Comparison of the Kx Developer and Kx Analyst products
Here is a brief summary of the features:
|Product Features||Kx Developer||Kx Analyst|
|Fine-Grained Version Control|
Git-based version control for q functions, scripts, and modules. Users can work locally and check items in and out of a shared repository. Many standard Git functions are supported.
|Interactive q Script Editor and q Lint Support|
Interactive editor with code completion, syntax highlighting, q lint support, breakpoints and context-sensitive help.
Quick debugger displays a visual stack trace for erroring lines of code to allow you to diagnosis issues faster.
The Profiler identifies performance characteristics and issues with your functions.
|Compare & Merge Tool|
Compare code for additions, deletions, and changes as well as conflict resolution on merge.
|Automated Test Support|
Complete support for automated test creation using a behavioural driven (BDD) testing framework similar to Cucumber and a property library similar to QuickCheck for automatically generating test cases. Code coverage is also supported.
Query & visualize massive datasets in real-time with a wide range of pre-built charts using a point-and-click interface to set a wide variety of visual attributes.
|Grammar of Graphics Library|
A complete q library for building any kind of visualization with full support for multi-chart linking, data types, visual aesthetics, and interactive drilldown/brushing.
|Data Import Wizard|
Import any kind of delimited data (e.g. CSV), JSON, XML, INI, ODBC, JDBC and any kdb+ dataset without programming using a point-and-click interface.
|Big Data ETL & Query Tool (Transformer)|
Perform extract, transform and load (ETL) operations as well as join and query operations on multiple datasets without programming using a point-and-click interface.
|Enhanced Visual Inspector|
Additional plot types are provided in the Visual Inspector including geo mapping, plot matrices, network diagrams, quantile plotting, and path diagrams.
|Big Data Spreadsheet|
Manipulate and explore massive datasets using an SQL scripting language or the complete q programming language using an intuitive spreadsheet interface.