Question 1

这些数据的来源是什么?

Accepted Answer

我们的数据来自于从数百万家公司收集的招聘信息。我们在公司网站、招聘平台和其他招聘平台上监控这些招聘信息。分析招聘信息提供了一种可靠的方法来了解公司正在使用的技术，包括他们使用的内部工具。

Question 2

数据多久更新一次?

Accepted Answer

我们每天更新数据，以确保您访问的是最新的可用信息。这一频繁的更新过程保证了我们的洞察力和情报反映了行业内的最新发展和趋势。

Question 3

什么是KSQL?

Accepted Answer

KSQL is a powerful streaming SQL engine for Apache Kafka allowing users to harness the streaming data processing capabilities of Kafka with the familiar syntax of SQL This technology simplifies the development of realtime data processing applications by enabling users to write SQL queries to process data streams in realtime KSQL provides a seamless and intuitive interface for working with streaming data making it accessible to a broader audience beyond traditional developers and data engineers

Stream Processing is the category under which KSQL falls Stream Processing technologies are designed to process and analyze continuous streams of data in realtime making them ideal for applications where immediate insights and actions are required based on incoming data KSQL as a stream processing technology excels in handling large volumes of streaming data efficiently making it a valuable tool for organizations looking to derive realtime insights from their data streams

Founded by Confluent the company behind Apache Kafka KSQL was introduced to the market in 2017 with the goal of democratizing realtime stream processing by providing a simple yet powerful tool for working with Kafka streams using SQL Confluents motivation behind KSQL was to lower the barrier to entry for processing realtime data and make it more accessible to data analysts business users and developers who are proficient in SQL

Currently KSQL holds a significant market share within the stream processing category thanks to its ease of use and seamless integration with Apache Kafka As the demand for realtime data processing continues to grow across industries it is expected that KSQLs market share will also see an upward trend in the future The userfriendly nature of KSQL and its ability to empower a broader user base to work with streaming data position it well for sustained growth and adoption in the evolving data landscape

Question 4

如何获得使用KSQL的公司的最新列表？

Accepted Answer

您可以访问 TheirStack.com，获取使用 KSQL 的公司更新名单。我们的平台提供了一个全面的数据库，涵盖了使用各种技术和内部工具的公司。

Question 5

KSQL 有多少客户？

Accepted Answer

截至目前，我们拥有关于 1,153 家使用 KSQL 的公司的数据。

Question 6

谁在使用KSQL?

Accepted Answer

KSQL 被广泛应用于包括 "It Services And It Consulting", "Truck Transportation", "Retail", "Wellness And Fitness Services", "It Services And It Consulting", "Software Development", "Retail Luxury Goods And Jewelry", "Entertainment Providers", "Defense And Space Manufacturing", "Financial Services" 在内的各个行业的各种组织中。欲了解所有使用 KSQL 的行业的完整列表，请访问 TheirStack.com。

Question 7

哪些公司使用KSQL?

Accepted Answer

一些使用KSQL的公司包括Intellibus, Estes Express Lines, Mercadona, Herbalife, Alarm.com, Jobs via Dice, Pandora, SiriusXM, Leidos, State Street以及更多公司。您可以在TheirStack.com上找到使用KSQL的1,153家公司完整列表。

Question 8

哪些国家使用KSQL最多？

Accepted Answer

根据我们的数据，KSQL 在 美国 (347 companies), 英国 (57 companies), 印度 (38 companies), 法国 (26 companies), 西班牙 (22 companies), 加拿大 (13 companies), 德国 (13 companies), 澳大利亚 (12 companies), 新加坡 (10 companies), 瑞士 (9 companies) 最受欢迎。然而，它被全世界的公司所使用。

Question 9

如何找到使用KSQL的公司？

Accepted Answer

您可以在TheirStack.com上搜索KSQL，来找到使用该技术的公司。我们跟踪数百万家公司的招聘信息，并借此发现他们正在使用的技术和内部工具。

Company	Country	Industry	Employees	Revenue
Company name Industry Size Revenue
Company name Industry Size Revenue
Company name Industry Size Revenue
Company name Industry Size Revenue
Company name Industry Size Revenue
Company name Industry Size Revenue
Company name Industry Size Revenue
Company name Industry Size Revenue
Company name Industry Size Revenue
Company name Industry Size Revenue
Company name Industry Size Revenue
Company name Industry Size Revenue

使用 KSQL 的公司

如何针对KSQL用户进行定位

KSQL 替代品和竞争对手

Apache Spark

Apache Spark Streaming

Apache Flink

Kafka Streams

PM2

Microsoft App-V

Apache Storm

Apache Heron

Heron

Faust

Redpanda

Apache Samza

Kapacitor

Azure Video Indexer

riko

Apama

Azure Text Analytics

Humanify

Amazon Kinesis Data Streams (KDS)

Apache Gearpump

Splunk Data Stream Processor (DSP)

Amazon WorkSpaces Streaming Protocol

Apama Streaming Analytics