# Best Enterprise Event Stream Processing Software

*By [Bijou Barry](https://research.g2.com/insights/author/bijou-barry)*


Products classified in the overall Event Stream Processing category are similar in many regards and help companies of all sizes solve their business problems. However, enterprise business features, pricing, setup, and installation differ from businesses of other sizes, which is why we match buyers to the right Enterprise Business Event Stream Processing to fit their needs. Compare product ratings based on reviews from enterprise users or connect with one of G2's buying advisors to find the right solutions within the Enterprise Business Event Stream Processing category.

In addition to qualifying for inclusion in the Event Stream Processing Software category, to qualify for inclusion in the Enterprise Business Event Stream Processing Software category, a product must have at least 10 reviews left by a reviewer from an enterprise business.






## G2 Grid® for Event Stream Processing Software
![G2 Grid® for Event Stream Processing Software plotting products by satisfaction and market presence](https://www.g2.com/categories/event-stream-processing/grids.png?focus%5B%5D=69889&focus%5B%5D=17348&focus%5B%5D=129332&focus%5B%5D=42780&focus%5B%5D=10735&focus%5B%5D=157270&focus%5B%5D=71631)
Highlighted products: IBM StreamSets, Amazon Kinesis Data Streams, Aiven for Apache Kafka, Apache Kafka, Confluent, Red Hat OpenShift Streams for Apache Kafka, and Spark Streaming.
Underlying data: [Grid® JSON](https://www.g2.com/categories/event-stream-processing/grids.json?focus%5B%5D=ibm-streamsets&focus%5B%5D=aws-amazon-kinesis-data-streams&focus%5B%5D=aiven-for-apache-kafka&focus%5B%5D=apache-kafka&focus%5B%5D=confluent&focus%5B%5D=red-hat-openshift-streams-for-apache-kafka&focus%5B%5D=spark-streaming&segment=enterprise)


## How Many Event Stream Processing Software Products Does G2 Track?
**Total Products under this Category:** 70

### Category Stats (Jul 2026)
- **Average Rating**: 4.37/5 The average rating of products in this category, based on all submitted ratings
- **Top Trending Product**: PubNub (+0.96%) - Among all products in this category, PubNub recorded the largest rating increase compared to last month
*Last updated: July 12, 2026*


## How Does G2 Rank Event Stream Processing Software Products?

**Why You Can Trust G2's Software Rankings:**

- 30 Analysts and Data Experts
- 2,400+ Authentic Reviews
- 70+ Products
- Unbiased Rankings

G2's software rankings are built on verified user reviews, rigorous moderation, and a consistent research methodology maintained by a team of analysts and data experts. Each product is measured using the same transparent criteria, with no paid placement or vendor influence. While reviews reflect real user experiences, which can be subjective, they offer valuable insight into how software performs in the hands of professionals. Together, these inputs power the G2 Score, a standardized way to compare tools within every category.


## Which Event Stream Processing Software Is Best for Your Use Case?

- **Best for Small Businesses:** [Aiven for Apache Kafka](https://www.g2.com/products/aiven-for-apache-kafka/reviews)
- **Best for Mid-Market:** [Redpanda Streaming](https://www.g2.com/products/redpanda-streaming/reviews)
- **Best for Enterprise:** [IBM StreamSets](https://www.g2.com/products/ibm-streamsets/reviews)
- **Highest User Satisfaction:** [Aiven for Apache Kafka](https://www.g2.com/products/aiven-for-apache-kafka/reviews)
- **Best Free Software:** [Aiven for Apache Kafka](https://www.g2.com/products/aiven-for-apache-kafka/reviews)


