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Seamless Migration: Apache Hive to Apache Iceberg with S3 Tables

5 min read AWS BlogNov 4, 2026Reviewed for accuracy
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The ability to migrate Apache Hive tables to Apache Iceberg is a game changer for data engineers managing large analytics datasets. Apache Iceberg offers powerful features like schema evolution and time travel queries, making it ideal for petabyte-scale data management. However, the migration process can often be complex and fraught with challenges. Amazon S3 Tables simplifies this by automating the entire workflow, allowing you to focus on your data rather than the migration headaches.

S3 Tables manage the migration workflow by performing data validation, compatibility checks, type conversions, file recompression, and compaction. Before any data is copied, S3 Tables identify every source object and generate a compatibility report. You can sync multiple times without halting writes to your source table, except for a brief period during the final cutover. This minimizes the time your tables are offline, which is crucial for production environments.

In production, ensure your Hive tables are registered with AWS Glue and stored in Parquet format within the same AWS account and region. Pay attention to the configuration parameters, such as roleARN for the IAM role and destinationTable settings for your Iceberg table. The migration process is available today, so you can start leveraging these features immediately. Remember, while this process is streamlined, always validate your migration plan to avoid unexpected issues.

Key takeaways

  • →Leverage S3 Tables to automate the migration workflow from Hive to Iceberg.
  • →Utilize compatibility reports to ensure data integrity before migration.
  • →Sync multiple times without stopping writes, minimizing downtime during cutover.
  • →Ensure your Hive tables are in Parquet format and registered with AWS Glue.

Why it matters

This migration capability significantly reduces the complexity and downtime associated with moving large datasets, allowing teams to adopt more efficient data management practices without major disruptions.

Code examples

JSON
1cat > /tmp/start-migration.json <<'EOF'
2{
3  "roleARN": "arn:aws:iam::123456789012:role/S3TablesMigrationRole",
4  "destinationTable": {
5    "tableBucketARN": "arn:aws:s3tables:us-east-1:123456789012:bucket/my-destination-bucket",
6    "namespace": "mynamespace",
7    "name": "my_destination_table",
8    "encryptionConfiguration": {
9      "sseAlgorithm": "aws:kms",
10      "kmsKeyArn": "arn:aws:kms:us-east-1:123456789012:key/1234abcd-12ab-34cd-56ef-1234567890ab"
11    },
12    "storageClassConfiguration": { "storageClass": "INTELLIGENT_TIERING" },
13    "tags": { "team": "s3tables", "purpose": "migration" },
14    "properties": {
15      "writeFormat": "parquet",
16      "icebergFormatVersion": 2,
17      "compressionCodec": "zstd",
18      "dictionaryEncoding": true
19    },
20    "schema": {
21      "type": "struct",
22      "schemaId": 0,
23      "identifierFieldIds": [1],
24      "fields": [
25        { "id": 1, "name": "id",      "type": "long",   "required": true, "doc": "primary key" },
26        { "id": 2, "name": "payload", "type": "string", "required": false }
27      ]
28    },
29    "icebergSortOrder": {
30      "orderId": 1,
31      "fields": [ { "sourceId": 1, "transform": "identity", "direction": "asc", "nullOrder": "nulls-first" } ]
32    }
33  },
34  "sourceType": "glueTable",
35  "source": {
36    "glueTable": {
37      "catalogId": "123456789012",
38      "databaseName": "my_glue_database",
39      "tableName": "my_source_table"
40    }
41  },
42  "dataMigration": {
43    "maintenanceSettings": {
44      "icebergCompaction": { "targetFileSizeMB": 512, "strategy": "binpack" },
45      "icebergSnapshotManagement": { "minSnapshotsToKeep": 3, "maxSnapshotAgeHours": 168 }
46    },
47    "migrationPolicies": {
48      "unmatchedSourceFieldsPolicy": "fail",
49      "incompatibleValuesPolicy": "fail"
50    }
51  },
52  "reviewMigrationPlan": false,
53  "migrationOutput": {
54    "bucket": "arn:aws:s3:::my-report-bucket",
55    "prefixes": {
56      "tableCompatibilityReport": "reports/table-compatibility/",
57      "objectCompatibilityReport": "reports/object-compatibility/",
58      "objectMigrationReport": "reports/object-migration/"
59    }
60  }
61}
62EOF
Bash
aws s3tables start-table-migration \
  --cli-input-json file:///tmp/start-migration.json

When NOT to use this

The official docs don't call out specific anti-patterns here. Use your judgment based on your scale and requirements.

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