Calisti
Lenses.io
VMware Tanzu
Red Hat Enterprise Linux
Integrify
Striim
Confluent
Laragon
Google Cloud Dataflow
Google BigQuery
Amazon EMR
Databricks
Google Cloud Dataproc
Snowflake
Qubole
Amazon Kinesis
Calisti effortlessly secures, deploys, and manages your cloud native apps and event drive platforms such as Apache Kafka at scale on Kubernetes, on hybrid multi-cloud ◦ Calisti simplifies zero-trust security by integrating security into Apache Kafka through Kubernetes. ◦ Calisti simplifies observability by integrating metrics, events, logs, topology, and tracing into a single pane of glass, accelerating root cause analysis and remediation time. ◦ Calisti simplifies the management of services such as Scaling of clusters by providing a user-friendly platform offering features like real-time network debugging tools, integrated configuration validation, and a sleek UI dashboard.
Calisti Google Cloud DataflowNo features have been listed yet.
Based on our record, Google Cloud Dataflow seems to be more popular. It has been mentiond 14 times since March 2021. We are tracking product recommendations and mentions on various public social media platforms and blogs. They can help you identify which product is more popular and what people think of it.
Imo if you are using the cloud and not doing anything particularly fancy the native tooling is good enough. For AWS that is DMS (for RDBMS) and Kinesis/Lamba (for streams). Google has Data Fusion and Dataflow . Azure hasData Factory if you are unfortunate enough to have to use SQL Server or Azure. Imo the vendored tools and open source tools are more useful when you need to ingest data from SaaS platforms, and... Source: over 1 year ago
This sub is for Apache Beam and Google Cloud Dataflow as the sidebar suggests. Source: over 1 year ago
I am pretty sure they are using pub/sub with probably a Dataflow pipeline to process all that data. Source: over 1 year ago
You can run a Dataflow job that copies the data directly from BQ into S3, though you'll have to run a job per table. This can be somewhat expensive to do. Source: over 1 year ago
It was clear we needed something that was built specifically for our big-data SaaS requirements. Dataflow was our first idea, as the service is fully managed, highly scalable, fairly reliable and has a unified model for streaming & batch workloads. Sadly, the cost of this service was quite large. Secondly, at that moment in time, the service only accepted Java implementations, of which we had little knowledge... - Source: dev.to / about 2 years ago
Lenses.io - Lenses delivers DataOps for any Apache Kafka. With Lenses, engineers are more productive when building streaming applications on Kafka.
Google BigQuery - A fully managed data warehouse for large-scale data analytics.
VMware Tanzu - Pivotal Platform is the unified, multi-cloud platform to run your enterprise apps at scale. Ship code more often, continuously deliver customer value, and thrive in a cloud-native era.
Amazon EMR - Amazon Elastic MapReduce is a web service that makes it easy to quickly process vast amounts of data.
Red Hat Enterprise Linux - Red Hat Enterprise Linux is an open source operating system that is certified on hundreds of clouds & with thousands of hardware & software vendors.
Databricks - Databricks provides a Unified Analytics Platform that accelerates innovation by unifying data science, engineering and business.What is Apache Spark?