---

**Sponsored**

### Kpow for Apache Kafka®

Kpow is a sophisticated enterprise Kafka management tool designed to enhance the experience of engineering teams by providing a comprehensive solution for managing, monitoring, exploring, and securing Kafka environments. This JVM-based web application serves as an all-in-one console, empowering Kafka engineers with the capabilities they need to streamline their operations and improve productivity. Targeted primarily at engineering teams working with Kafka, Kpow addresses the complexities of managing multiple Kafka clusters, schema registries, and connection installations. With Kpow, users can efficiently monitor and control their Kafka resources from a single interface, simplifying the management process and reducing the time spent on routine tasks. The tool is particularly beneficial for organizations that rely heavily on Kafka for data streaming and processing, as it provides essential functionalities that enhance observability and operational efficiency. One of the standout features of Kpow is its real-time monitoring and visualization capabilities. Users can quickly identify unbalanced brokers and gain insights into how data is distributed across their Kafka Streams topologies. This level of visibility is crucial for diagnosing production issues and optimizing performance. Kpow's advanced search functionalities, including Data Inspect, Streaming Search, and kREPL, enable users to search through vast amounts of messages at remarkable speeds, allowing for rapid troubleshooting and data analysis. Kpow also prioritizes security and access control, making it suitable for enterprise environments. It integrates seamlessly with standard authentication providers and offers role-based access controls, ensuring that user actions can be finely tuned to meet organizational security requirements. Additional security features, such as data masking and audit logs, further enhance the tool's capability to operate in sensitive environments, including air-gapped installations. Installation of Kpow is straightforward, requiring only a single Docker container or JAR file, which operates efficiently with minimal resource requirements of 1GB memory and 1 CPU for production use. This ease of deployment, combined with its powerful features, positions Kpow as a valuable asset for organizations looking to maximize their Kafka infrastructure while maintaining robust security and operational control.



[Visit website](https://www.g2.com/external_clickthroughs/record?secure%5Bad_program%5D=ppc&secure%5Bad_slot%5D=category_product_list&secure%5Bcategory_id%5D=1509&secure%5Bchosen_at%5D=2026-07-12T07%3A07%3A46Z&secure%5Bdisplayable_resource_id%5D=1509&secure%5Bdisplayable_resource_type%5D=Category&secure%5Bmedium%5D=sponsored&secure%5Bplacement_reason%5D=page_category&secure%5Bplacement_resource_ids%5D%5B%5D=1509&secure%5Bprioritized%5D=false&secure%5Bproduct_id%5D=133071&secure%5Bresource_id%5D=1509&secure%5Bresource_type%5D=Category&secure%5Bsource_type%5D=category_page&secure%5Bsource_url%5D=https%3A%2F%2Fwww.g2.com%2Fcategories%2Fevent-stream-processing%2Fenterprise%3Fopen_modal_url%3D%252Fproducts%252Faws-amazon-kinesis-data-streams%252Fwishlists%253Fhost_path%253D%25252Fcategories%25252Fevent-stream-processing%25252Fenterprise%2526source%253Dcategory&secure%5Btoken%5D=3dd75a25e4f123d6588a7e474df4efb2b5af50c368c28a3a7fdf4664b8f02a20&secure%5Burl%5D=http%3A%2F%2Ffactorhouse.io%2F&secure%5Burl_type%5D=custom_url)

---

## What Are the Top-Rated Event Stream Processing Software Products in 2026?
### 1. [IBM StreamSets](https://www.g2.com/products/ibm-streamsets/reviews)
IBM StreamSets is a robust streaming data integration tool for hybrid, multi-cloud environments that enables real-time decision making. It allows ingestion and in-flight transformation of structured, unstructured, and semi-structured data from streaming sources, and reliably delivers trusted data into diverse destinations. Flexible deployment options promote security, cost-effectiveness and performance. With several pre-built connectors, an intuitive no-code/low-code interface, and automatic adaptability to data drifts, StreamSets accelerates data pipeline operationalization. It integrates with IBM’s broader data integration capabilities, enabling reliable pipelines that unify multiple data integration patterns, underpinned by data observability capabilities for continuous data quality monitoring and remediation. That’s why the largest companies in the world trust StreamSets to power millions of data pipelines for modern analytics, data science, smart applications, and hybrid integration.


