalog, Extended Relational Algebra and SQL, all of them recursive.
• Share a common database of relations which can be defined with any of these languages, and query it with any of them too!

Live project:

• Expect a new release every 2 or 3 months.

Stable system:

• Few bugs have been reported.

Popular system:

• Look at the download Statistics and Facts!
• Just google ”Datalog”

Database updates:

• Modify the database with both SQL DML and system commands.

Null values:

• Take the responsibility of unknowness á la SQL at your own risk!

Outer joins:

• If nulls are allowed, why not use outer joins: left, right and full outer joins for SQL, RA and Datalog?

Aggregates:

• Summarize with count, sum, min, max, avg, and times for SQL, RA and Datalog.
• Find both predicate and functions versions of Datalog aggregates.
• Group data sets and filter with aggregates.
• Quickly build groups on-the-fly with Datalog auto-grouping.

Multisets:

• Enable or disable duplicates in both Datalog and SQL processing. Discard duplicates with distinct/1 and distinct/2

Hypothetical queries and rules

• Use the implication => to build “what-if” applications in a business intelligence scenario

Relational database access via ODBC:

• ODBC sources of data can be seamlessly accessed. Connect DES to any DBMS supporting such connections (MySQL, MS Access, Oracle, ...)

Persistency:

• Make predicates to persist on external data sources via ODBC connections

Modes:

• An input mode warns users about the need to ground an argument for an unsafe predicate.

Negation:

• Don’t expect much more than stratified negation and null flaws.

Novel and extended SQL features:

• Enforcement of functional dependencies
• Hypothetical queries:
  Let's assume data which is not in the database and play with decision-support systems.
• DIVISION relational operation:
  Use in SQL as well as in RA.
  (Don’t miss it with the arithmetic operator!)
• Mutual and non-linear recursion

That’s ok, but, may I use this novel features with external databases, such as MySQL?
Yes! Even with DB2, PostgreSQL, SQL Server and any DBMS connected with ODBC

Integrity constraints:

• Domain
• Types
• Primary keys
• Referential integrity
• Functional dependency
  Even for SQL CREATE TABLE definitions
  (Why don’t we have this in current DBMS’s already)?
• User-defined strong constraints
• Enable or disable constraint checking

Declarative debugging of Datalog programs:

• Did you ever looked for a working declarative debugger? Debug towards intended semantics rather than procedural semantics!

Test case generation for SQL views:

• Try this prototype for working with views over large tables and test them with the test cases, not with the actual tables!

Full-fledged arithmetic:

• Write arithmetical expressions with a wide set of arithmetical functions, operators and constants.

Type system for Datalog rules and SQL tables and views:

• Feel the benefits of typed relations and type inference.

Source-to-source program transformations:

• Safety. Enable safe transformations to execute safe rules. Experiment with unsafe rules.
• Performance. Enable simplifications to speed-up computations.
• Built-ins. Programs with outer join calls are transformed in order to be computed by the underlying tabled, fixpoint method.

Tabling-based implementation:

• Memo tables are used for implementing fixpoint and speeding-up computations.

Development mode:

• Enable it to understand how the system works. See the transformed program and examine nulls.

Pretty-printers:

• For SQL, RA and Datalog programs. Feel free to enable or disable pretty-print.

Batch execution:

• Provide a file with DES inputs and log the results into another file.

Connect DES to the outside world:

• Plug DES to a host system via standard streams.
• Try the new TAPI as released since version 2.5.
  You can connect DES to any development system! Java, C++, VB, Python, ...

CONS:

Not all is good. Consider that this is an educational system primarily supported by one developer. So:

• Do not expect DES to beat any performance mark.
• Do not expect DES to handle large amounts of data (but for external ODBC databases).
• Datalog:
• No compound terms as arguments in user relations.
• No database updates via Datalog rules are allowed.
• SQL:
• Table and column identifiers are case sensitive.
• Some incorrect SQL statements are not rejected (as those containing a GROUP BY clause and columns in the projection list which do not occur in the grouping list).
• Computable SQL statements follow the grammar in user manual. The current grammar parses extra clauses which cannot be computed yet (e.g., ALL, ANY, ...)
• Hypothetical queries cannot be used in view definitions

Bottomline:

Most CONS became PROS along time, so: What we would expect from DES in the future?

Keep an eye on the next version!