CLOUD-NATIVE DATA STREAMING
Data Streaming Turns Data at Rest into Data in Motion
From event-driven architectures to real-time analytics and AI, everything you build starts here.
Audacy slashes time-to-implementation by 50%
Notion rapidly scales to serve 100M+ users
SAS reduces annual Kafka costs by 69%
Data streaming moves high-throughput, low-latency data between systems in real-time. Confluent’s CEO, Jay Kreps, co-created Apache Kafka®—the open source standard for data streaming.
Today, thousands of startups and enterprises trust Confluent instead of managing Kafka. Our cloud-native Kafka engine, KORA autoscales GBps+ workloads 10x faster with 10x lower tail latencies––and a 99.99% SLA.
Access Events as They Happen
With data streaming, you don’t operate brittle point-to-point pipelines. Instead, every event—like a click, transaction, sensor reading, or database update—is written to a shared append-only log.
Confluent streams data for any use case:
Cluster options
Optimize your resources at the lowest cost, with pay-as-you-go pricing
Cluster linking
Automatically syncs data across global architectures within your private network
Enterprise security
Includes RBAC, encryption in transit and at rest, and BYOK
1800+ certifications
Include SOC 2 Type II, PCI DSS Level 1, HIPAA, and FedRAMP Moderate
Decouple Data Producers and Consumers
Any number of data producers can write events to a shared log, and any number of consumers can read those events independently and in parallel. You can add, evolve, recover, and scale producers or consumers—without dependencies.
Confluent integrates your legacy and modern systems:
Client libraries
Deploy a sample client app in minutes using your preferred language
Pre-built connectors
Avoid 3-6 engineering months of designing, building, and testing each connector
Fully managed connectors
Launch in minutes without operational overhead, reducing your total cost of ownership
Custom connectors
Build your own integrations and let us manage the Connect infrastructure
Use High Quality Data Everywhere
Once events are in the stream, they’re organized into logical topics like "orders" or "payments”. Applications, analytics, and AI all access these topics as a shared source of record.
Confluent enriches your data as it’s created—not after its batched:
Stream processing
Filters, transforms, and joins each event in real-time using SQL
Data contracts
Enforce schema and semantic validation before bad data enters the system
Stream catalog
Organizes topics for self-service enrichment and access through a UI or APIs
Tableflow
Represents topics in open table formats such as Apache Iceberg® and Delta Lake
「Confluent は、ミッションクリティカルなユースケースを実行するために必要なエンタープライズグレードの機能をすべて備えた、完全なエンドツーエンドのデータストリーミングプラットフォームを提供してくれます。Confluent のおかげで、過去の2年間、Apache Kafka のデプロイにかかる時間を8か月から9か月も短縮することができました。」
「Kafka クラスターをスピンアップしたり、プロトタイプを迅速に起動して実行したりなどの際に、Confluent は非常に役に立ちました。もしオープンソースの Kafka を導入していたとしたら、当社のチームでも相当な時間がかかったはずです。Confluent なら、そうした手間も一切不要です。」
「Confluent Cloud を導入したことで、リソースが限られる中でも厳しい立ち上げの期限に間に合わせることが可能となりました。マネージドサービスとしてのイベントストリーミングにより、費用をかけてクラスタを管理する担当者を採用することを心配したり、信頼性を常に維持できるか心配する必要もなくなりました。」
「Apache Kafka を活用し、運営面での透明性を改善し 、データに裏打ちされたタイムリーな意思決定を実現する上で、Confluent は重要な役割を果たしています。ビジネスフローの監視、貸出承認までの時間短縮、適時に質の高い不正分析の提供などが改善できたことを嬉しく思っています。」
「Kafka の管理をすべてオフロードし、なおかつ Kafka の利点をすべて享受できる方法はないだろうかと検討を始めました。そこで浮上したのが Confluent です。」
「当行はオープンソースの価値を高く評価していますが、スタートアップ企業ではありません。世界トップクラスの組織と協業する大規模な金融機関であり、極めて信頼性の高いサービスを必要としています。Confluent はまさにそうしたサービスで、ダウンする心配は決してなく、当行のバックボーンとしての役割を果たしてくれています。」
「スケーリングは当社の成長のボトルネックとなっていました。しかし、Confluent のおかげで、アーキテクチャを簡単に再設計し、リアルタイムデータを活用して、すべての人にとってより優れたシームレスなエクスペリエンスを生み出すことができました。」
Deployment Options
Confluent can be deployed across multi-cloud, hybrid, edge, and on-premises environments at a cost less than open-source Kafka and your favorite hyperscaler.
