Why We Built HQL, the ASAM ODS Query Language | Page: 3 of 4 | Previous: Page 2: HQL, the Query Language for ASAM ODS | Next: Page 4: Why HQL Democratizes ASAM ODS Data Access

HQL gives engineers one query language for ASAM ODS data across every tool they already use, from Java and the command line to MATLAB, REST, and Python. That single fact is the payoff of this series, because the same query string that works in an interactive shell works unchanged in a script, an application, or a shared service, with no translation in between. This page walks the delivery spectrum by who needs it and what problem each form solves. It gives Python its own section, since ASAM ODS Python access through pyHQL reaches the largest audience, shows how the same language reaches AVL Santorin servers, and closes with how to get started, the questions buyers ask most, and the ways to take the next step.

HQL gives engineers, scripters, and developers a single, SQL-like query language across Python, MATLAB, Java, CLI, REST, and the browser. Comfort functions, relationship navigation, and unit conversion built in. Access ASAM ODS data without learning the ODS API. That single promise is the payoff of the whole series, and it matters because the same query string runs unchanged everywhere, so a query worked out interactively moves into a script, an application, or a shared service without a rewrite. This is genuine whitespace in the market. No other vendor offers a SQL-like text query language for ASAM ODS that runs the same way across Java, a command line, a REST service, Python, and MATLAB. The sections below organize the delivery forms by who needs them and what problem each one solves, rather than by product name.

The HQL Java library embeds the query language directly inside Java applications, and its origin is the clearest proof of how useful it is. HQL began as a library inside HighQSoft's own ASAMCommander Web application, where it proved so universally useful for reaching ODS data that HighQSoft extracted it and released it as a product in its own right. Developers embed it through a factory that opens a connection by URI or wraps an existing ODS session, and it offers a statement-builder API that bypasses the string parser entirely, which is the safe way to build queries from user input without risking injection. Because the library is the same engine that runs behind HighQSoft's own clients, it arrives hardened by years of production use rather than shipped as a separate, less-exercised code path.

The HQL library is the backbone of every HighQSoft ODS client. Building its own products on one query language means less training for the teams who maintain them, simpler products, and a single place to improve data access for everything at once.

The HQL command line client is an interactive shell for the simple, quick research an engineer does against an ASAM ODS server before anything becomes a script. Started from a connection string or a property file, it connects to an ODS 5 or ODS 6 server automatically and lets a user type a query and see results immediately, which is the fastest way to explore a model, check a filter, or confirm what a relationship returns. It also supports scripted command sequences with value injection between steps, so a session that began as exploration can become a repeatable, chained set of operations, including transactional inserts, without leaving the shell. A query proven in the command line is the same query text that drops into a Java application or a Python script later, so the shell doubles as a low-cost place to get a query right before committing it anywhere.

matHQL, the ASAM ODS Toolbox for MATLAB, connects MATLAB directly to ASAM ODS servers and to ATFx files, with read and write, using the same HQL syntax as every other surface. HighQSoft is the only test data management vendor offering native MATLAB integration with ASAM ODS, so measurement data lands in MATLAB as native tables and columns ready to plot and analyze, with no export in between. The depth of the MATLAB workflow, from connection through analysis and write-back, is covered in HighQSoft's MATLAB and ASAM ODS integration guide, and the toolbox itself is on the ASAM ODS Toolbox for MATLAB product page.

The ASAM ODS HQL Web Service is a REST endpoint that turns HQL into a single, installation-free access layer for an entire organization, and it is the section an IT Manager should read first. Rather than every team building and maintaining its own access code against the ODS API, the Web Service is installed once in the infrastructure and exposes HQL over HTTP to any language that can make a request, with pyHQL itself being one such client built on top of it. That consolidation is the point. One access layer means one thing to secure, monitor, and operate, instead of a sprawl of custom integrations each with its own maintenance burden and its own security surface. Because HQL runs against the ODS server, the Web Service inherits the standard's authentication and access-control model rather than inventing a parallel one, so it standardizes access without weakening governance. For an architecture review, the argument is simple. Fewer access layers, centrally operated, is less to build and less to defend.

