Up your coding game and discover issues early. SonarLint is a free plugin that helps you find & fix bugs and security issues from the moment you start writing code. Install from your favorite IDE marketplace today. Learn more →
ApacheKafka Alternatives
Similar projects and alternatives to ApacheKafka
-
-
debezium
Change data capture for a variety of databases. Please log issues at https://issues.redhat.com/browse/DBZ.
-
InfluxDB
Access the most powerful time series database as a service. Ingest, store, & analyze all types of time series data in a fully-managed, purpose-built database. Keep data forever with low-cost storage and superior data compression.
-
Grafana
The open and composable observability and data visualization platform. Visualize metrics, logs, and traces from multiple sources like Prometheus, Loki, Elasticsearch, InfluxDB, Postgres and many more.
-
dramatiq
A fast and reliable background task processing library for Python 3.
-
outbox-inbox-patterns
Repository to support the article "Building a Knowledge Base Service With Neo4j, Kafka, and the Outbox Pattern"
-
redpanda
Redpanda is a streaming data platform for developers. Kafka API compatible. 10x faster. No ZooKeeper. No JVM!
-
Apache Spark
Apache Spark - A unified analytics engine for large-scale data processing
-
SonarLint
Clean code begins in your IDE with SonarLint. Up your coding game and discover issues early. SonarLint is a free plugin that helps you find & fix bugs and security issues from the moment you start writing code. Install from your favorite IDE marketplace today.
-
PostgreSQL
Mirror of the official PostgreSQL GIT repository. Note that this is just a *mirror* - we don't work with pull requests on github. To contribute, please see https://wiki.postgresql.org/wiki/Submitting_a_Patch
-
-
-
-
Redis
Redis is an in-memory database that persists on disk. The data model is key-value, but many different kind of values are supported: Strings, Lists, Sets, Sorted Sets, Hashes, Streams, HyperLogLogs, Bitmaps.
-
-
materialize
Materialize is a fast, distributed SQL database built on streaming internals. (by MaterializeInc)
-
-
-
Docker Compose
Define and run multi-container applications with Docker
-
-
NATS
High-Performance server for NATS.io, the cloud and edge native messaging system.
-
-
SaaSHub
SaaSHub - Software Alternatives and Reviews. SaaSHub helps you find the best software and product alternatives
NOTE:
The number of mentions on this list indicates mentions on common posts plus user suggested alternatives.
Hence, a higher number means a better ApacheKafka alternative or higher similarity.
ApacheKafka reviews and mentions
Posts with mentions or reviews of ApacheKafka.
We have used some of these posts to build our list of alternatives
and similar projects. The last one was on 2023-06-01.
-
JR, quality Random Data from the Command line, part II
In the first part of this series, we have seen how to use JR in simple use cases to stream random data from predefined templates to standard out and Apache Kafka on Confluent Cloud.
-
Exploring Async PHP
The use of queues such as Amazon SQS, RabbitMQ or Apache Kafka has been a widely accepted solution for some time.
-
Best way to schedule events and handle them in the future?
The second approach is to use a message queue, as some others have suggested. The most powerful of these is probably Kafka, but it's almost certainly overkill. (Technically, Kafka is an event log, not a message queue, but that's semantics at this point)
-
Top 6 message queues for distributed architectures
Apache Kafka is an open-source, distributed event streaming platform with message communication and storage capabilities. Although Kafka is not technically a message queue, it has the functionality of a message queue using a topic partition.
-
Amazon Ditches Microservices for Monolith: Decoding Prime Video's Architectural Shift
When it comes to the limitations of AWS Step Functions, let us look at what it was doing. Step Functions handled communication between the different steps of their stream quality architecture and error handling. When it comes to communication between services, tools like Kafka exist and can be used to transfer data (or state) between services. Kafka uses a pub/sub (publish and subscribe) messaging model that allows producers to publish topics to consumers, that can then act on the topics they are subscribed to. Kafka's pub/sub model allows for efficient and reliable data streaming, making it perfect for building event-driven systems, such as one that handles monitoring video quality.
-
HRV-Mart
In order to create a scalable back-end I use micro-service architecture. Current version of HRV-Mart back-end consist of Product-Microservice, User-Microservice, Auth-Microservice, Order-Microservice, Cart-Microservice, Like-Micorservice and API-Gateway. Above micro-services are loosely couple and communication between them happens via Apache Kafka. In order to make them more secure, I added unit tests. The master branch is protected via branch protection rules
-
JR, quality Random Data from the Command line, part I
So, is JR yet another faking library written in Go? Yes and no. JR indeed implements most of the APIs in fakerjs and Go fake it, but it's also able to stream data directly to stdout, Kafka, Redis and more (Elastic and MongoDB coming). JR can talk directly to Confluent Schema Registry, manage json-schema and Avro schemas, easily maintain coherence and referential integrity. If you need more than what is OOTB in JR, you can also easily pipe your data streams to other cli tools like kcat thanks to its flexibility.
-
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.
-
Modern stack to build a real-time event-driven app
The first component is a database that acts as a data source, which can be PostgreSQL (Other popular options include MongoDB or MySQL). As data changes in the database, a change is detected using the Log-based CDC (Change Data Capture) capabilities of the database. It captures the change and records it in a transaction log. The captured changes are then transformed into a change event that can be consumed in real-time by downstream systems (a message broker) such as Kafka.
-
How Change Data Capture (CDC) Works with Streaming Database
A streaming database is a type of database that is designed to handle continuous data streams in real-time and makes it possible to query this data. You can read more about how a Streaming database differs from a Traditional database and how to choose the right streaming database in my other blog posts. CDC is particularly useful when working with streaming databases, you can ingest CDC data from directly databases (See an example in the next section) without setting up additional services like Kafka.
-
A note from our sponsor - SonarLint
www.sonarlint.org | 5 Jun 2023
Stats
Basic ApacheKafka repo stats
80
24
10.0
over 5 years ago
SaaSHub - Software Alternatives and Reviews
SaaSHub helps you find the best software and product alternatives
www.saashub.com