Code Airlock vs sqlsure

Detailed side-by-side comparison to help you choose the right tool

Code Airlock

🔴Developer

developer-tools

A thin CLI wrapper around Docker Sandboxes that runs Claude Code, Codex, or OpenCode in a disposable microVM against a clone of your repo, then brings the work back as ordinary git commits for review.

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Starting Price

$0 (self-hosted)
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sqlsure

🔴Developer

developer-tools

A deterministic semantic checker that catches silently-wrong AI-generated SQL — double-counted joins, summed averages, exposed PII — in 0.1 ms before the query runs, with machine-actionable fixes.

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Starting Price

$0 (self-hosted)
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Feature Comparison

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FeatureCode Airlocksqlsure
Categorydeveloper-toolsdeveloper-tools
Pricing Plans1 listed plan1 listed plan
Starting Price$0 (self-hosted)$0 (self-hosted)
Key Features
  • • Runs coding agents in disposable Docker Sandbox microVMs, a boundary below the agent process rather than inside it
  • • Clone mode by default: the agent works in a private clone while your host repo stays read-only
  • • One-command task runs (code-airlock run "...") using each agent's non-interactive mode
  • • Deterministic semantic verdicts in ~0.1 ms, before the query runs — same SQL plus same rulebook always yields the same result
  • • Catches silent correctness bugs: FANOUT and CHASM join double-counting, summed averages (ADDITIVITY), semi-additive balance sums, undeclared/keyless joins, cross joins, re-weighted AVGs, and PHI/PII exposure
  • • Machine-actionable fix on every rejection, enabling agent self-repair loops (draft, check, fix, check, execute)

Code Airlock - Pros & Cons

Pros

  • ✓Real security boundary at the microVM level — not just agent-side prompts
  • ✓Host repo stays read-only; every change comes back as a reviewable git commit
  • ✓Multi-agent: swap between Claude Code, Codex, OpenCode with one flag
  • ✓Sandbox never needs GitHub creds — PRs push from the host
  • ✓MIT licensed with npm/Homebrew/curl installs and preflight `doctor` diagnostics

Cons

  • ✗Requires Docker Sandboxes and KVM/virtualization on the host
  • ✗No MCP integration — wraps agents but doesn't extend their tool surface
  • ✗Extra latency vs. running the agent directly on the host
  • ✗Small project (thin wrapper) — you're also depending on the underlying sbx CLI
  • ✗Adds cognitive load: another layer between you and the agent

sqlsure - Pros & Cons

Pros

  • ✓Deterministic, sub-millisecond judgments make sqlsure viable inside a per-query agent gate
  • ✓Zero-config rulebook derivation from existing dbt tests — no new metadata to author
  • ✓Machine-actionable fixes make self-repair loops work end-to-end, not just error out
  • ✓Fully offline with no telemetry and no database connection required
  • ✓External benchmark on Spider/BIRD (45 flags, 0 false alarms) is unusually credible for an OSS tool

Cons

  • ✗Coverage is nine rules — real correctness bugs outside those categories will still ship
  • ✗Requires a semantic layer (dbt tests, PK/FK, OSI, or MDL) — without one, sqlsure returns 'can't verify' for most cases
  • ✗PHI/PII rule matches on declared sensitive columns; unlabeled sensitive columns won't be caught
  • ✗Python-only runtime; teams on Node or Go stacks need a subprocess boundary
  • ✗Pre-1.0 project with a small maintainer team — support model is community-only

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Review Code AirlockReview sqlsure