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informix-driver

WTF did you build this for?

The existing tools were not my style.

Every Informix driver in any language wraps either IBM’s C Client SDK or the JDBC JAR. That covers IfxPy, the legacy informixdb, ODBC bridges, JPype/JDBC, and Perl’s DBD::Informix. To our knowledge informix-driver is the first pure-socket Informix driver in any language.

The problem with IBM’s C SDK

Section titled “The problem with IBM’s C SDK”

The IBM Informix Client SDK (CSDK), now packaged as part of OneDB Client, is a 92 MB tarball with a non-trivial install gauntlet:

  • Python ≤ 3.11 (IfxPy is broken on 3.12+)
  • setuptools < 58 (legacy build system)
  • Permissive CFLAGS for the C extension build
  • Manual download of the 92 MB ODBC tarball
  • Four LD_LIBRARY_PATH directories
  • libcrypt.so.1, deprecated in 2018 and missing on Arch, Fedora 35+, RHEL 9

For containerized deployments, ETL pipelines, FastAPI services, or anywhere Python lives and IBM’s C SDK is friction, the friction compounds. informix-driver’s install is pip install informix-driver (import informix_db; the distribution name dodges PyPI’s 2008-vintage informixdb package, while the import name is what you’d expect). The wheel is ~50 KB. There are zero runtime dependencies.

What it does

Section titled “What it does”

informix-driver opens a TCP socket to an Informix server’s SQLI listener and speaks the wire protocol directly. It is the same protocol IBM’s JDBC driver uses, and the same one the CSDK speaks under the hood. No native code is in the thread of execution.

The wire protocol was reverse-engineered through three sources:

  1. Decompiled IBM JDBC driver (com.informix.jdbc.IfxConnection and friends), used as a clean-room reference for PDU shapes and protocol semantics.
  2. Annotated socat captures of real client/server traffic against the IBM Informix Developer Edition Docker image.
  3. Differential testing against IfxPy, so every codec path is checked against the C driver’s behavior on the same data.

The result is a PEP 249 compliant driver with a sync API, an async API (FastAPI / asyncio compatible), a connection pool, TLS support, smart-LOB read/write, scrollable cursors, fast-path stored procedure invocation, and bulk-insert / bulk-fetch performance within ~10–60% of the C driver depending on workload.

What it’s good for

Section titled “What it’s good for”

The places where informix-driver is unambiguously the right choice:

  • ETL and bulk-load pipelines. Pipelined executemany (Phase 33) is 1.6× faster than IfxPy at scale because every BIND+EXECUTE PDU goes out before any responses are drained. IfxPy still pays one round-trip per IfxPy.execute(stmt, tuple) call.
  • Container deployments. The 50 KB wheel and absent native deps mean a slim base image works. No multi-stage build to compile the CSDK.
  • Modern Python. Works on 3.10 through 3.14 unmodified. IfxPy hasn’t shipped 3.12 wheels.
  • Async / FastAPI. Native async support via thread-pool wrapping. IfxPy is fully synchronous; using it from FastAPI requires run_in_executor boilerplate and gives up the connection pool’s natural async semantics.
  • Anywhere libcrypt.so.1 is missing. Modern Linux distributions ship libcrypt.so.2. IfxPy refuses to load without libcrypt.so.1. We don’t link against either.

What IfxPy is still better at

Section titled “What IfxPy is still better at”

Honesty matters here:

  • Large analytical fetches. IfxPy’s C-level fetch_tuple decoder is faster than our Python parse_tuple_payload (~1.1 µs/row vs ~2.0 µs/row after Phase 39). For workloads pulling 10k+ rows in a single SELECT where the per-row decode cost dominates, IfxPy is currently 5–15% faster. The gap is shrinking phase by phase.
  • Workloads built around the CSDK. If your existing code already uses IfxPy idioms (IfxPyDbi.connect_pooled, IBM’s specific cursor extensions), the migration to informix-driver is straightforward but not zero-cost.

The honest summary table from the comparison page:

WorkloadWinnerMargin
Bulk insert (executemany 10k–100k rows)informix-driver1.6× faster
Bulk SELECT (10k–100k rows)IfxPy1.05–1.15× faster
Single-row queriestiedwithin noise
Cold connecttiedwithin noise
Containerized deploymentinformix-driverno contest
Python 3.12+informix-driveronly option

Production-ready

Section titled “Production-ready”

Every finding from a system-wide failure-mode audit (data correctness, wire safety, resource leaks, concurrency, async cancellation) has been addressed:

  • Pool no longer returns connections with open transactions
  • Per-connection wire lock prevents PDU interleaving from accidental sharing
  • Async cancellation cannot leak running workers onto recycled connections
  • _raise_sq_err no longer masks wire desync via bare-except
  • Cursor finalizers release server-side resources on mid-fetch raise
  • 5 medium-severity hardening items resolved

0 critical, 0 high, 0 medium audit findings remain. Every architectural change went through a Margaret Hamilton-style review focused on silent-failure modes, recovery paths, and documented invariants. Each documented invariant is paired with either a runtime guard or a CI tripwire test.

470+ tests across unit / integration / benchmark suites. The integration suite runs against the official IBM Informix Developer Edition Docker images and passes 472/472 on 15.0.1.0.3DE and 14.10.FC7W1DE, and 471/472 on 12.10.FC12W1DE (the single skip is a common table expression, which 12.10 predates). make test-matrix runs the lot.

That matrix exists because it turned out to be needed. A user reported corrupted result sets on Informix 12; the cause was three framing bugs that affected every version including the one we tested against, and they’d survived because no fixture used the affected types. Testing one server and inferring the rest is how that happens.

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