Confluent vs KSQL | What are the differences? | StackShare

Confluent vs KSQL

Overview

Confluent

Stacks337

Followers239

Votes14

KSQL

Stacks57

Followers126

Votes5

GitHub Stars256

Forks1.0K

KSQL vs Confluent: What are the differences?

What is KSQL? Open Source Streaming SQL for Apache Kafka. KSQL is an open source streaming SQL engine for Apache Kafka. It provides a simple and completely interactive SQL interface for stream processing on Kafka; no need to write code in a programming language such as Java or Python. KSQL is open-source (Apache 2.0 licensed), distributed, scalable, reliable, and real-time.

What is Confluent? We make a stream data platform to help companies harness their high volume real-time data streams. It is a data streaming platform based on Apache Kafka: a full-scale streaming platform, capable of not only publish-and-subscribe, but also the storage and processing of data within the stream.

KSQL and Confluent can be primarily classified as "Stream Processing" tools.

KSQL is an open source tool with 2.38K GitHub stars and 496 GitHub forks. Here's a link to KSQL's open source repository on GitHub.

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Detailed Comparison

Confluent	KSQL
It is a data streaming platform based on Apache Kafka: a full-scale streaming platform, capable of not only publish-and-subscribe, but also the storage and processing of data within the stream	KSQL is an open source streaming SQL engine for Apache Kafka. It provides a simple and completely interactive SQL interface for stream processing on Kafka; no need to write code in a programming language such as Java or Python. KSQL is open-source (Apache 2.0 licensed), distributed, scalable, reliable, and real-time.
Reliable; High-performance stream data platform; Manage and organize data from different sources.	Real-time; Kafka-native; Simple constructs for building streaming apps
Statistics
GitHub Stars -	GitHub Stars 256
GitHub Forks -	GitHub Forks 1.0K
Stacks 337	Stacks 57
Followers 239	Followers 126
Votes 14	Votes 5
Pros & Cons
Pros 4 Free for casual use 3 No hypercloud lock-in 3 Dashboard for kafka insight 2 Zero devops 2 Easily scalable Cons 1 Proprietary	Pros 3 Streamprocessing on Kafka 2 SQL syntax with windowing functions over streams 0 Easy transistion for SQL Devs
Integrations
Microsoft SharePoint Java Python Salesforce Sales Cloud Kafka Streams	Kafka

What are some alternatives to Confluent, KSQL?

Kafka

Kafka is a distributed, partitioned, replicated commit log service. It provides the functionality of a messaging system, but with a unique design.

RabbitMQ

RabbitMQ gives your applications a common platform to send and receive messages, and your messages a safe place to live until received.

Celery

Celery is an asynchronous task queue/job queue based on distributed message passing. It is focused on real-time operation, but supports scheduling as well.

Amazon SQS

Transmit any volume of data, at any level of throughput, without losing messages or requiring other services to be always available. With SQS, you can offload the administrative burden of operating and scaling a highly available messaging cluster, while paying a low price for only what you use.

NSQ

NSQ is a realtime distributed messaging platform designed to operate at scale, handling billions of messages per day. It promotes distributed and decentralized topologies without single points of failure, enabling fault tolerance and high availability coupled with a reliable message delivery guarantee. See features & guarantees.

ActiveMQ

Apache ActiveMQ is fast, supports many Cross Language Clients and Protocols, comes with easy to use Enterprise Integration Patterns and many advanced features while fully supporting JMS 1.1 and J2EE 1.4. Apache ActiveMQ is released under the Apache 2.0 License.

ZeroMQ

The 0MQ lightweight messaging kernel is a library which extends the standard socket interfaces with features traditionally provided by specialised messaging middleware products. 0MQ sockets provide an abstraction of asynchronous message queues, multiple messaging patterns, message filtering (subscriptions), seamless access to multiple transport protocols and more.

Apache NiFi

An easy to use, powerful, and reliable system to process and distribute data. It supports powerful and scalable directed graphs of data routing, transformation, and system mediation logic.

Gearman

Gearman allows you to do work in parallel, to load balance processing, and to call functions between languages. It can be used in a variety of applications, from high-availability web sites to the transport of database replication events.

Memphis

Highly scalable and effortless data streaming platform. Made to enable developers and data teams to collaborate and build real-time and streaming apps fast.