Load data into ClickHouse in minutes

Renta ELT writes data from 100+ sources into ClickHouse — self-hosted or Cloud.

Trusted by teams at

ClickHouse is an open-source columnar OLAP database built for millisecond-latency analytics on billions of rows.

Renta turns ClickHouse — self-hosted or ClickHouse Cloud — into your single source of truth by automatically pulling data from 100+ sources (ad platforms, CRMs, databases, SaaS tools), normalizing the schema and writing ready-to-query tables on the MergeTree engine family.

Marketing, product and data teams can focus on dashboards in Grafana, Superset or Metabase, funnel and retention analysis, and real-time reporting instead of maintaining homegrown ETL scripts.

Start loading data into ClickHouse in 3 steps

Pick any connector — ad platforms, CRMs, databases, SaaS — and authorize the account in a couple of clicks. No code, no servers to maintain.

Connecting a data source in Renta for loading into ClickHouse.

1Connect a source

Pick any connector — ad platforms, CRMs, databases, SaaS — and authorize the account in a couple of clicks. No code, no servers to maintain.

2Point Renta at ClickHouse

3Configure and sync

ClickHouse loading capabilities

Renta replicates data into ClickHouse with production-grade reliability — typed, normalized and backed by a 99.9% SLA.

Incremental sync

After the initial historical backfill Renta only writes new and changed records to ClickHouse. This reduces storage cost, source load and refresh latency — from 15-minute windows down to daily.

Automatic schema

Renta creates tables, assigns column types and tracks schema changes on the source side. When a new field appears in the API, a column is added to ClickHouse without breaking the pipeline.

Typing and normalization

Data types from every source are normalized to a single consistent format. Cross-source JOINs work without manual CAST or JSON parsing.

Upsert and deduplication

Renta uses ReplacingMergeTree with a version column and the source's natural keys to prevent duplicates. Records are updated by primary key, deletes are soft-flagged and retroactive changes are applied correctly.

Use cases

What teams build on top of ClickHouse data

Join GA4, ad platform and CRM data in ClickHouse to compute end-to-end CAC, LTV and ROMI per channel
Build attribution models (last-click, data-driven, Markov) on raw events and spend replicated by Renta
Run high-cardinality funnel, retention and cohort analysis at millisecond latency on billions of rows
Visualize data in Grafana, Superset, Metabase and Tableau straight from ClickHouse, with no manual exports
Blend financial data from Stripe, Paddle and billing databases with marketing spend for cohort-level P&L
Power real-time product and marketing dashboards — Renta refreshes data as often as every 15 minutes, ClickHouse returns results in milliseconds