
DBeaver
DataGrip
Navicat
Beekeeper Studio
DbVisualizer
HeidiSQL
phpMyAdmin
Easily edit database data and structure

CSV Cleaner
Bulk Phone Normalizer
Clean Spreadsheets
CleanCSV AI
neatcsv
Insycle
MessyData.app
Clean messy spreadsheets in minutes. CleanSmart finds duplicates, fixes formatting, fills gaps, & finds anomalies automatically. No code required. Try it free.

Which is more popular?
Based on our record, TablePlus seems to be more popular. It has been mentioned 67 times since March 2021.
Website, pricing, platforms and company facts side by side.
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| Website | tableplus.com | cleansmartlabs.com |
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| Platforms | — | |
| Company | — | 1 - 9 employees · 2026 |
| Listed in |
In their own words, as submitted to SaaSHub.


No description of TablePlus yet.
Dirty data is a quiet disaster. Duplicate contacts, inconsistent formats, missing fields, & records across Mailchimp, HubSpot, Klaviyo, Shopify, and Salesforce -- most teams live with this mess because cleaning it properly requires hours of manual work nobody has time for. CleanSmart fixes...
What each product offers, as listed by its team.


Possible disadvantages
An editorial look at what each product does well and who it suits.


No analysis of TablePlus yet.
Overall verdict
Why this product is good
Recommended for
Walkthroughs and reviews on video.
09 - Instalar TablePlus en Mac
CleanSmart Demo - Full Cleaning Pipeline
How often each product is chosen within a category, 0–100% relative to the other.


As answered by people managing TablePlus and CleanSmart.
CleanSmart's answer:
Marketing Ops, RevOps, and SalesOps practitioners at growing businesses who manage customer data across multiple platforms and don't have a dedicated data engineering team. These are the people manually deduplicating CRM records, fixing formatting inconsistencies before a campaign send, and dealing with bounced emails from bad data. They know the problem is costing them time and revenue -- they just haven't had a tool built specifically for them.
CleanSmart's answer:
Most data cleaning tools make you run separate processes for separate problems -- one tool for duplicates, another for formatting, something else for missing values. CleanSmart handles all four in a single automated pass: semantic duplicate detection, format standardization, missing value prediction, and anomaly flagging. What makes that technically different is the confidence-based review layer -- high-confidence changes happen automatically, low-confidence ones get routed to you for approval. Nothing changes in your data without a full audit trail, and every decision is reversible.
CleanSmart's answer:
CleanSmart is built for the people who actually live with messy data -- Marketing Ops, RevOps, and SalesOps practitioners -- not data engineers. There's no code to write, no complex configuration, and no need to export and re-import files manually. It connects directly to HubSpot, Salesforce, Mailchimp, Klaviyo, and Shopify via OAuth and cleans your data where it already lives. The semantic duplicate detection catches matches that traditional string matching misses -- "Jon Smith" and "John Smith" at the same company get flagged, not treated as two separate contacts. And the human-in-the-loop review workflow means you stay in control of every change the AI makes.
CleanSmart's answer:
CleanSmart was built by William Flaiz, a digital transformation executive with 20+ years of enterprise software and MarTech consulting experience. After repeatedly watching businesses lose revenue to data they couldn't trust -- duplicate leads, inconsistent formats, records scattered across disconnected systems -- and spending countless hours cleaning that data manually before it could be useful, he built the tool he kept wishing existed. The product went from concept to working beta in four months, built with AI-assisted development and informed by direct feedback from RevOps and MarOps practitioners who shaped its core features.
CleanSmart's answer:
CleanSmart is built on a React and TypeScript frontend with a FastAPI Python backend. The AI capabilities use sentence-transformers for semantic similarity matching and scikit-learn for anomaly detection and missing value prediction. Data is stored in PostgreSQL in production. Platform integrations connect via OAuth 2.0. The infrastructure runs on DigitalOcean.
Share your experience with using TablePlus and CleanSmart. For example, how are they different and which one is better?
External articles and on-site reviews we used to compare the two products.


If you want a commercial tool for modeling and admin, Navicat fits. And if you mostly need a fast Postgres DB viewer to browse and edit, TablePlus or the free, open-source Beekeeper Studio will do the job nicely....
Daily SQL development: Heavy authoring rewards a full IDE; occasional lookups are better served by lightweight PostgreSQL interactive query tools such as TablePlus or Beekeeper Studio.
The best SQL GUI is the one that fits your team’s work. If you need to work with multiple database platforms, dbForge Edge has one of the most complete feature sets. DBeaver is great for mixed database environments ....
We have no reviews of CleanSmart yet. Be the first one to post
Recommendations tracked on public social media and blogs since March 2021.


TablePlus is a polished native database client known for speed, clean design, and direct data editing. It supports relational databases such as MySQL, PostgreSQL, SQLite, and others, with apps across macOS, Windows, Linux, and iOS. - Source: dev.to / 5 months ago
Best part? It’s standard Postgres. Any tool that speaks Postgres can connect, TablePlus, Retool, Cloudflare Hyperdrive, pgAdmin, even other ORMs. - Source: dev.to / 11 months ago
If you want something sleeker than DBeaver, TablePlus is a beautiful database client. Its free tier is limited but plenty for small dev projects. - Source: dev.to / about 1 year ago
Tracking CleanSmart since Apr 2026.
When comparing TablePlus and CleanSmart, you can also consider the following products.

DBeaver - Universal Database Manager and SQL Client.
Compare DBeaver to TablePlus or CleanSmart:



Clean messy CSV phone columns before CRM, dialer, or API import. Convert safe rows to E.164, preserve the rest of your data, and split risky numbers into a needs-review file in your browser.
Compare Bulk Phone Normalizer to TablePlus or CleanSmart:

Powerful database management & design tool for Win, Mac & Linux. With intuitive GUI, user manages MySQL, MariaDB, SQL Server, SQLite, Oracle & PostgreSQL DB easily.
Compare Navicat to TablePlus or CleanSmart:
Automatically clean customer data with a few clicks
Compare Clean Spreadsheets to TablePlus or CleanSmart: