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.
Confluent is an enterprise-ready, full-scale streaming platform that enhances Apache Kafka.
You have to pay additional for one or two features.
Confluent is expensive, I would prefer, Apache Kafka over Confluent because of the high cost of maintenance.
You have to pay additional for one or two features.
Confluent is expensive, I would prefer, Apache Kafka over Confluent because of the high cost of maintenance.
Azure Stream Analytics is a robust real-time analytics service that has been designed for critical business workloads. Users are able to build an end-to-end serverless streaming pipeline in minutes. Utilizing SQL, users are able to go from zero to production with a few clicks, all easily extensible with unique code and automatic machine learning abilities for the most advanced scenarios.
The cost of this solution is less than competitors such as Amazon or Google Cloud.
We pay approximately $500,000 a year. It's approximately $10,000 a year per license.
The cost of this solution is less than competitors such as Amazon or Google Cloud.
We pay approximately $500,000 a year. It's approximately $10,000 a year per license.
Amazon Kinesis makes it easy to collect, process, and analyze real-time, streaming data so you can get timely insights and react quickly to new information. Amazon Kinesis offers key capabilities to cost-effectively process streaming data at any scale, along with the flexibility to choose the tools that best suit the requirements of your application. With Amazon Kinesis, you can ingest real-time data such as video, audio, application logs, website clickstreams, and IoT telemetry data for machine learning, analytics, and other applications. Amazon Kinesis enables you to process and analyze data as it arrives and respond instantly instead of having to wait until all your data is collected before the processing can begin.
Under $1,000 per month.
The solution's pricing is fair.
Under $1,000 per month.
The solution's pricing is fair.
Apache Flink is an open-source batch and stream data processing engine. It can be used for batch, micro-batch, and real-time processing. Flink is a programming model that combines the benefits of batch processing and streaming analytics by providing a unified programming interface for both data sources, allowing users to write programs that seamlessly switch between the two modes. It can also be used for interactive queries.
This is an open-source platform that can be used free of charge.
The solution is open-source, which is free.
This is an open-source platform that can be used free of charge.
The solution is open-source, which is free.
Amazon Managed Streaming for Apache Kafka (Amazon MSK) is a fully managed service that enables you to build and run applications that use Apache Kafka to process streaming data. Amazon MSK provides the control-plane operations, such as those for creating, updating, and deleting clusters.
The price of Amazon MSK is less than some competitor solutions, such as Confluence.
The platform has better pricing than one of its competitors.
The price of Amazon MSK is less than some competitor solutions, such as Confluence.
The platform has better pricing than one of its competitors.
Spring Cloud Data Flow is a toolkit for building data integration and real-time data processing pipelines.
Pipelines consist of Spring Boot apps, built using the Spring Cloud Stream or Spring Cloud Task microservice frameworks. This makes Spring Cloud Data Flow suitable for a range of data processing use cases, from import/export to event streaming and predictive analytics. Use Spring Cloud Data Flow to connect your Enterprise to the Internet of Anything—mobile devices, sensors, wearables, automobiles, and more.
This is an open-source product that can be used free of charge.
If you want support from Spring Cloud Data Flow there is a fee. The Spring Framework is open-source and this is a free solution.
This is an open-source product that can be used free of charge.
If you want support from Spring Cloud Data Flow there is a fee. The Spring Framework is open-source and this is a free solution.
Solace PubSub+ Event Broker is a serverless, scalable technology that efficiently streams events throughout all sorts of environments: within the cloud, on-premises, and IoT. The technology is based on the publish/subscribe model of communication. The “+” in the solution’s name alludes to its support of a wide spectrum of message exchange patterns beyond the publish/subscribe model; it supports queueing, streaming, and request/reply. The “+” also alludes to the fact that the solution supports a range of different qualities of service. PubSub+ Event Broker can be managed and monitored with a single administration interface.
The pricing and licensing were very transparent and well-communicated by our account manager.
It could be cheaper. Its licensing is on a yearly basis.
The pricing and licensing were very transparent and well-communicated by our account manager.
It could be cheaper. Its licensing is on a yearly basis.
Starburst Enterprise is a data analytics platform that enables organizations to access and analyze data from multiple sources, including cloud-based and on-premises data warehouses. It provides a single access point to all data sources, allowing users to query and analyze data without moving it between systems.
Cloudera DataFlow (CDF) is a comprehensive edge-to-cloud real-time streaming data platform that gathers, curates, and analyzes data to provide customers with useful insight for immediately actionable intelligence. It resolves issues with real-time stream processing, streaming analytics, data provenance, and data ingestion from IoT devices and other sources that are associated with data in motion. Cloudera DataFlow enables secure and controlled data intake, data transformation, and content routing because it is built entirely on open-source technologies. With regard to all of your strategic digital projects, Cloudera DataFlow enables you to provide a superior customer experience, increase operational effectiveness, and maintain a competitive edge.
DataFlow isn't expensive, but its value for money isn't great.
DataFlow isn't expensive, but its value for money isn't great.
Aiven provides managed open source data technologies on all major clouds.
Apache Pulsar is a cloud-native, distributed messaging and streaming platform originally created at Yahoo! and now a top-level Apache Software Foundation project
A commercial license is required to operate Software AG Apama.
A commercial license is required to operate Software AG Apama.
Artificial intelligence and machine learning are the most transformative technologies of our time, and SAS is more committed than ever to investing in its potential to move humanity forward.
WSO2 Stream Processor is an open source, cloud native and lightweight stream processing platform that understands streaming SQL queries in order to capture, analyze, process and act on events in real time. This facilitates real-time streaming analytics and streaming data integration. With the product’s powerful streaming SQL, simple deployment, and ability to adapt to changes rapidly, enterprises can go to market faster and achieve greater ROI. Unlike other offerings, it provides a simple two-node deployment for high availability and scales beyond with its distributed deployment to cater to extremely high workloads.