**Average Rating:** 4.0/5.0
**Total Reviews:** 115
**How Do G2 Users Rate IBM StreamSets?**

- **Has the product been a good partner in doing business?:** 8.2/10 (Category avg: 8.9/10)
- **Data Sources:** 8.0/10 (Category avg: 8.6/10)
- **Data Processing:** 8.2/10 (Category avg: 8.8/10)
- **Real-Time Processing:** 9.0/10 (Category avg: 9.1/10)

**Who Is the Company Behind IBM StreamSets?**

- **Seller:** [IBM](https://www.g2.com/sellers/ibm)
- **Year Founded:** 1911
- **HQ Location:** Armonk, New York, United States
- **Twitter:** @IBMSecurity (74,660 Twitter followers)
- **LinkedIn® Page:** https://www.linkedin.com/company/1009/ (328,202 employees on LinkedIn®)
- **Ownership:** SWX:IBM

**Who Uses This Product?**
- **Who Uses This:** Data Engineer, Software Engineer
- **Top Industries:** Information Technology and Services, Computer Software
- **Company Size:** 42% Enterprise, 33% Mid-Market


#### What Are IBM StreamSets's Pros and Cons?

**Pros:**

- Ease of Use (30 reviews)
- User Interface (16 reviews)
- Data Management (15 reviews)
- Data Pipelining (15 reviews)
- Integrations (14 reviews)

**Cons:**

- Learning Curve (13 reviews)
- Expensive (10 reviews)
- Learning Difficulty (8 reviews)
- Slow Performance (8 reviews)
- Steep Learning Curve (8 reviews)


### What Do G2 Reviewers Say About IBM StreamSets?
*AI-generated summary from verified user reviews*

**Pros:**

- Users enjoy the **ease of use** of IBM StreamSets, noting its intuitive interface and simplified pipeline creation.
- Users appreciate the **user-friendly drag-and-drop interface** of IBM StreamSets, enhancing pipeline visualization and debugging ease.
- Users praise the **effective data pipeline management** of IBM StreamSets, streamlining integration and automation across environments.
- Users appreciate the **simplification of data integration workflows** in IBM StreamSets, enhancing usability and efficiency.
- Users benefit from the **robust integrations** of IBM StreamSets, enhancing real-time data handling and workflow management effectively.

**Cons:**

- Users face a **steep learning curve** with IBM StreamSets, requiring deep technical knowledge and time for advanced features.
- Users highlight the **high cost** of IBM StreamSets, particularly challenging for smaller teams and budget constraints.
- Users find **learning difficulties** with StreamSets due to complex features and unclear documentation, hindering onboarding and expertise.
- Users experience **slow performance** while managing large data volumes, impacting efficiency and requiring more time for configurations.
- Users face a **steep learning curve** with IBM StreamSets, requiring deep technical knowledge for advanced features.

#### What Are Recent G2 Reviews of IBM StreamSets?

**"[Powerful Data Integration With IBM Stream sets.](https://www.g2.com/survey_responses/ibm-streamsets-review-11654909)"**

**Rating:** 5.0/5.0 stars
*— Abhishek D.*

[Read full review](https://www.g2.com/survey_responses/ibm-streamsets-review-11654909)

---

**"[Simplifies Real-Time Data Pipelines with Mixed Customization](https://www.g2.com/survey_responses/ibm-streamsets-review-12240946)"**

**Rating:** 4.0/5.0 stars
*— Sravya A.*

[Read full review](https://www.g2.com/survey_responses/ibm-streamsets-review-12240946)

