Apache Pulsar
Apache Spark
Apache Pulsar | Apache Spark | |
---|---|---|
30 | 101 | |
13,772 | 38,414 | |
0.8% | 0.7% | |
9.8 | 10.0 | |
2 days ago | 6 days ago | |
Java | Scala | |
Apache License 2.0 | Apache License 2.0 |
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
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.
Apache Pulsar
-
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.
-
Apache Pulsar VS quix-streams - a user suggested alternative
2 projects | 7 Dec 2023
-
Help finding open source Terraform configurations that are not educational projects or developer tools
Edit: Here's a good example of what I'm looking for: https://github.com/apache/pulsar. It is a full application that happens to be deployed (or deployable) with Terraform, and the configuration files are available.
-
Kafka Is Dead, Long Live Kafka
I am the founder of RisingWave (http://risingwave.com/), an open-source SQL streaming database. I am happy to see the launch of Warpstream! I just reviewed the project and here's my personal opinion:
* Apache Kafka is undoubtedly the leading product in the streaming platform space. It offers a simple yet effective API that has become the golden standard. All streaming/messaging vendors need to adhere to Kafka protocol.
* The original Kafka only used local storage to store data, which can be extremely expensive if the data volume is large. That's why many people are advocating for the development of Kafka Tiered Storage (KIP-405: https://cwiki.apache.org/confluence/display/KAFKA/KIP-405%3A...). To my best knowledge, there are at least five vendors selling Kafka or Kafka-compatible products with tiered storage support:
-- Confluent, which builds Kora, the 10X Kafka engine: https://www.confluent.io/10x-apache-kafka/;
-- Aiven, the open-source tiered storage Kafka (source code: https://github.com/Aiven-Open/tiered-storage-for-apache-kafk...
-- Redpanda Data, which cuts your TCO by 6X (https://redpanda.com/platform-tco);
-- DataStax, which commercializes Apache Pulsar (https://pulsar.apache.org/);
-- StreamNative, which commercializes Apache Pulsar (https://pulsar.apache.org/).
* WarpStream claims to be "built directly on top of S3," which I believe is a very aggressive approach that has the potential to drastically reduce costs, even compared to tiered storage. The potential tradeoff is system performance, especially in terms of latency. As new technology, WarpStream brings novelty, and definitely it also needs to convince users that the service is robust and reliable.
* BYOC (Bring Your Own Cloud) is becoming the default option. Most of the vendors listed above offer BYOC, where data is stored in customers' cloud accounts, addressing concerns about data privacy and security.
I believe WarpStream is new technology to this market, and and would encourage the team to publish some detailed numbers to confirm its performance and efficiency!
-
Analyzing Real-Time Movie Reviews With Redpanda and Memgraph
In recent years, it has become apparent that almost no production system is complete without real-time data. This can also be observed through the rise of streaming platforms such as Apache Kafka, Apache Pulsar, Redpanda, and RabbitMQ.
-
There are about Pulsar 10k users in Slack, but about 70 in this subreddit.
It's colored black on the refreshed Apache Pulsar site. https://pulsar.apache.org/
- Is anyone frustrated with anything about Prometheus?
- Kafka alternatives
-
Is Redpanda going to replace Apache Kafka?
So many tools out there, its just which one do you like, I guess. I like Kafka. Works for our environment and we have a few clusters. People have brought up Cribl to replace our kafka (havent really looked into Cribl and we also run NiFi). I have even heard https://pulsar.apache.org/ , which seems to be almost another flavor of Kafka.
-
Querying microservices in real-time with materialized views
RisingWave is an open-source streaming database that has built-in fully-managed CDC source connectors for various databases, also it can collect data from other sources such Kafka, Pulsar, Kinesis, or Redpanda and it allows you to query real-time streams using SQL. You can get a materialized view that is always up-to-date.
Apache Spark
- "xAI will open source Grok"
-
Groovy 🎷 Cheat Sheet - 01 Say "Hello" from Groovy
Recently I had to revisit the "JVM languages universe" again. Yes, language(s), plural! Java isn't the only language that uses the JVM. I previously used Scala, which is a JVM language, to use Apache Spark for Data Engineering workloads, but this is for another post 😉.
-
🦿🛴Smarcity garbage reporting automation w/ ollama
Consume data into third party software (then let Open Search or Apache Spark or Apache Pinot) for analysis/datascience, GIS systems (so you can put reports on a map) or any ticket management system
-
Go concurrency simplified. Part 4: Post office as a data pipeline
also, this knowledge applies to learning more about data engineering, as this field of software engineering relies heavily on the event-driven approach via tools like Spark, Flink, Kafka, etc.
-
Five Apache projects you probably didn't know about
Apache SeaTunnel is a data integration platform that offers the three pillars of data pipelines: sources, transforms, and sinks. It offers an abstract API over three possible engines: the Zeta engine from SeaTunnel or a wrapper around Apache Spark or Apache Flink. Be careful, as each engine comes with its own set of features.
-
Apache Spark VS quix-streams - a user suggested alternative
2 projects | 7 Dec 2023
-
Integrate Pyspark Structured Streaming with confluent-kafka
Apache Spark - https://spark.apache.org/
-
Spark – A micro framework for creating web applications in Kotlin and Java
A JVM based framework named "Spark", when https://spark.apache.org exists?
- Rest in Peas: The Unrecognized Death of Speech Recognition (2010)
-
PySpark SparkSession Builder with Kubernetes Master
I recently saw a pull request that was merged to the Apache/Spark repository that apparently adds initial Python bindings for PySpark on K8s. I posted a comment to the PR asking a question about how to use spark-on-k8s in a Python Jupyter notebook, and was told to ask my question here.
What are some alternatives?
redpanda - Redpanda is a streaming data platform for developers. Kafka API compatible. 10x faster. No ZooKeeper. No JVM!
Trino - Official repository of Trino, the distributed SQL query engine for big data, formerly known as PrestoSQL (https://trino.io)
Apache ActiveMQ - Mirror of Apache ActiveMQ
Pytorch - Tensors and Dynamic neural networks in Python with strong GPU acceleration
Apache ActiveMQ Artemis - Mirror of Apache ActiveMQ Artemis
Airflow - Apache Airflow - A platform to programmatically author, schedule, and monitor workflows
Apache Camel - Apache Camel is an open source integration framework that empowers you to quickly and easily integrate various systems consuming or producing data.
Scalding - A Scala API for Cascading
Apache RocketMQ - Apache RocketMQ is a cloud native messaging and streaming platform, making it simple to build event-driven applications.
mrjob - Run MapReduce jobs on Hadoop or Amazon Web Services
RocketMQ
luigi - Luigi is a Python module that helps you build complex pipelines of batch jobs. It handles dependency resolution, workflow management, visualization etc. It also comes with Hadoop support built in.