How do you store semi-structured data?
1Times asked
Jul 2026Last seen
Jul 2026First seen
💡 Model Answer
Semi‑structured data (e.g., JSON, Avro, XML) can be stored efficiently in a data lake or warehouse using columnar, schema‑on‑read formats. Common approaches include:
- Flat files in a data lake – Store raw JSON or Avro files in S3, ADLS, or GCS. Use a metadata catalog (Glue, Hive Metastore) to describe the schema.
- Parquet/ORC – Convert semi‑structured data to a columnar format that compresses well and supports predicate push‑down. Tools like Spark or AWS Glue can read JSON and write Parquet.
- NoSQL databases – Document stores such as MongoDB or DynamoDB keep the original JSON structure and allow flexible queries.
- Data warehouse support – Modern warehouses (Snowflake, BigQuery, Redshift Spectrum) natively ingest JSON/Avro and expose it via virtual tables with automatic schema inference.
The choice depends on query patterns, performance needs, and cost. For analytics, converting to Parquet and using a warehouse is often the most efficient.
This answer was generated by AI for study purposes. Use it as a starting point — personalize it with your own experience.
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