If you’re evaluating systems for large-scale JSON analytics, such as Apache Doris(https://doris.apache.org/), Snowflake, ClickHouse, Elasticsearch, or more, start with this list of questions: 1️⃣ Can it handle 1K, 5K, 10K JSON fields without dropping performance? 2️⃣ Does it support type evolution without breaking ingestion? 3️⃣ Can you apply indexes selectively to the fields that matter? 4️⃣ Does query performance degrade after schema expansion? Apache Doris check these boxes ✅, thanks to the VARIANT data type. With Apache Doris VARIANT data type, you can: - Store raw JSON as a VARIANT column - Automatically extract JSON fields into sub-columns during ingestion - Define schema templates to control data types for groups of fields - Add indexes (inverted, bloomfilter, minmax, vector) to specific JSON patterns - Scale to 1K–10K+ JSON fields while keeping queries fast 🔗 Watch the full webinar for more info on Variant in Apache Doris (contains demo: querying 1 billion rows of JSON data in seconds): https://lnkd.in/g6JKcx4w