---


#### What Are G2 Users Discussing About IBM StreamSets?

- [What is StreamSets used for?](https://www.g2.com/discussions/what-is-streamsets-used-for)
- [What is StreamSets data collector?](https://www.g2.com/discussions/what-is-streamsets-data-collector)
- [What is StreamSets control hub?](https://www.g2.com/discussions/what-is-streamsets-control-hub)
- [Are StreamSets free?](https://www.g2.com/discussions/are-streamsets-free)
- [What is StreamSets tool?](https://www.g2.com/discussions/what-is-streamsets-tool) - 1 comment

### 2. [Amazon Kinesis Data Streams](https://www.g2.com/products/aws-amazon-kinesis-data-streams/reviews)
Amazon Kinesis Data Streams is a massively scalable, durable, and low-cost streaming data service. Kinesis Data Streams can continuously capture gigabytes of data per second from hundreds of thousands of sources, such as website clickstreams, database event streams, financial transactions, social media feeds, IT logs, and location-tracking events. The collected data is available in milliseconds to allow real-time analytics use cases, such as real-time dashboards, real-time anomaly detection, dynamic pricing. Customers run more than two million unique streams and process tens of PB of data per day with Amazon Kinesis Data Streams.


**Average Rating:** 4.3/5.0
**Total Reviews:** 82
**How Do G2 Users Rate Amazon Kinesis Data Streams?**

- **Has the product been a good partner in doing business?:** 8.6/10 (Category avg: 8.9/10)
- **Data Sources:** 9.2/10 (Category avg: 8.6/10)
- **Data Processing:** 9.1/10 (Category avg: 8.8/10)
- **Real-Time Processing:** 9.4/10 (Category avg: 9.1/10)

**Who Is the Company Behind Amazon Kinesis Data Streams?**

- **Seller:** [Amazon Web Services (AWS)](https://www.g2.com/sellers/amazon-web-services-aws-3e93cc28-2e9b-4961-b258-c6ce0feec7dd)
- **Year Founded:** 2006
- **HQ Location:** Seattle, WA
- **Twitter:** @awscloud (2,232,483 Twitter followers)
- **LinkedIn® Page:** https://www.linkedin.com/company/amazon-web-services/ (147,094 employees on LinkedIn®)
- **Ownership:** NASDAQ: AMZN

**Who Uses This Product?**
- **Who Uses This:** Software Engineer
- **Top Industries:** Information Technology and Services, Computer Software
- **Company Size:** 37% Enterprise, 36% Mid-Market


#### What Are Amazon Kinesis Data Streams's Pros and Cons?

**Pros:**

- Real-time Data (2 reviews)
- Real-Time Processing (2 reviews)
- Real-time Streaming (2 reviews)
- Streaming (2 reviews)
- API Integration (1 reviews)

**Cons:**

- Difficult Setup (2 reviews)
- Expensive (2 reviews)
- Resource Intensive Learning (2 reviews)
- Complexity (1 reviews)
- Complexity Issues (1 reviews)


### What Do G2 Reviewers Say About Amazon Kinesis Data Streams?
*AI-generated summary from verified user reviews*

**Pros:**

- Users appreciate the **real-time data processing** capability of Amazon Kinesis Data Streams for high-volume streaming demands.
- Users appreciate the **real-time data processing capability** of Amazon Kinesis Data Streams, enabling efficient handling of large data volumes.
- Users value the **real-time data processing capability** of Amazon Kinesis Data Streams, enhancing their analytics and log processing tasks.
- Users value the **real-time data processing capabilities** of Amazon Kinesis Data Streams, ensuring efficient handling of large data volumes.
- Users appreciate the **seamless API integration** with AWS services, enhancing the overall efficiency of their data streaming solutions.

**Cons:**

- The **difficult setup** of Amazon Kinesis Data Streams can overwhelm beginners, complicating usage and management.
- Users find the service **expensive** , particularly when monitoring usage and managing costs for small items.
- Users face a **resource intensive learning** curve with Kinesis Data Streams, requiring time and understanding to manage effectively.
- Users find the **complexity** of setup and cost management a hurdle, especially for newcomers to AWS streaming.
- Users find the **complexity of configuration** among AWS services a challenge when using Kinesis Data Streams for analysis.

