Sherlock Calls
for ClickHouse + PostgreSQL
ClickHouse stores and queries high-volume event and operational data at scale. PostgreSQL stores your application's core operational data and business records. When you need to investigate across both, the evidence is split between two dashboards neither of which knows the other exists. Sherlock Calls bridges them — no code, no exports, no manual joins. Ask once from Slack and get a sourced answer in under 5 seconds.
TL;DR — What beta users get access to
- 1
Sherlock Calls connects to ClickHouse, PostgreSQL simultaneously — read-only, no code changes, no webhooks — and lets you query both with a single Slack message.
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Ask questions that neither ClickHouse nor PostgreSQL can answer alone. ClickHouse holds the raw source of truth — but querying it for business questions requires SQL access and data engineering resources. PostgreSQL holds every business record your app has ever created — but turning that into an answer requires a developer to write the query. Sherlock deduces the complete picture from both.
- 3
No dashboard switching, no manual joins, no fog of uncertainty — ask in Slack and receive a sourced answer with evidence from every connected provider in under 5 seconds. The game is afoot.
<5s
Answer to any database + database query
2
Connected platforms, 1 Slack question
0
Code changes or webhooks required
The Investigation Gap
What's invisible when you use ClickHouse + PostgreSQL without Sherlock
Each platform shows you its own data. But the questions that matter most live in the gaps between them.
ClickHouse and PostgreSQL each hold half the picture
ClickHouse holds the raw source of truth — but querying it for business questions requires SQL access and data engineering resources. PostgreSQL holds every business record your app has ever created — but turning that into an answer requires a developer to write the query. Without correlating both, your team sees two incomplete views of the same underlying reality — and every investigation stops at the boundary between systems.
Cross-platform cost and performance remain invisible
ClickHouse tracks its own query compute and storage cost. PostgreSQL tracks its own database infrastructure and query compute cost. Your true cost per outcome — and the performance of each component in your combined stack — requires data from both, but neither platform shows you that unified picture.
Critical events disappear at the boundary between systems
When a session, contact, or signal moves between ClickHouse and PostgreSQL, the transition is recorded with different identifiers in each system. Tracing what happens across the full journey requires a manual join that takes hours you don't have.
Cross-Provider Questions
What teams ask Sherlock about ClickHouse + PostgreSQL
Questions that would take hours to answer manually — answered in under 5 seconds from Slack.
- SC“What's the combined activity across ClickHouse and PostgreSQL in the last 7 days?”
- SC“Show me events that touched both ClickHouse and PostgreSQL in the last 24 hours”
- SC“What's our blended cost per outcome across ClickHouse and PostgreSQL this month?”
- SC“Which ClickHouse sessions had issues that correlate with PostgreSQL events this week?”
- SC“Compare performance metrics across ClickHouse and PostgreSQL for the past 30 days”
Beta Setup
Connect ClickHouse + PostgreSQL to Sherlock in 2 minutes
No code, no webhooks, no new dashboards. Beta users get direct onboarding support.
- 1
Connect ClickHouse
Add your ClickHouse credentials to Sherlock Calls. Read-only access — no code changes, no webhooks, no ClickHouse configuration required.
- 2
Connect PostgreSQL
Add your PostgreSQL credentials. Sherlock indexes all relational tables, business records, operational data, and application state automatically.
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Ask your first cross-provider question. The game is afoot.
Type any question about your combined ClickHouse + PostgreSQL stack in Slack. Sherlock queries all connected platforms in parallel, correlates the evidence, and returns a sourced answer in under 5 seconds.
FAQ
Common questions about Sherlock + ClickHouse + PostgreSQL
How does Sherlock Calls connect ClickHouse and PostgreSQL data?
- Sherlock uses read-only API access to both platforms simultaneously. When you ask a question, it queries ClickHouse, PostgreSQL in parallel, correlates the results by timestamp and shared identifiers, and produces a single sourced answer — the same way a good detective correlates evidence from multiple witnesses.
Do I need to set up any data pipelines between ClickHouse and PostgreSQL?
- No. Sherlock Calls is entirely pull-based — it queries both APIs on demand when you ask a question. There are no webhooks, no ETL pipelines, no data warehouses, and no code changes required in any of the connected platforms.
What kinds of questions can I ask about my ClickHouse + PostgreSQL stack?
- You can investigate anything that spans both platforms — query volume and event ingestion rate, table row counts and query latency, cross-platform costs, handoff patterns, and performance comparisons. Sherlock translates your plain-English question into the right API calls and returns the deduced answer.
Is my ClickHouse and PostgreSQL data stored by Sherlock?
- No. Sherlock Calls queries your data in real time and returns results directly to Slack — nothing is stored, indexed, or replicated in any Sherlock database. All data remains in ClickHouse and PostgreSQL and is accessed only during an active investigation.
How long does it take to set up the ClickHouse + PostgreSQL integration?
- Elementary — typically under 5 minutes total. Connect each platform with read-only credentials, install the Sherlock Calls Slack app, and ask your first question. No engineering, no dashboards, no onboarding calls required.
Apply for early access to Sherlock + ClickHouse + PostgreSQL
We're accepting a select group of beta users to shape the ClickHouse + PostgreSQL combination. Tell us about your stack and we'll reach out personally if you're a fit.
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