Introducing Upsolver SQLake

Build Pipelines. Not DAGs.

Streaming plus batch in a single pipeline platform
No Airflow - orchestration inferred from data
$99 / TB of data ingested | unlimited free pipelines

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$99 per TB Ingested | Transformations Free | 30 Day Unlimited Trial

The Broken Pipeline Development Process

When you query a database, it automatically generates an execution plan. While a data pipeline is just query logic that runs continuously, data engineers are forced to spend countless hours manually building execution plans – a.k.a. coding orchestration DAGs.

Having to manually orchestrate data pipelines leads to:

Long analytics cycles – every pipeline is an engineering project
Unreliable and untrustworthy data
High cost from poorly optimized pipelines
Data engineering burnout from frequent break-fix cycles
Frustrated data consumers who can’t self-serve raw data

Write a Query -> Get a Pipeline

With SQLake, you use SQL to ingest streams and files into data lake tables and then create jobs which transform, join, and aggregate that data, and stream it into destination systems for analytics consumption.

How SQLake Simplifies Pipelines for Data-in-Motion

Unify Batch & Streaming

Batch and stream processing has traditionally required separate tools and skills. We unify batch and streaming sources into a single stream processing flow that minimizes complexity.

Escape DAG Hell

Mapping all pipeline success and failure modes is manual work in Airflow. It’s hard, time consuming and error-prone. SQLake’s unique architecture deterministically guarantees correct results in all cases.

Avoid Sticker Shock

Predictable, affordable pricing. You only pay for data you ingest ($99/TB, or < 10 cents / GB), which is retained and managed in the data lake. You build unlimited transformation pipelines for free.

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