Databricks is an industry-leading data analytics platform which is a one-stop product for all data requirements. Databricks is made by the creators of Apache Spark, Delta Lake, ML Flow, and Koalas. It builds on these technologies to deliver a true lakehouse data architecture, making it a robust platform that is reliable, scalable, and fast. Databricks speeds up innovations by synthesizing storage, engineering, business operations, security, and data science.
Licensing on site I would counsel against, as on-site hardware issues tend to really delay and slow down delivery.
I do not exactly know the costs, but one of our clients pays between $100 USD and $200 USD monthly.
Licensing on site I would counsel against, as on-site hardware issues tend to really delay and slow down delivery.
I do not exactly know the costs, but one of our clients pays between $100 USD and $200 USD monthly.
Informatica PowerCenter is a data integration and data visualization tool. The solution works as an enterprise data integration platform that helps organizations access, transform, and integrate data from various systems. The product is designed to support companies in the full cycle of a project, from its initial rollout to critical deployments. Informatica PowerCenter allows developers and analysts to collaborate while accelerating the work process to deploy projects within days instead of months.
We have found the pricing very cost-effective. The licensing is CPU and data source-based.
Cost could be improved.
We have found the pricing very cost-effective. The licensing is CPU and data source-based.
Cost could be improved.
Rivery is a serverless, SaaS DataOps platform that empowers companies of all sizes around the world to consolidate, orchestrate, and manage internal and external data sources with ease and efficiency.
The Striim platform makes it easy to ingest, process, and deliver real-time data across diverse environments in the cloud or on-premise, helping you rapidly adopt a modern data architecture. With Striim you can build streaming data pipelines to cloud environments - such as Microsoft Azure, Amazon AWS, and Google Cloud Platform - as well as Kafka, Hadoop, NoSQL and relational databases (on-premises or in the cloud) with reliability, security, and scalability.