Two more consumers complete the picture, and both run the same language. The browser is one, since HighQSoft's own web client builds its navigation and filters on HQL, as described earlier in this series. Plain English is the other, since the MCP Server for ASAM ODS translates natural-language questions into HQL, letting engineers query test data in plain English while the query stays inspectable underneath.

pyHQL is a ready-to-use Python library for ASAM ODS data access, and it removes the two things that make raw ASAM ODS Python integration tedious, hand-built REST calls and manual decoding of ODS datatypes. It wraps the HQL REST Web Service into Python-native objects, so a Python session speaks exactly the same HQL as the command line or MATLAB. Query results arrive as column-oriented objects carrying their own metadata, name, unit, type, and source element, and individual columns hand back plain Python lists that flow straight into NumPy, pandas, or any other analysis code. pyHQL handles typed values correctly, including dates and complex numbers, supports transactional writes with explicit commit or abort, and moves attachment files to and from the server through built-in upload and download. Because it runs over the Web Service, which connects to any compliant ASAM ODS server, pyHQL works against ODS 5 and ODS 6 alike. The result for a scripting engineer is that the whole loop of finding data, pulling channels, computing, and writing results back stays inside Python, with no export step and no custom access layer to build or maintain. Full details live on the pyHQL product page, and readers who want runnable Python code can see a complete session in HighQSoft's reference on working with the ASAM ODS API.

HighQSoft makes Python and MATLAB access to AVL Santorin servers straightforward, so a Santorin-based test data landscape becomes just as scriptable as any other. AVL Santorin is a solid, widely deployed ASAM ODS server, and HQL is built to add value on top of servers like it rather than to replace them. pyHQL and the MATLAB Toolbox both connect through the HQL Web Service, which uses the same connection-string mechanism documented for HQL generally, including the one accommodation Santorin's ODS 5 authentication needs. The command line client and the MATLAB Toolbox name AVL Santorin explicitly in their connection documentation, setting a single authentication-string flag for it, and because pyHQL reaches the server through that same connection model, the same access applies in Python. Engineers get full self-made and custom analysis access, in Python or MATLAB, against a Santorin server, with results arriving as the same native objects they would get from any other ODS source.

The value of that access shows up most clearly in the words of the people using it. One engineer at a Santorin-based test operation, after HighQSoft set up this interface, described the experience this way.

No. HQL is HighQSoft's own query language, not part of the ASAM ODS standard. What makes it safe to adopt is that it is readable, inspectable, and translates directly into standard ASAM ODS API operations, while the data stays in a standard ODS repository that any ASAM-compliant tool can reach through the standard API at any time.

No. HQL exists specifically so that engineers do not have to learn the ODS API or the database schema. It loads the application model and lets you query using your organization's own element names in a syntax that reads like SQL, so anyone comfortable with a SELECT statement is productive quickly.

Yes. HQL connects to ASAM ODS 5 and ODS 6 servers, including third-party implementations, through its Java library, REST Web Service, and pyHQL. AVL Santorin is a concrete example, covered above, where HighQSoft enables full Python and MATLAB access using the same connection model HQL uses for any server, with one authentication-string flag for Santorin's ODS 5 authentication.

HQL can write as well as read. Beyond queries, it supports inserting, updating, and deleting instances, managing references and file attachments, and grouping changes into transactions, all through the ODS server so that access rights and model constraints stay enforced.

It is strongly discouraged. Direct SQL bypasses the ODS security and access-control layer, couples your queries to a private, per-customer physical schema that is not guaranteed to be stable, and often cannot even reach mass data, which frequently lives outside the relational tables. HQL runs against the server instead, which is why it stays safe and portable where raw SQL does not.

Yes. pyHQL delivers ASAM ODS Python access, and matHQL, the ASAM ODS Toolbox for MATLAB, delivers the MATLAB one, both running the identical HQL syntax used in the command line, in Java, and over REST.

HighQSoft offers several ways to move from reading about HQL to using it, at whatever level of commitment fits your team. Start free and hands-on by exploring the HQL query language product page and trying HQL interactively against sample data through pyHQL or the command line. When you are ready to see it on your own data, request a demo of HQL running against your application model, or for a full evaluation, work through HighQSoft's proof-of-concept guide for test data management. For a guided technical session on pyHQL, matHQL, or the HQL Web Service, contact HighQSoft directly. To see why this saves real development time and money, continue to how HQL democratizes ASAM ODS data access.