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.
Spark provides programmers with an application programming interface centered on a data structure called the resilient distributed dataset (RDD), a read-only multiset of data items distributed over a cluster of machines, that is maintained in a fault-tolerant way. It was developed in response to limitations in the MapReduce cluster computing paradigm, which forces a particular linear dataflowstructure on distributed programs: MapReduce programs read input data from disk, map a function across the data, reduce the results of the map, and store reduction results on disk. Spark's RDDs function as a working set for distributed programs that offers a (deliberately) restricted form of distributed shared memory
Apache Spark is open-source. You have to pay only when you use any bundled product, such as Cloudera.
Spark is an open-source solution, so there are no licensing costs.
Apache Spark is open-source. You have to pay only when you use any bundled product, such as Cloudera.
Spark is an open-source solution, so there are no licensing costs.
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.
AWS Lambda is a compute service that lets you run code without provisioning or managing servers. AWS Lambda executes your code only when needed and scales automatically, from a few requests per day to thousands per second. You pay only for the compute time you consume - there is no charge when your code is not running. With AWS Lambda, you can run code for virtually any type of application or backend service - all with zero administration. AWS Lambda runs your code on a high-availability compute infrastructure and performs all of the administration of the compute resources, including server and operating system maintenance, capacity provisioning and automatic scaling, code monitoring and logging. All you need to do is supply your code in one of the languages that AWS Lambda supports (currently Node.js, Java, C# and Python).
AWS is slightly more expensive than Azure.
Its pricing is on the higher side.
AWS is slightly more expensive than Azure.
Its pricing is on the higher side.
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 used for building data pipelines, ETL processes, and asynchronous workloads. It excels in real-time streaming, Kafka and Elasticsearch integration, and microservices orchestration. Users appreciate its straightforward programming model, auto-configuration, and user-friendly interface. Enhancements are needed in monitoring tools, documentation, and multi-language support.
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.
It's an open-source solution.
We use the free version of Apache NiFi.
It's an open-source solution.
We use the free version of Apache NiFi.
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.
Apache Pulsar is a cloud-native, distributed messaging and streaming platform originally created at Yahoo! and now a top-level Apache Software Foundation project
Aiven for Apache Kafka is a highly praised service designed to streamline real-time data processing and integration across various systems. Primarily celebrated for enhancing data streaming capabilities, it supports crucial operations such as real-time analytics, event-driven architectures, message brokering, and log aggregation. These applications allow for rapid and reliable handling of large data volumes, facilitating immediate insights and swift decision-making. Users have acknowledged Kafka's robust tools in maintaining high throughput for event notifications and acting as a central communication hub, which boosts system consistency and reduces dependencies.
Among its standout features, Aiven for Apache Kafka offers scalable solutions that adapt to changing demands without impacting performance. Its data replication capabilities ensure data integrity and availability across various locations, boosting organizational resilience. Additionally, comprehensive monitoring and automated backups provide essential insights and data security, further endorsed by users for adding layers of reliability and operational peace of mind.
Leveraging Aiven for Apache Kafka has notably enhanced organizational efficiency by automating workflows, minimizing errors, and allowing teams to concentrate on strategic objectives. Improved data management and accessibility foster informed decision-making, ultimately contributing to better collaboration and increased productivity across teams.
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 Instaclustr Platform is your one-stop destination for deploying, managing, and monitoring all components of your data layer and related infrastructure, all managed and operated in unison by the same provider with no competing agendas or priorities.
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.