#### What Are Recent G2 Reviews of Amazon Kinesis Data Streams?

**"[Amazon Kinesis Data Streams: Reliable Tool for Real-Time Data Streaming](https://www.g2.com/survey_responses/amazon-kinesis-data-streams-review-12239194)"**

**Rating:** 4.0/5.0 stars
*— SURAJ K.*

[Read full review](https://www.g2.com/survey_responses/amazon-kinesis-data-streams-review-12239194)

---

**"[Real-Time Streaming at Scale with Low Latency and Seamless AWS Integration](https://www.g2.com/survey_responses/amazon-kinesis-data-streams-review-12933879)"**

**Rating:** 4.5/5.0 stars
*— Atharva P.*

[Read full review](https://www.g2.com/survey_responses/amazon-kinesis-data-streams-review-12933879)

---


#### What Are G2 Users Discussing About Amazon Kinesis Data Streams?

- [How do I connect to Amazon Kinesis?](https://www.g2.com/discussions/how-do-i-connect-to-amazon-kinesis)
- [How do you use Kinesis?](https://www.g2.com/discussions/how-do-you-use-kinesis)
- [What is a Kinesis?](https://www.g2.com/discussions/what-is-a-kinesis)
- [What does Amazon Kinesis do?](https://www.g2.com/discussions/what-does-amazon-kinesis-do)

### 3. [Aiven for Apache Kafka](https://www.g2.com/products/aiven-for-apache-kafka/reviews)
Aiven for Apache Kafka® is a fully managed distributed event streaming service, that can be deployed in the cloud of your choice. Aiven for Apache Kafka is ideal for event-driven applications, near-real-time data transfer and data pipelines, streaming analytics, and any use case that requires moving huge amounts of real-time data between applications and systems. With Aiven for Apache Kafka you can set up fully managed Kafka clusters in less than 10 minutes — using the Aiven web console or programmatically via Aiven’s API, CLI, Terraform provider or Kubernetes operator. You can easily connect it to your existing tech stack with a fully managed Apache Kafka Connect service with over 30+ connectors. Monitoring your clusters with logs and metrics is also available out of the box via multiple service integrations. Get access to a complete open source ecosystem of streaming technologies and tools around Apache Kafka to fully manage, and operate a real time data infrastructure at scale using: Aiven for Apache Kafka: the core event streaming framework allowing you to transport data within your organization Aiven for Apache Kafka Connect: a fully managed, fully open source, distributed service enabling you to integrate your existing data sources and sinks seamlessly with Aiven for Apache Kafka. Aiven for Apache Kafka MirrorMaker2: a fully managed, fully open source distributed data replication service for cluster to cluster data replication, disaster recovery and geo proximity across multiple regions. Karapace®: a fully open source Kafka Schema Registry that applications can access to serialize and deserialize messages with popular formats such as AVRO, Protobuf and JSON. Aiven for Apache Flink®: a fully managed, fully open source streaming SQL engine for stateful stream processing over your data streams. Klaw: an open source data governance tool that helps enterprises exercise Apache Kafka® topic and schema governance. Aiven is ISO / IEC 27001: 2013, SOC 2, HIPAA, GDPR, and CCPA compliant. Check our pricing and try our free 30-day trial at https://aiven.io/kafka.


