Upsolver
Upsolver is a cloud-native Lakehouse provider that ingests 27 trillion rows and manages 50 petabytes of data monthly, offering high-performance data management and optimization solutions without vendor lock-in.
Services
Upsolver provides a cloud-native Lakehouse offering warehouse-like capabilities without vendor lock-in. The company utilizes a no-code approach for the ingestion and analysis of streams, files, and operational data. The platform supports schema evolution, exactly-once delivery, and data quality management in data ingestion. Upsolver also offers real-time database replication with minimal configuration and automatic table maintenance, as well as high-volume CDC connectors for reliable, fast, and cost-effective replication.
Products
Upsolver offers several key products and tools. This includes their Iceberg Table Optimizer that is designed to reduce costs and accelerate queries for any Iceberg table. Another critical product is their support for real-time database replication which ensures minimal configuration and automatic table maintenance. Their services also include high-volume Change Data Capture (CDC) connectors, which are known for their reliability, speed, and cost-effectiveness.
Data Handling Capabilities
Upsolver is capable of ingesting 27 trillion rows of data and managing 50 petabytes of data on a monthly basis. The platform achieves a peak throughput of 35 gigabytes per second. These capabilities are enhanced by its use of SQL for complex data ingestion and transformations, enabling effective data handling and processing at an exceptional scale.
Technology
Upsolver's technology framework includes a cloud-native Lakehouse which offers warehouse-like capabilities without vendor lock-in. They provide a no-code experience for users to easily ingest and analyze streams, files, and operational data. Additionally, the platform uses SQL for more complex data ingestion and transformation tasks. Their comprehensive tooling supports schema evolution and ensures exactly-once delivery, which is crucial for maintaining high data quality.