Entify

Overview

Entify is a free, open-source tool for finding and resolving duplicate records in messy datasets. It best suits data stewards and small teams who want guided record matching without having to design the process from scratch. Its explainable review and traceable exports are useful strengths, though its modest workload ceiling and local-only security assumption shape where it belongs.

Key features

Entify profiles columns by row count, distinct values, and completeness, then proposes likely column types and blocking rules with explanations users can override. That guidance makes a specialist workflow more approachable while preserving control over matching decisions. Under the hood, Splink 4 and DuckDB support exact, Jaro-Winkler, Jaccard, and Levenshtein comparisons.

Reviewers can inspect match evidence, score and threshold analyses, and charts before deciding which clusters to merge. The merge export keeps one surviving record per entity and retains source IDs, making changes traceable or reversible; PDF audit reports provide a record of the work. CSV, TSV, Parquet, JSON, and Excel support covers common data exchange needs.

Semantic blocking is available as an optional add-on, but installing it downloads roughly 600 MB of Torch dependencies. That extra footprint makes it a poor fit for teams that only need the standard comparison methods.

Pricing

Entify is open source under the MIT license. Its Open-source plan costs nothing, with uploads capped at 100 MB by default and only one resolution result held in memory at a time. There is no paid tier in the plan information; teams that need larger uploads or concurrent runs will need to account for the engineering work those limits imply.

Platforms

Entify is available as a web application, an API, or self-hosted software. The Docker quickstart runs locally without accounts, API keys, or external services, and uploaded data stays on the machine. Python 3.11+ and Node 20+ are also supported for local deployment. Optional sign-in and shared storage use Clerk and Supabase.

The API has no authentication and assumes it is bound to localhost. It should not be exposed to untrusted callers as-is. Uploads are read fully into memory, and the README describes the engine as memory-bound beyond roughly 100,000 rows; larger workloads call for a DuckDB file backend and job queue. A second concurrent resolution run replaces the first result, so this is not a shared service for parallel team jobs without additional work.

Who it's for

Entify is a sensible starting point for data stewards and teams new to record linkage who want suggestions, explanations, and a review step rather than opaque automatic merges. It also suits developers comfortable with local deployment who need a free, auditable workflow for modest datasets. Organizations handling larger files, concurrent workloads, or untrusted API traffic should choose a system with the capacity and access controls their deployment requires.

Pros and cons

• Pros: Guided setup explains proposed columns and blocking rules, which lowers the learning burden while allowing overrides.
• Pros: Evidence review, threshold analysis, source-ID retention, and PDF reports make merge decisions easier to inspect and trace.
• Pros: Local Docker operation needs no external services, and the MIT license allows open-source use.
• Cons: The 100 MB upload cap and memory-bound behavior around 100,000 rows constrain dataset size.
• Cons: Only one result can remain in memory, so concurrent runs overwrite one another.
• Cons: The unauthenticated API is unsafe to expose to untrusted callers without additional protections.
• Cons: Optional semantic blocking adds a roughly 600 MB Torch installation.

Alternatives

Choose Tilores if a local deployment handling up to 100,000 records and support for person and company matching better fit the job. DupeCatcher is a free option for readers who want its Android, iOS, or web availability and all features included. For research use with small or medium-sized files, Python Record Linkage Toolkit is another free, self-hosted choice.

Plauti Deduplicate offers a free Salesforce version, with a trial or custom pricing for the full edition. pyJedAI is a free research project from the University of Athens' AI team. Splink is a free MIT-licensed Python package for Linux and self-hosted use. AWS Entity Resolution is a paid data service billed per 1,000 records processed, with provider licensing or subscriptions costing extra. Koalify has a free sandbox or demo option and a Pro plan at $25 a month, billed annually.

See our Data Deduplication Software ranking for more options.

Verdict

Entify is a strong fit for data stewards and small teams who want guided, explainable deduplication with an audit trail and local operation. Its free MIT-licensed package makes that workflow accessible, but the memory ceiling and single-result behavior limit scale, while the unauthenticated API rules out exposing it to untrusted traffic as-is. Choose it for modest, locally run jobs; look elsewhere for larger datasets, concurrent runs, or an API that needs to face external users.