Upsolver Builders Hub

Education, resources and templates for designing, deploying and managing Upsolver data processing pipelines.

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How Upsolver works

how upsolver works sqlake

What makes Upsolver unique

Event Sourced Architecture

Upsolver converts all ingested data into an immutable stream of events that are processed on a per-minute basis. This enables exactly once consistency as well as time travel / replay.

Live Table Outputs

Upsolver outputs tables to your data lake or data warehouse. Tables are incrementally updated to cost-effectively provide near-real-time latency.

Declarative Data Pipelines

Build data processing pipelines declaratively using SQL. Our engine optimizes the pipeline for performance, automating tasks such as orchestration, state management , file compaction, conversion, compression and more.

Affordable Processing at Scale

Upsolver processes data on low-cost Spot cloud compute and separates ingestion from processing to scale up to millions of events per second and PB of data in process.

Try Upsolver on sample data using our SQL pipeline templates

Explore our detailed tutorials including SQL code

Read our latest articles

How to Reduce Your Data Platform Costs with Value-Based Pricing

How to Reduce Your Data Platform Costs with Value-Based Pricing

Upsolver offers a batch and streaming data pipeline platform that runs on cloud resources.  Until…

Transform Nested JSON to Parquet with SQLake

Transform Nested JSON to Parquet with SQLake

Learn different approaches for dealing with complex nested JSON, and how Upsolver SQLake can be…

How to Structure a Data Lake: Draining the Data Swamp

How to Structure a Data Lake: Draining the Data Swamp

What is a data lake meant to achieve? The idea of a data lake serving…

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Templates

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Explore our expert-made templates & start with the right one for you.