**Average Rating:** 4.3/5.0
**Total Reviews:** 243
**How Do G2 Users Rate Aiven for Apache Kafka?**

- **Has the product been a good partner in doing business?:** 8.9/10 (Category avg: 8.9/10)
- **Data Sources:** 8.4/10 (Category avg: 8.6/10)
- **Data Processing:** 8.4/10 (Category avg: 8.8/10)
- **Real-Time Processing:** 8.5/10 (Category avg: 9.1/10)

**Who Is the Company Behind Aiven for Apache Kafka?**

- **Seller:** [Aiven](https://www.g2.com/sellers/aiven)
- **Year Founded:** 2016
- **HQ Location:** Helsinki, Southern Finland
- **Twitter:** @aiven_io (4,104 Twitter followers)
- **LinkedIn® Page:** https://www.linkedin.com/company/10294984/ (464 employees on LinkedIn®)

**Who Uses This Product?**
- **Who Uses This:** Software Engineer, Senior Software Engineer
- **Top Industries:** Computer Software, Information Technology and Services
- **Company Size:** 45% Mid-Market, 29% Small-Business


#### What Are Aiven for Apache Kafka's Pros and Cons?

**Pros:**

- Setup Ease (29 reviews)
- Ease of Use (23 reviews)
- Scaling (17 reviews)
- Management Ease (14 reviews)
- Reliability (13 reviews)

**Cons:**

- Expensive (27 reviews)
- Poor Documentation (8 reviews)
- Limited Features (7 reviews)
- Complexity (6 reviews)
- Not User-Friendly (5 reviews)


### What Do G2 Reviewers Say About Aiven for Apache Kafka?
*AI-generated summary from verified user reviews*

**Pros:**

- Users appreciate the **easy setup** of Aiven for Apache Kafka, simplifying deployment and management of data streams.
- Users find Aiven for Apache Kafka incredibly **easy to use** , enabling smooth setup and effective data-driven project management.
- Users value the **seamless scalability** of Aiven for Apache Kafka, enjoying effortless management of data streams.
- Users value the **management ease** of Aiven for Apache Kafka, enabling quick deployment and effortless self-management.
- Users value the **reliability** of Aiven for Apache Kafka, appreciating its high availability and effortless management.

**Cons:**

- Users find the **pricing increases quickly** as usage grows, making it an expensive option for scaling.
- Users often find the **poor documentation** of Aiven for Apache Kafka frustrating, hindering their ability to configure advanced features.
- Users note the **limited features** in advanced configurations, which may hinder teams needing finer control and flexibility.
- Users find the **operational complexity** of Aiven for Apache Kafka overwhelming, especially for small teams managing configurations.
- Users find the **interface unintuitive** and face challenges with advanced configurations and scaling larger clusters effectively.

#### What Are Recent G2 Reviews of Aiven for Apache Kafka?

**"[Aiven Keeps Us on Top with Fast Setup, Terraform Support, and Zero-Downtime Upgrades](https://www.g2.com/survey_responses/aiven-for-apache-kafka-review-12403301)"**

**Rating:** 5.0/5.0 stars
*— Prasanth K.*

[Read full review](https://www.g2.com/survey_responses/aiven-for-apache-kafka-review-12403301)

---

**"[Streamlined Kafka Management with Built-In Integrations](https://www.g2.com/survey_responses/aiven-for-apache-kafka-review-12593412)"**

**Rating:** 4.0/5.0 stars
*— Takwa A.*

[Read full review](https://www.g2.com/survey_responses/aiven-for-apache-kafka-review-12593412)

---


#### What Are G2 Users Discussing About Aiven for Apache Kafka?

- [What is Aiven for Apache Kafka used for?](https://www.g2.com/discussions/what-is-aiven-for-apache-kafka-used-for)
- [What is Apache Kafka connect?](https://www.g2.com/discussions/what-is-apache-kafka-connect)
- [What is Apache Kafka architecture?](https://www.g2.com/discussions/what-is-apache-kafka-architecture)
- [What is Apache Kafka good for?](https://www.g2.com/discussions/what-is-apache-kafka-good-for)
- [What are the characteristics of Apache Kafka?](https://www.g2.com/discussions/what-are-the-characteristics-of-apache-kafka) - 1 comment

