Upsolver is a big data analytics solution built for analyzing event streams at scale by providing a complete solution for self-service ETL, data preparation and management of streaming data within a cloud data lake architecture. The solution enables BI and data analysts to be self-sufficient when working with complex data sources such as IoT, app activity and server logs, without relying on complex data engineering pipelines to provide the data.
Upsolver supports multiple input and output formats such as Avro, Parquet and Protobuf for data integration across platforms. Users can segregate data by actual event time, merge data files and split large files. The drag-and-drop interface allows managers to prepare the data for analysis.
Upsolver supports integration with Amazon S3, Apache Kafka and Amazon Kinesis and Presto. The solution offers nested aggregations for the user or device profiling. Additionally, professionals can define custom metrics to monitor the data in Influx or DataDog.
Upsolver offers services on an annual basis and customer support is available via phone, email and online ticketing system.
Sagi W. Branche: Internet Mitarbeiteranzahl: 13-50 Mitarbeiter
The system shortened development times, saved manpower and infrastructure
Saves great development time
Does not require a large team for development and maintenance
Amazing customer service!
A relatively long study time,
The system is still in development so with time there are more options so you need some patience, but you can say that every problem I had was resolved quickly
Verifizierter Rezensent Branche: Computer-Software Mitarbeiteranzahl: Selbstständig
Can handle very large amounts of data (10's of terabytes) reliably with ease and is overall a very powerful product to use. Also has fantastic customer service.
Although the customer service is great, it may be necessary to consult them multiple times while trying to figure out some of the more powerful features of Upsolver.
Amit A. Mitarbeiteranzahl: 13-50 Mitarbeiter
Handles 10s of TBs easily. The data is aggregated very reliably. The stream is updated on a near real time basis. Great customer service.
Some features require a 1:1 explanation session, cause they're not easy to understand. The team is really responsive though, so it's not a big problem.