flink-statefun
redpanda
flink-statefun | redpanda | |
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18 | 69 | |
495 | 8,822 | |
1.0% | 2.0% | |
5.1 | 10.0 | |
5 months ago | 3 days ago | |
Java | C++ | |
Apache License 2.0 | - |
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
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For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
flink-statefun
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flink-statefun VS quix-streams - a user suggested alternative
2 projects | 7 Dec 2023
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Snowflake - what are the streaming capabilities it provides?
When low latency matters you should always consider an ETL approach rather than ELT, e.g. collect data in Kafka and process using Kafka Streams/Flink in Java or Quix Streams/Bytewax in Python, then sink it to Snowflake where you can handle non-critical workloads (as is the case for 99% of BI/analytics). This way you can choose the right path for your data depending on how quickly it needs to be served.
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JR, quality Random Data from the Command line, part I
Sometimes we may need to generate random data of type 2 in different streams, so the "coherency" must also spread across different entities, think for example to referential integrity in databases. If I am generating users, products and orders to three different Kafka topics and I want to create a streaming application with Apache Flink, I definitely need data to be coherent across topics.
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Brand Lift Studies on Reddit
The Treatment and Control audiences need to be stored for future low-latency, high-reliability retrieval. Retrieval happens when we are delivering the survey, and informs the system which users to send surveys to. How is this achieved at Reddit’s scale? Users interact with ads, which generate events that are sent to our downstream systems for processing. At the output, these interactions are stored in DynamoDB as engagement records for easy access. Records are indexed on user ID and ad campaign ID to allow for efficient retrieval. The use of stream processing (Apache Flink) ensures this whole process happens within minutes, and keeps audiences up to date in real-time. The following high-level diagram summarizes the process:
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Query Real Time Data in Kafka Using SQL
Most streaming database technologies use SQL for these reasons: RisingWave, Materialize, KsqlDB, Apache Flink, and so on offering SQL interfaces. This post explains how to choose the right streaming database.
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How to choose the right streaming database
Apache Flink.
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5 Best Practices For Data Integration To Boost ROI And Efficiency
There are different ways to implement parallel dataflows, such as using parallel data processing frameworks like Apache Hadoop, Apache Spark, and Apache Flink, or using cloud-based services like Amazon EMR and Google Cloud Dataflow. It is also possible to use parallel dataflow frameworks to handle big data and distributed computing, like Apache Nifi and Apache Kafka.
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Forward Compatible Enum Values in API with Java Jackson
We’re not discussing the technical details behind the deduplication process. It could be Apache Flink, Apache Spark, or Kafka Streams. Anyway, it’s out of the scope of this article.
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Which MQTT (or similar protocol) broker for a few 10k IoT devices with quite a lot of traffic?
One can also consider https://flink.apache.org/ instead of Kafka for connecting a large number of devices.
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Apache Pulsar vs Apache Kafka - How to choose a data streaming platform
Both Kafka and Pulsar provide some kind of stream processing capability, but Kafka is much further along in that regard. Pulsar stream processing relies on the Pulsar Functions interface which is only suited for simple callbacks. On the other hand, Kafka Streams and ksqlDB are more complete solutions that could be considered replacements for Apache Spark or Apache Flink, state-of-the-art stream-processing frameworks. You could use them to build streaming applications with stateful information, sliding windows, etc.
redpanda
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Choosing Between a Streaming Database and a Stream Processing Framework in Python
Stream-processing platforms such as Apache Kafka, Apache Pulsar, or Redpanda are specifically engineered to foster event-driven communication in a distributed system and they can be a great choice for developing loosely coupled applications. Stream processing platforms analyze data in motion, offering near-zero latency advantages. For example, consider an alert system for monitoring factory equipment. If a machine's temperature exceeds a certain threshold, a streaming platform can instantly trigger an alert and engineers do timely maintenance.
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The best WebAssembly runtime may be no runtime at all
Yeah it’s just the stack switching itself that is a handful of cycles, but there is not much more overhead for the full VM switch if you structure your embedding the right way. Code the code is source available if you want to peek at it!
https://github.com/redpanda-data/redpanda/blob/dev/src/v/was...
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redpanda VS quix-streams - a user suggested alternative
2 projects | 7 Dec 2023
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Kafka Is Dead, Long Live Kafka
that's a littlebit of a stretch. when you say "no shortage" - outside of redpanda what product exists that actually compete in all deployment modes?
it's a misconception that redpanda is simply a better kafka. the way to think about it is that is a new storage engine, from scratch, that speaks the kafka protocol. similar to all of the pgsql companies in a different space, i.e.: big table pgsql support is not a better postgres, fundamentally different tech. you can read the src and design here: https://github.com/redpanda-data/redpanda. or an electric car is not the same as a combustion engine, but only similar in that they are cars that take you from point a to point b.
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Real-time Data Processing Pipeline With MongoDB, Kafka, Debezium And RisingWave
Redpanda with the MongoDB Debezium Connector installed. We use Redpanda as a Kafka broker.
- Redpanda
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Flink CDC / alternatives
And Kafka + Kafka Connect has https://www.confluent.io/ https://aiven.io/ https://upstash.com/ (and not quite Kafka, but protocol-compatible, https://redpanda.com/)
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The Redpanda Project
There exists a C++ project which was created after Rust the language was available. github.com/redpanda-data/redpanda/
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SOCKS Proxy Server Architecture for High Concurrency
I suggest you check out io_uring and thread per core architecture. Applications like scylladb and redpanda have thread per core architecture and use io_uring for async io.
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Kafka alternatives
Redpanda
What are some alternatives?
opensky-api - Python and Java bindings for the OpenSky Network REST API
Apache Kafka - Mirror of Apache Kafka
Apache Spark - Apache Spark - A unified analytics engine for large-scale data processing
Apache Pulsar - Apache Pulsar - distributed pub-sub messaging system
debezium - Change data capture for a variety of databases. Please log issues at https://issues.redhat.com/browse/DBZ.
NATS - High-Performance server for NATS.io, the cloud and edge native messaging system.
jetstream - JetStream Utilities
faust - Python Stream Processing. A Faust fork
RabbitMQ - Open source RabbitMQ: core server and tier 1 (built-in) plugins
Apache Accumulo - Apache Accumulo
kafkacat - Generic command line non-JVM Apache Kafka producer and consumer [Moved to: https://github.com/edenhill/kcat]