本文提供Databricks數據洞察中的Databricks Runtime Delta與社區開源版本Delta Lake。
Databricks Runtime vs Apache Spark
下表中的 feature 列表來自 Databricks 官網（https://databricks.com/spark/comparing-databricks-to-apache-spark）
| Feature | Apache Spark | Databricks數據洞察 |
|---|---|---|
| Built-in file system optimized for cloud storage access | No | Yes |
| Spark-native fine grained resource sharing for optimum utilization | No | Yes |
| Fault isolation of compute resources | No | Yes |
| Faster writes to OSS | No | Yes |
| Compute optimization during joins and filters | No | Yes |
| Rapid release cycles | No | Yes |
| Auto-scaling compute | No | Yes |
Databricks Delta vs Open-source Delta Lake
| Feature | Open SourceDelta Lake | Databricks Delta |
|---|---|---|
| Snapshot Isolation / Transactional Guarantees | Yes | Yes |
| Efficient directory / File listing | Yes | Yes |
| Version history and time travel | Yes | Yes |
| Schema evolution & enforcement | Yes | Yes |
| Hidden partitions / Partitioning by expressions | In Roadmap | In Roadmap |
| HDFS Support | Yes | Yes |
| Object Storage Support | Yes | Yes |
| Streaming Data Sink | Yes | Yes |
| Streaming Data Source | Yes | Yes |
| Basic Upsert (merge into) | Yes | Yes |
| Scalable Upsert (merge into) | No | Yes |
| Data skipping based on stats | No | Yes |
| Compact small files | Yes | Yes |
| Optimize (efficiently compact small files) | No | Yes |
| Auto Optimize | No | Yes |
| Native Parquet Reader | No | Yes |
| Read from Presto | Yes | Yes |
| Read from Hive | In Roadmap | In Roadmap |