新規開発者は、最初の30日間で$400分のクレジットを獲得できます — 営業担当者とのやり取りは不要です。
Confluent は、必要なすべてを提供します。
- 構築：Java や Python などのクライアントライブラリ、サンプルコード、120以上の事前構築済みコネクタ、Visual Studio Code 拡張機能を活用して開発可能です。
- 学習：オンデマンドコース、認定資格、世界中のエキスパートコミュニティから学べます。
- 運用：CLI、Terraform や Pulumi 向け IaC サポート、OpenTelemetry による可観測性を活用できます。
以下のクラウドマーケットプレイスアカウントでサインアップするか、当社で直接サインアップできます。
Confluent Cloud
完全マネージド型、クラウドネイティブの Apache Kafka® サービス
Data Streaming With Confluent | FAQS
What is data streaming?
Data streaming is the practice of processing data as a continuous, real-time flow of events, rather than in static batches, and Apache Kafka® is the open source, de facto standard for data streaming
How does data streaming work on Confluent?
Both Confluent Cloud and Confluent Platform are powered by enterprise distributed Kafka rearchitected for cloud-native scalability that is faster, most cost-efficient, and more resilient. Confluent Cloud specifically is powered by Kora, a cloud-native Kafka engine that allows us to pass on significant savings to our customers—including up to 20-90%+ throughput savings with our autoscaling Standard, Enterprise, and Freight clusters.
Who are Confluent’s cloud-native data streaming capabilities for?
Using Confluent for data streaming is a solid choice for any organization that wants to modernize its data architecture, build event-driven applications, leverage real-time data for analytics and AI, and solve data integrity challenges that come with traditional, batch-based ETL.
How is data streaming different from traditional APIs?
Traditional APIs typically use a request-response model, where a client requests data from a server. Data streaming uses a publish-subscribe model, where producers publish events to a shared log, and any number of consumers can access those events independently. This decoupling is fundamental to modern, scalable architectures.
What types of applications benefit from Confluent’s cloud-native data streaming?
A wide range of applications benefit, including applications for streaming analytics, event-driven generative AI, and multi-agent systems. Any application that needs to react to events instantly or needs highly trustworthy data for mission-critical use cases like from fraud detection and cybersecurity can benefit from leveraging cloud-native data streaming on Confluent.
What data formats and integrations are supported on Confluent?
Confluent supports industry-standard data formats like Avro, Protobuf, and JSON Schema through Schema Registry, part of Stream Quality in Stream Governance (Confluent’s fully managed governance suite). This allows users to integrate with hundreds of systems via our portfolio of 120+ pre-built connectors for sources and sinks like databases, data warehouses, and cloud services.
Can I use Confluent’s data streaming platform with my existing Kafka topics?
Yes, Confluent is 100% compatible with Apache Kafka®. Tools like Cluster Linking enable you to create reliable, real-time replicas of your existing Kafka data and metadata in Confluent and can also be used to migrate your Kafka workloads without downtime.
Is Confluent’s data streaming engine secure and scalable?
Yes. Confluent Cloud's cloud-native Kora engine is designed for massive scale and resilience. It can handle GBps+ workloads, scale 10x faster than traditional Kafka, and is backed by a 99.99% uptime SLA. Confluent Platform also runs on a cloud-native distribution of Kafka and provides features for easier self-managed scaling, including Confluent for Kubernetes and Ansible playbooks. For security, Confluent provides enterprise-grade features and holds numerous compliance certifications including SOC 2, ISO 27001, and PCI DSS across deployment options.
How do I get started with streaming data on Confluent?
New users receive $400 in credits to start building immediately. Simply sign up, activate your account, and you’ll be walked through how to launch your first cluster, connect a data source, and use Schema Registry on Confluent Cloud. We also recommend exploring our Demo Center and resources on Confluent Developer as you get started.
Does streaming data on Confluent require Apache Flink® or ksqlDB?
No. While Confluent offers a fully managed service for Apache Flink® for powerful stream processing, it is not required for the core data streaming capability. You can stream data directly from producers to any number of consumers without using an integrated processing layer.