Customer Recovery Records

Real PostgreSQL Data Recovery Cases

Organized by real recovery incidents across unwanted updates, TRUNCATE, file damage, ransomware, and domestic PG-compatible systems. Each case focuses on environment, challenges, recovery path, and validation.

350,000 Rows Recovered After a Large-Scale Accidental Data Deletion
DELETE
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1DELETEHealthcare industry customerDELETEPostgreSQL 17No WAL archivingDatabase stopped promptly

350,000 Rows Recovered After a Large-Scale Accidental Data Deletion

At around 14:00 on a weekend, more than 95% of the rows in a PostgreSQL 17 table at a healthcare organization were accidentally deleted, leaving only a few thousand of roughly 380,000 rows. WAL archiving was not enabled, but the customer stopped the database service immediately after discovering the incident. Analysis began close to 16:00 and found about 350,000 usable DELETE records still present in pg_wal. PDU recovered the data and completed import and validation in about three hours.

Environment
PostgreSQL 17 / healthcare
Scale
About 380,000 rows reduced to a few thousand
Result
About 350,000 rows recovered, imported, and validated

Main Timeline

1
Accidental deletion
Around 14:00

A large-scale DELETE removed more than 95% of the target table, leaving only a few thousand of roughly 380,000 rows.

2
Service stopped
After discovery

Because the incident occurred on a weekend, the customer could stop the database immediately and preserve the site after discovering the abnormal row count.

3
Incident reported
Close to 16:00

Nearly two hours had passed since the accidental operation, and the remaining WAL was assessed for recovery value.

4
Site assessed
Analysis started

The site was confirmed to run PostgreSQL 17 without WAL archiving, so an archived-WAL point-in-time recovery path was unavailable.

5
WAL inspected
During analysis

The pg_wal range around the accidental deletion was inspected, confirming that the relevant WAL segments were still present.

6
Records identified
During analysis

About 350,000 usable DELETE records were identified in the remaining WAL, far more than initially expected.

7
Recovery executed
Recovery stage

PDU parsed the relevant WAL, reconstructed the pre-deletion data, and prepared importable results.

8
Imported and validated
Completed in about 3 hours

About 350,000 rows were recovered and imported. Row-count and usability checks passed, and the customer confirmed the result.

Situation
  1. 1A healthcare industry customer was running PostgreSQL 17, and the target table originally contained roughly 380,000 rows.
  2. 2At around 14:00 on a weekend, a large-scale accidental deletion removed more than 95% of the data and left only a few thousand rows.
  3. 3WAL archiving was not enabled, and recovery analysis began close to 16:00.
Constraints
  1. 1DELETE does not immediately erase the original rows from heap pages, but deleted tuples can later be pruned and cleaned.
  2. 2The deletion volume was far above a normal autovacuum threshold, so continued database activity would progressively reduce the recovery window.
  3. 3Without archived WAL, the recoverable amount depended on how many usable DELETE records remained in pg_wal.
Recovery Path
  1. 1The customer stopped the PostgreSQL service immediately after discovering the incident to avoid further changes to the site.
  2. 2The pg_wal range around the incident was inspected to locate DELETE records that were still present.
  3. 3PDU parsed the relevant WAL and reconstructed the pre-deletion data.
  4. 4The recovered results were imported into the database and validated for row count and usability.
Validation
  1. 1About 350,000 usable DELETE records were found in pg_wal.
  2. 2About 350,000 of the roughly 380,000 affected rows were ultimately recovered.
  3. 3Recovery took about three hours from the start of analysis; the data was imported, validated, and confirmed usable by the customer.
Engineering note: The absence of WAL archiving does not always make recovery impossible, but the recovery ceiling depends heavily on whether the site continues running. Because this incident occurred on a weekend, the customer could stop the database service immediately, limiting further business writes and background activity and preserving the WAL needed to recover about 350,000 rows.
2DROP DATABASEChina manufacturing customerDROP DATABASENo recent backupPostgreSQL 18Core table recovery

Core Tables Recovered After a PG18 Production Database Was Dropped

A user confused test and production connections in pgAdmin and dropped a critical production database. With only a year-old logical backup available, PDU scanned the disk and preserved remaining pages within one hour, then recovered all 24 requested core tables.

