Cloudingo vs Splink
Cloudingo
cloudingo.comSplink
github.comSide by side
| Figure | Cloudingo | Splink |
|---|---|---|
| Price from | $208.33/mo | Free |
| Free plan | — | Yes |
| Free trial | Yes | — |
| Open source | — | — |
| Web | Yes | — |
| Linux | — | Yes |
| API | Yes | — |
| Self-hosted | — | Yes |
| Plans published | 3 | 1 |
| Spec score · Data Deduplication Software | 8.3 (#3) | 7.8 (#20) |
| Matching | Its deduplication tools support standard and custom objects, with more than 10 matching styles ranging from exact to fuzzy matching. | It supports term frequency adjustments and user-defined fuzzy matching logic. |
| Purpose | Cloudingo provides no-code tools to find, merge, and prevent duplicate Salesforce records and manage data quality. | Splink is a Python package for probabilistic record linkage that deduplicates and links records without unique identifiers. |
| Support | Cloudingo offers email support, a knowledge base with articles and videos, biweekly user webinars, and monthly training sessions. | The documentation directs users with questions to the project’s GitHub discussion forum. |
Plans
Cloudingo
- Standard$2,500 a year
- Professional$6,000 a year
- Enterprise$10,000 a year
In their own words
Splink
Splink is a free Python package for probabilistic record linkage: it deduplicates and connects records without unique identifiers. Its core algorithm is based on the Fellegi–Sunter model, and it can train models without training data using an unsupervised approach. Matching supports term-frequency adjustments and user-defined fuzzy logic. Interactive outputs help users inspect models and diagnose linkage problems. Splink documents DuckDB, Spark, PostgreSQL, and SQLite backends; DuckDB is installed by default, while Spark and PostgreSQL have optional installs. The project says it can run with big-data backends such as Spark on datasets of 100 million or more records, and can link a million records on a laptop in around a minute. It works best with standardised data containing multiple columns that are not highly correlated. Installation is through pip or conda and requires Python 3.10 or later. The project lists Linux and self-hosted use and an MIT license.