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Data Lakehouse · Rank #9 of 10

Dremio review and pricing

Lakehouse-native query engine on Iceberg with Project Nessie Git-for-data catalog.

By Dremio Corporation · Founded 2015 · Santa Clara, CA · private

Dremio is the lakehouse-native query engine purpose-built for SQL on Apache Iceberg tables in S3/ADLS/GCS, with Project Nessie as the Git-for-data catalog. The fit: teams that want to separate storage from compute vendor, run their data in Iceberg in their own object store, and use Dremio as the engine without committing to Databricks or Snowflake compute. Series E $410M raised in Jan 2022 at $2B+ valuation; no significant funding rounds publicly disclosed since. Strengths: Iceberg-first engineering, Nessie data versioning, and reflections (acceleration layer) for sub-second BI. Trade-offs: smaller market presence than Databricks/Snowflake, narrower ecosystem.

Visit Dremio Vendor pricing Compare to Apache Hudi + Onehouse
Best for

Engineering-led teams (100-5,000 employees) committing to Iceberg lakehouse architecture who want to separate storage from compute vendor and use a query engine outside the Databricks/Snowflake duopoly.

Worst for

Buyers wanting fully managed integrated lakehouse + ML platform (Databricks), heavy AI/ML training shops, or teams without dedicated data engineering capacity.

Vendor Trust Score

Is Dremio a trustworthy vendor?

7.8/10
Mixed
Pricing transparency
Published rates; no hidden fees
6.5
Contract fairness
Reasonable terms; no auto-renew traps
8.0
Incident response
How they handle outages and breaches
8.0
Post-acquisition behavior
Customer treatment after M&A or PE
8.5
Executive stability
Leadership churn over 24 months
8.0
Roadmap honesty
Public commitments held
8.0
Trust signal log
  • 2022-01-25
    Series E $410M raised at $2B+ valuation
  • 2024-09-10
    Reflections 2.0 and Nessie GA in Dremio Cloud
  • 2025-11-04
    No new significant funding round disclosed since 2022
Vendor Trust is scored independently of product quality. A great product from an unfair vendor still earns a low trust score.
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Editorial: Strengths

  • Iceberg-first lakehouse query engine
  • Project Nessie for Git-for-data versioning and branching
  • Reflections (materialized view acceleration) for sub-second BI
  • Apache Arrow-based engine with strong query performance
  • Bring-your-own-cloud and bring-your-own-object-store model

Editorial: Weaknesses

  • Smaller market presence than Databricks or Snowflake
  • No significant funding round publicly disclosed since 2022
  • Narrower BI and partner ecosystem than the leaders

Key features & integrations

  • +Iceberg-native query engine
  • +Project Nessie (Git-for-data catalog)
  • +Reflections (materialized view acceleration)
  • +Apache Arrow-based execution
  • +Lakehouse semantics: ACID, time travel, branching
  • +SQL over S3/ADLS/GCS
80+ integrations
Apache IcebergProject NessieTableauPower BIdbtAWS S3ADLS
Geography supported
Global
Best fit
100-5,000+ employees · Engineering-led lakehouse teams
Vendor trust

Dremio trust score

6-dimension scorecard, dated, separate from product quality.
Worst for

Who shouldn’t buy Dremio

Editorial verdict on the buyers it’s the wrong fit for.
Alternatives

Dremio alternatives, ranked

9 independent picks from the same category.
Editorial deep-dive

Read our full ranking of Data Lakehouse

Dremio ranks #9 in our editorial review of 10 data lakehouse platforms. The deep-dive covers methodology, comparison tables, decision matrix, migration scoring, and FAQs.

Read the full ranking

Closest alternatives in Data Lakehouse

#8
Apache Hudi + Onehouse
Streaming-first open table format from Uber, with Onehouse as commercial managed offering.
★ 4.3 partial
#10
Starburst
Managed Trino with multi-format lakehouse support and Stargate federation.
★ 4.4 partial
#7
Delta Lake
Databricks-led open table format with Iceberg interop via Delta UniForm.
★ 4.5 public
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