Apache Pulsar VS flink-statefun

Compare Apache Pulsar vs flink-statefun and see what are their differences.

Apache Pulsar

Apache Pulsar - distributed pub-sub messaging system (by apache)

flink-statefun

Apache Flink Stateful Functions (by apache)
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Apache Pulsar flink-statefun
30 18
13,655 488
0.9% 1.6%
9.8 5.1
1 day ago 4 months ago
Java Java
Apache License 2.0 Apache License 2.0
The number of mentions indicates the total number of mentions that we've tracked plus the number of user suggested alternatives.
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

Posts with mentions or reviews of Apache Pulsar. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2024-02-10.
  • Choosing Between a Streaming Database and a Stream Processing Framework in Python
    10 projects | dev.to | 10 Feb 2024
    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
    2 projects | /r/Terraform | 28 Sep 2023
    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
    6 projects | news.ycombinator.com | 7 Aug 2023
    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
    2 projects | dev.to | 6 Jul 2023
    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.
  • Is anyone frustrated with anything about Prometheus?
    5 projects | /r/PrometheusMonitoring | 18 Jun 2023
  • Kafka alternatives
    6 projects | /r/apachekafka | 22 May 2023
  • Is Redpanda going to replace Apache Kafka?
    2 projects | /r/dataengineering | 7 May 2023
    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
    4 projects | dev.to | 30 Apr 2023
    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.
  • How Streaming database differs from a Traditional database?
    3 projects | dev.to | 31 Mar 2023
    For example, RisingWave is one of the fastest-growing open-source streaming databases that can ingest data from Apache Kafka, Apache Pulsar, Amazon Kinesis, Redpanda, and databases via native Change data capture connections or using Debezium connectors to MySQL and PostgreSQL sources. Previously, I wrote a blog post about how to choose the right streaming database that discusses some key factors that you should consider.

flink-statefun

Posts with mentions or reviews of flink-statefun. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2023-12-07.
  • flink-statefun VS quix-streams - a user suggested alternative
    2 projects | 7 Dec 2023
  • Snowflake - what are the streaming capabilities it provides?
    3 projects | /r/dataengineering | 10 May 2023
    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.
  • JR, quality Random Data from the Command line, part I
    8 projects | dev.to | 7 May 2023
    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.
  • Query Real Time Data in Kafka Using SQL
    7 projects | dev.to | 23 Mar 2023
    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.
  • How to choose the right streaming database
    8 projects | dev.to | 16 Mar 2023
    Apache Flink.
  • 5 Best Practices For Data Integration To Boost ROI And Efficiency
    3 projects | /r/ReviewNPrep | 12 Mar 2023
    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.
  • Forward Compatible Enum Values in API with Java Jackson
    5 projects | dev.to | 11 Feb 2023
    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.
  • Which MQTT (or similar protocol) broker for a few 10k IoT devices with quite a lot of traffic?
    2 projects | /r/MQTT | 16 Jan 2023
    One can also consider https://flink.apache.org/ instead of Kafka for connecting a large number of devices.
  • Apache Pulsar vs Apache Kafka - How to choose a data streaming platform
    3 projects | dev.to | 13 Dec 2022
    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.
  • Real Time Data Infra Stack
    15 projects | dev.to | 4 Dec 2022
    The Apache Flink, which is often mentioned, is one of these options, and there are many others.

What are some alternatives?

When comparing Apache Pulsar and flink-statefun you can also consider the following projects:

redpanda - Redpanda is a streaming data platform for developers. Kafka API compatible. 10x faster. No ZooKeeper. No JVM!

Apache ActiveMQ - Mirror of Apache ActiveMQ

Apache ActiveMQ Artemis - Mirror of Apache ActiveMQ Artemis

Apache Camel - Apache Camel is an open source integration framework that empowers you to quickly and easily integrate various systems consuming or producing data.

Apache RocketMQ - Apache RocketMQ is a cloud native messaging and streaming platform, making it simple to build event-driven applications.

RocketMQ

Aeron - Efficient reliable UDP unicast, UDP multicast, and IPC message transport

Embedded RabbitMQ - A JVM library to use RabbitMQ as an embedded service

Apache Kafka - Mirror of Apache Kafka

jetstream - JetStream Utilities

Nakadi - A distributed event bus that implements a RESTful API abstraction on top of Kafka-like queues

envoy - Cloud-native high-performance edge/middle/service proxy