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.
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.
The price of the solution depends on many factors, such as how they pay for tools in the company and its size.
Google Cloud is slightly cheaper than AWS.
The price of the solution depends on many factors, such as how they pay for tools in the company and its size.
Google Cloud is slightly cheaper than AWS.
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.
Spark Streaming makes it easy to build scalable fault-tolerant streaming applications.
People pay for Apache Spark Streaming as a service.
I was using the open-source community version, which was self-hosted.
People pay for Apache Spark Streaming as a service.
I was using the open-source community version, which was self-hosted.
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.
Apache Pulsar is a cloud-native, distributed messaging and streaming platform originally created at Yahoo! and now a top-level Apache Software Foundation project
Informatica Intelligent Streaming allows organizations to prepare and process streams of data and uncover insights while acting in time to suit business needs. It can scale out horizontally and vertically to handle petabytes of data while honoring business service level agreements (SLAs). Intelligent Streaming provides pre-built high-performance connectors such as Kafka, HDFS, NoSQL databases, and enterprise messaging systems and data transformations to enable a code-free method of defining your data integration logic.
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.
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.