Environment
PostgreSQL 18 / 256 tables
Result
24 customer-selected core tables
Result
24/24 recovered and imported

Main Timeline

1
Incident reported
17:26

The customer reported that test and production connections had been confused in pgAdmin, leading to DROP DATABASE being run against the PG18 production database.

2
Site protected
17:30

No database operations had been performed after the incident, and the disk was kept unchanged to avoid overwriting remaining data pages.

3
Scope confirmed
17:40

The scope was confirmed as 256 production tables with only a year-old logical backup, and 24 core tables were prioritized for recovery.

4
Disk scan started
17:50

Physical disk scanning began for remaining database pages without relying on the now-invalid database directory or catalog mappings.

5
Image assembled
Before 18:26

Pages related to the dropped database objects were collected into one ISO page-image file, moving subsequent analysis away from the original disk.

6
Image checked
18:30

The readable range and page distribution in the image were checked, confirming that table identification and fragment assembly could proceed.

7
Tables identified
19:00

Using table structures and the old logical backup, each requested core table was identified inside the ISO page image.

8
Fragments assembled
19:00–20:30

Matched data pages were classified and assembled in order, producing importable table data throughout the recovery.

9
Recovery completed
20:30

All 24 core tables requested by the customer were recovered and moved into result validation.

10
Results compared
20:30–21:30

Recovered results were compared with the year-old logical backup, and table-level recovery status and delivery lists were prepared.

11
Report delivered
21:30

A complete recovery report and importable data were delivered, closing the same-day workflow from site preservation to delivery.

12
Production validation
After recovery

The recovered data was imported into the on-site production database and the customer confirmed normal operation of the core business workload.

Situation
  1. 1The critical production system ran PostgreSQL 18 with 256 tables, and the customer prioritized 24 core tables for recovery.
  2. 2The user had both test and production connections open in pgAdmin and ran DROP DATABASE against production after confusing the two connections.
  3. 3Only a year-old logical backup was available, so conventional backup restoration could not return the database to its pre-incident state.
Constraints
  1. 1After DROP DATABASE, the target database and its objects were no longer accessible through normal database directories or catalog mappings.
  2. 2No usable recovery material was available other than the year-old logical backup.
  3. 3Remaining disk pages had to be preserved quickly before offline identification could begin.
Recovery Path
  1. 1Kept the site unchanged after the incident and started disk scanning immediately.
  2. 2Collected remaining pages related to dropped objects into one ISO page-image file so later analysis did not require continued reads from the original disk.
  3. 3Consolidated fragments inside the image and identified and recovered each requested core table from its structure.
  4. 4Used the year-old logical backup as comparison material and produced a recovery report with importable data.
Validation
  1. 1All 24 core tables requested by the customer were recovered.
  2. 2The results were compared with the year-old logical backup, and a complete report was delivered at 21:30 the same day.
  3. 3After import into the on-site production database, the customer confirmed normal business use.
Engineering note: No further operations were performed after DROP DATABASE, and remaining disk pages were preserved within one hour. This retained the key conditions for table-by-table identification; without a recent backup, the speed of site preservation directly affects the recovery ceiling.
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3TRUNCATE SUSPECTEDLarge enterprise customerSuspected database-wide TRUNCATEPostgreSQL 161,200+ tablesAnonymized case

More Than 1,200 Tables Recovered After a Suspected Database-Wide TRUNCATE

A PostgreSQL 16 production database at a large enterprise suffered a business outage. More than 1,200 table structures remained intact, but their data had disappeared. The recovery team became involved about two weeks after the incident; because the logs were incomplete, the original source of the operation could not be confirmed. Disk scanning, image preservation, and table-by-table schema matching were used to recover the target scope in batches. To protect customer privacy, the industry, scale, timing, and backup details in this case have been anonymized and perturbed.

