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Elevarq Analyzer 1.0 is here.Book a demo →

For teams running production PostgreSQL

Keep PostgreSQL problems from becoming production incidents.

Performance and reliability problems build up quietly in PostgreSQL, and most teams have no senior database expert on hand. Elevarq is a senior PostgreSQL assessment on demand: it finds the risks, explains them, and prepares fixes your team reviews and ships.

For example, a checkout query quietly slowed by a missing index: Elevarq shows the evidence and the exact, reviewable fix before it becomes a customer-facing slowdown. (Illustrative.)

Read-only, in your own environment — Elevarq proposes the fix, your team decides. See how the platform fits together ↓

Works with the PostgreSQL you already run — self-managed or managed (Amazon RDS, Google Cloud SQL, Azure). See compatibility.

From raw database to a fix your team ships

Who it's for

Elevarq is built for the teams who operate PostgreSQL — and it speaks to each of them in their own terms.

CTOs & CIOs

De-risk PostgreSQL operations without growing a DBA org. Evidence-grounded triage, lower incident risk, and a read-only, airgap-friendly posture.

See the business case →

DevOps, platform & SRE

A dashboard shows a line moving and leaves you to guess what it means. Elevarq tells you what to change — every finding lands as a ready-to-ship ticket in GitHub, GitLab, Jira, or Linear, with the evidence, the fix, and the rollback attached.

See how findings become tickets →

Developers who own the database

Elevarq is the senior-database read your team can act on — it does the investigation and explains what to change, why, and how, in language any engineer can use.

Explore Analyzer →

Already have DBAs? Elevarq changes their work rather than replacing it — see the DBA transformation on the Analyzer page.

What a finding looks like

Before the architecture: this is the actual output. Analyzer turns database evidence into a reviewed, ready-to-ship fix — problem, why it matters, the evidence, and the exact change.

Sample finding · rule indexes.missing.v1

Missing index candidate on public.events.user_id

Severity: mediumConfidence: 0.85

Problem

Frequent sequential scans on public.events filter on user_id. The evidence indicates that this access pattern is worth an operator's review.

Why it matters

This query is on the hot read path and runs frequently. Current execution wastes shared-buffer cache on rows that the predicate then discards. The gap widens as public.events grows; addressing it now is cheap and reversible.

Evidence

  • queryid = 0xab12cd34
  • calls = 1,247,392 over 24 hours
  • mean_exec_time_ms = 11.7
  • Source refs: indexes.missing.v1, table=events, column=user_id

Recommended action

Create a single-column index on user_id. Use CONCURRENTLY so the build does not block writes onpublic.events; note that CREATE INDEX CONCURRENTLY cannot run inside a transaction (a common gotcha for migration tools that wrap each statement by default).

CREATE INDEX CONCURRENTLY idx_events_user_id
  ON public.events (user_id);

An illustrative finding. Your team reviews it and ships the change — Elevarq never touches your production database.

Evaluate Analyzer on your terms

See exactly what Analyzer produces before you talk to anyone. Every path is read-only and self-hosted — Elevarq never touches your production database and sends no telemetry.

Start here

See a sample finding

Inspect a full Analyzer finding — the evidence it gathered, the reasoning, the confidence, and the exact recommended change your team reviews and ships.

Run Signals locally

Download the read-only Signals collector and point it at a PostgreSQL you can reach. It captures a diagnostic snapshot — nothing leaves your environment. Prerequisites and the exact next step are in the release notes.

Download Signals →

Book a technical review

Evaluating Analyzer for a team? Walk through your PostgreSQL estate and a real finding with us — a working technical conversation, not a sales pitch.

Book a technical review →

How the pieces fit

One flow, end to end: Signals collects read-only evidence from your PostgreSQL; the Elevarq image — Analyzer, Insight, and Workbench in one — diagnoses, explains, and presents it; your team reviews and ships the fix.

PostgreSQL
Signals
Elevarq(Analyzer + Insight + Workbench)
Your team

The products

Each does one job. Together they take a snapshot from evidence to a shipped fix.

Anatomy of a finding
ProblemEvidenceRecommended action
PostgreSQL Diagnostics · FlagshipCommercial

Elevarq Analyzer

Understand why PostgreSQL performance changes over time. Analyzer turns a Signals snapshot into evidence-grounded findings a reviewer can act on — a senior-DBA-grade read of the database, written for any engineer.

Explore Analyzer
Elevarq Signals architecture: read-only collection from PostgreSQL targets into local snapshots
PostgreSQL DiagnosticsOpen source

Elevarq Signals

Collect PostgreSQL evidence safely using a read-only collector — snapshots of execution stats, wait events, and configuration state, with no writes and no telemetry to Elevarq. Free on GitHub and AWS Marketplace.

Explore Signals
Review to ticket
ReviewApprovePush
PostgreSQL Diagnostics

Elevarq Workbench

Set up your databases and trackers once, then work in the tools you already use. Each finding arrives as a complete, ready-to-ship ticket in GitHub, GitLab, Jira, or Linear — reviewed and shipped in your team's normal ticket workflow.

See the workflow

What's open source, what's commercial

The collector and the base pooler are free and production-ready. The commercial products are the operational layers built around them.

Open source

Free · production-ready

Inspect the code, run either standalone against any PostgreSQL — no license, no phone-home. Get Signals from GitHub releases or free on AWS Marketplace.

Commercial

Runs in your environment

Offline-activated licenses, airgap-capable. Your data never leaves your environment.

The commercial products don't fork the open ones — fixes to the open collector and pooler go upstream. See the security page for the data-boundary model.

Works with the tracker you already use

Every finding becomes a ticket in the system your team already runs on. Elevarq integrates with GitHub, GitLab, Jira, and Linear — the fix lands where your team already works.

  • GitHub
  • GitLab
  • Jira
  • Linear

GitHub, GitLab, Jira, and Linear are trademarks of their respective owners. Elevarq is not affiliated with, or endorsed by, them.

Start with the flagship, or the free collector.

Explore Analyzer to see how a snapshot becomes an implementable ticket, or download Signals and point it at your own database.

Not sure where to start? talk to us.