Distributed SQL System Review: Snowflake vs Splice Machine
After many years of Big Data, NoSQL, and Schema-on-Read detours, there is a clear return to SQL as the lingua franca for data operations. Developers need the comprehensive expressiveness that SQL provides. A world without SQL ignores more than 40 years of database research and results in hard-coded spaghetti code in applications to handle functionality that SQL handles extremely efficiently such as joins, groupings, aggregations, and (most importantly) rollback when updates go wrong. Luckily, there is a modern architecture for SQL called Distributed SQL that no longer suffers from the challenges of traditional SQL systems (cost, scalability, performance, elasticity, and schema flexibility). The key attribute of Distributed SQL is that data is stored across many distributed storage locations and computation takes place across a cluster of networked servers. This yields unprecedented performance and scalability because it distributes work on each worker node in the cluster in parall...