Environment
PostgreSQL 16 / 1,200+ tables in one database
Result
More than 1,200 target tables recovered
Result
Over 95% was newer than the historical backup

Main Timeline

1
Incident discovered
About two weeks before recovery

A critical business system failed, and investigation found that more than 1,200 table structures in a PostgreSQL 16 database still existed while the business data had disappeared.

2
Recovery requested
Morning of engagement

The recovery team became involved some time after the incident. Only a historical backup more than three years old was available, so conventional restoration could not cover later business data.

3
Cause bounded
During site assessment

The symptoms were consistent with a database-wide TRUNCATE, but the relevant logs were incomplete and could not confirm the operator, execution path, or exact root cause.

4
Scope reviewed
After engagement

The PostgreSQL 16 single-database environment, more than 1,200 affected tables, and the surviving schemas were reviewed to define a phased scan, matching, and validation sequence.

5
Disk scan started
That afternoon

Remaining disk pages were scanned, prioritizing the locations of identifiable main-table, index, and TOAST pages.

6
Image prepared
That evening

Recoverable pages found by the scan were collected into an offline image so later identification and recovery no longer required continued reads from the original disk.

7
Schemas matched
The following day

Using the intact schemas, data pages for more than 1,200 target tables were matched in batches inside the image and a table-level recovery inventory was prepared.

8
Initial validation
Recovery stage

Initial recovered results were sampled for column alignment and importability; batch processing continued after the recovery path was confirmed.

9
Batch recovery
Recovery stage

Page fragments were consolidated by schema, importable data was exported in batches, and parsing and validation status was recorded for each table.

10
Backup comparison
Before delivery

The recovered results were compared with the historical backup from more than three years earlier, confirming that over 95% of the data was newer than that backup.

11
Recovery completed
After more than 20 hours of processing

More than 1,200 target tables were recovered, together with table-level results, import materials, and a complete recovery report.

12
Business validation
After recovery

The recovered data was imported into a validation environment and sampled for business checks; the customer confirmed that the target data was usable.

Situation
  1. 1A critical business system at a large enterprise ran PostgreSQL 16 with more than 1,200 business tables in one database.
  2. 2When the incident was discovered, the target table structures still existed but their data had disappeared.
  3. 3The site suspected a database-wide TRUNCATE, but complete log evidence that could confirm the source of the operation was unavailable.
Constraints
  1. 1The recovery team became involved about two weeks after the incident, and the relevant log information was already incomplete.
  2. 2Only a historical backup more than three years old was available, so substantial business data created after that backup could not be obtained through conventional restoration.
  3. 3Old-page identification, schema matching, and result validation had to be completed across more than 1,200 tables in one database.
Recovery Path
  1. 1Scanned remaining disk pages and collected identifiable content into an offline image.
  2. 2Used the intact schemas to match target-table data pages in batches inside the image.
  3. 3Consolidated fragments and exported importable data while recording table-level parsing and validation status.
  4. 4Compared the recovered results with the historical backup and delivered a recovery report and import materials.
Validation
  1. 1More than 1,200 target tables in the database were recovered and documented in a table-level result inventory.
  2. 2Comparison with the historical backup from more than three years earlier showed that over 95% of the recovered data had been created after that backup.
  3. 3After import into a validation environment, business samples were checked and the customer confirmed that the target data was usable.
Engineering note: Intact schemas combined with database-wide data loss were consistent with a database-wide TRUNCATE, but the relevant logs were already incomplete when recovery began. The incident can therefore only be described as suspected; neither the operator nor the exact root cause can be confirmed. In this type of incident, stopping writes, preserving the original disk promptly, and retaining complete schemas directly affect the recoverable scope.

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