1
Spark as a Compiler: Joining a Billion Rows per Second on a Laptop
Discover how Apache Spark can join a billion rows per second on a laptop, showcasing its powerful data processing capabilities.
Databricks Blog
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2
Postgres data stored in Parquet on S3: LTAP architecture explained
Almost every traditional database keeps its write-ahead log and data files on one machine's disk, which is the root cause of data loss risk, expensive read replicas and high-availability clones, and analytics queries that drag down transactions.
3
Spark Breaks Previous Large-Scale Sort Record
Read how Apache Spark sorted 100 TB of data (1 trillion records) 3X faster using 10X fewer machines in 2014.
4
Intelligent Kubernetes Load Balancing at Databricks
How Databricks uses client-side load balancing to improve gRPC traffic, reduce tail latency, and handle ingress with real-time service discovery.
5
Lakebase architecture delivers faster Postgres writes
How Lakebase's storage architecture pushes down full page write generation to cut WAL traffic by 94% and boost Postgres write throughput by up to 5x.