Telepresence
mirrord
DevSpace (for Kubernetes and Docker)
Okteto
Garden.io
Gefyra
DockStation
Portainer
Apache Flink
Apache Spark
Amazon Kinesis
Spring Framework
Spark Mail
Apache Airflow
Confluent
Grails
Telepresence Apache FlinkBased on our record, Apache Flink seems to be a lot more popular than Telepresence. While we know about 30 links to Apache Flink, we've tracked only 2 mentions of Telepresence. 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.
This is where shared environment tools like Telepresence and CodeZero can help. They assume you're only working on one or two microservices anyway, and running them locally is not an issue. These tools let you connect your local service to the staging environment, replacing the service currently running in the cluster, without deployment. The code you're working on runs locally, and its dependencies run in the... - Source: dev.to / over 1 year ago
Local development is an entirely different story on its own. There many tools just for this (tilt.dev, garden.io, telepresence.io, okteto.com). Source: about 3 years ago
Restate is built as a sharded replicated state machine similar to how TiKV (https://tikv.org/), Kudu (https://kudu.apache.org/kudu.pdf) or CockroachDB (https://github.com/cockroachdb/cockroach) since it makes it possible to tune the system more easily for different deployment scenarios (on-prem, cloud, cost-effective blob storage). Moreover, it allows for some other cool things like seamlessly moving from one log... - Source: Hacker News / 7 days ago
I’ve recently started my journey with Apache Flink. As I learn certain concepts, I’d like to share them. One such "learning" is the expansion of array type columns in Flink SQL. Having used ksqlDB in a previous life, I was looking for functionality similar to the EXPLODE function to "flatten" a collection type column into a row per element of the collection. Because Flink SQL is ANSI compliant, it’s no surprise... - Source: dev.to / 27 days ago
You should let the Apache Flink team know, they mention exactly-once processing on their home page (under "correctness guarantees") and in their list of features. [0] https://flink.apache.org/ [1] https://flink.apache.org/what-is-flink/flink-applications/#building-blocks-for-streaming-applications. - Source: Hacker News / about 1 month ago
Data scientists often prefer Python for its simplicity and powerful libraries like Pandas or SciPy. However, many real-time data processing tools are Java-based. Take the example of Kafka, Flink, or Spark streaming. While these tools have their Python API/wrapper libraries, they introduce increased latency, and data scientists need to manage dependencies for both Python and JVM environments. For example,... - Source: dev.to / 2 months ago
Other stream processing engines (such as Flink and Spark Streaming) provide SQL interfaces too, but the key difference is a streaming database has its storage. Stream processing engines require a dedicated database to store input and output data. On the other hand, streaming databases utilize cloud-native storage to maintain materialized views and states, allowing data replication and independent storage scaling. - Source: dev.to / 4 months ago
mirrord - Connect your local process and your cloud environment.
Apache Spark - Apache Spark is an engine for big data processing, with built-in modules for streaming, SQL, machine learning and graph processing.
DevSpace (for Kubernetes and Docker) - Cloud-Native Software Development with Kubernetes and Docker
Amazon Kinesis - Amazon Kinesis services make it easy to work with real-time streaming data in the AWS cloud.
Okteto - Development platform for Kubernetes applications.
Spring Framework - The Spring Framework provides a comprehensive programming and configuration model for modern Java-based enterprise applications - on any kind of deployment platform.