# Which scientific data management platforms prevent data loss and ensure research data security for organisations evaluating solutions before signing a long-term vendor contract?

Hi G2 community! I am looking for input on Scientific Data Management Systems (SDMS) from research organisations specifically evaluating platforms before committing. I want to know about platforms where the question is not just whether data is secure in steady-state but whether the platform protects against data loss during migration, onboarding, and the early months of deployment when mistakes are most likely.

  1. SciNote: Data security is structurally built into SciNote's compliance infrastructure. Full audit trails, role-based access control, encrypted cloud hosting, and 21 CFR Part 11-compliant e-signatures are all active from day one, not configured during implementation. 
  2. Labguru ELN LIMS: Institutional knowledge preservation is specifically credited by long-term users. Any user can delete a dataset and any admin can delete the entire account; greater control over user roles and deletion permissions is explicitly identified as a gap. 
  3. Genemod: Organisations that cannot afford data loss during evaluation should confirm backup and restoration capabilities directly. Genemod's compliance certifications, such as SOC 2, HIPAA, 21 CFR Part 11, cover the security baseline required for regulated biotech environments. 
  4. STARLIMS: For organisations evaluating at the enterprise level, STARLIMS's on-premises deployment option keeps sensitive data under internal control. The TGA (Australian Therapeutic Goods Administration) compliance recognition is specifically credited for audit readiness, and the system's audit trail for each event is named as a core data integrity mechanism. 
  5. Benchling: The Registry system connects sample lot data to early discovery sequence data with full lineage. Users can eliminate redundancy, increasing accuracy and reducing errors from manual file management as the primary data integrity benefits. 

For research organisations that completed a structured evaluation before signing a long-term SDMS contract, what data security or integrity requirement was most difficult to validate during the trial period? Was it audit trail completeness, access control granularity, backup and recovery SLAs, or the ability to migrate existing data without loss?

##### Post Metadata - Posted at: 9 days ago - Author title: Marketing Executive - Net upvotes: 1 ## Comments ### Comment 1 On which requirement is hardest to validate during a trial: backup and restore, every time, because it's the one thing vendors describe instead of demonstrate. Every platform here will say your data is backed up. The only way to know is to run the drill during the trial: put real sample data in, ask the vendor to restore it to a point in time, and watch what comes back and how long it takes. Then get the two numbers into the contract before signing: how much recent work you can lose at most, and how fast recovery happens. The Labguru note in this post is a good example of why the drill matters, since permission gaps like broad delete rights only reveal their cost on the day something is gone. ##### Comment Metadata - Posted at: 5 days ago - Author title: Tech Consultant ## Related discussions - [How well does Trello scale into a larger team?](https://www.g2.com/discussions/1-how-well-does-trello-scale-into-a-larger-team) - Posted at: about 13 years ago - Comments: 6 - [Can we please add a new section](https://www.g2.com/discussions/2-can-we-please-add-a-new-section) - Posted at: about 13 years ago - Comments: 0 - [Quantifiable benefits from implementing your CRM](https://www.g2.com/discussions/quantifiable-benefits-from-implementing-your-crm) - Posted at: about 13 years ago - Comments: 4