### 4. [Apache Kafka](https://www.g2.com/products/apache-kafka/reviews)
Apache Kafka is an open-source distributed event streaming platform developed by the Apache Software Foundation. It is designed to handle real-time data feeds with high throughput and low latency, making it ideal for building data pipelines, streaming analytics, and integrating data across various systems. Kafka enables organizations to publish, store, and process streams of records in a fault-tolerant and scalable manner, supporting mission-critical applications across diverse industries. Key Features and Functionality: - High Throughput and Low Latency: Kafka delivers messages at network-limited throughput with latencies as low as 2 milliseconds, ensuring efficient data processing. - Scalability: It can scale production clusters up to thousands of brokers, handling trillions of messages per day and petabytes of data, while elastically expanding and contracting storage and processing capabilities. - Durable Storage: Kafka stores streams of data safely in a distributed, durable, and fault-tolerant cluster, ensuring data integrity and availability. - High Availability: The platform supports efficient stretching of clusters over availability zones and connects separate clusters across geographic regions, enhancing resilience. - Stream Processing: Kafka provides built-in stream processing capabilities through the Kafka Streams API, allowing for operations like joins, aggregations, filters, and transformations with event-time processing and exactly-once semantics. - Connectivity: With Kafka Connect, it integrates seamlessly with hundreds of event sources and sinks, including databases, messaging systems, and cloud storage services. Primary Value and Solutions Provided: Apache Kafka addresses the challenges of managing real-time data streams by offering a unified platform that combines messaging, storage, and stream processing. It enables organizations to: - Build Real-Time Data Pipelines: Facilitate the continuous flow of data between systems, ensuring timely and reliable data delivery. - Implement Streaming Analytics: Analyze and process data streams in real-time, allowing for immediate insights and actions. - Ensure Data Integration: Seamlessly connect various data sources and sinks, promoting a cohesive data ecosystem. - Support Mission-Critical Applications: Provide a robust and fault-tolerant infrastructure capable of handling high-volume and high-velocity data, essential for critical business operations. By leveraging Kafka's capabilities, organizations can modernize their data architectures, enhance operational efficiency, and drive innovation through real-time data processing and analytics.


**Average Rating:** 4.5/5.0
**Total Reviews:** 126
**How Do G2 Users Rate Apache Kafka?**

- **Has the product been a good partner in doing business?:** 8.3/10 (Category avg: 8.9/10)
- **Data Sources:** 8.7/10 (Category avg: 8.6/10)
- **Data Processing:** 9.0/10 (Category avg: 8.8/10)
- **Real-Time Processing:** 9.1/10 (Category avg: 9.1/10)

**Who Is the Company Behind Apache Kafka?**

- **Seller:** [The Apache Software Foundation](https://www.g2.com/sellers/the-apache-software-foundation)
- **Year Founded:** 1999
- **HQ Location:** Wakefield, MA
- **Twitter:** @TheASF (66,168 Twitter followers)
- **LinkedIn® Page:** https://www.linkedin.com/company/215982/ (2,470 employees on LinkedIn®)

**Who Uses This Product?**
- **Who Uses This:** Software Engineer, Senior Software Engineer
- **Top Industries:** Computer Software, Information Technology and Services
- **Company Size:** 47% Enterprise, 33% Mid-Market


#### What Are Apache Kafka's Pros and Cons?

**Pros:**

- Scalability (5 reviews)
- Real-time Data (3 reviews)
- Easy Integrations (2 reviews)
- Performance (2 reviews)
- Performance Efficiency (2 reviews)

**Cons:**

- Complexity (1 reviews)
- Data Management Issues (1 reviews)
- Debugging Issues (1 reviews)
- Difficult Learning (1 reviews)
- Limited Customization (1 reviews)


### What Do G2 Reviewers Say About Apache Kafka?
*AI-generated summary from verified user reviews*

**Pros:**

- Users value the **high scalability** of Apache Kafka, seamlessly handling large data volumes and real-time processing.
- Users value the **real-time data processing** capabilities of Apache Kafka, benefiting from its speed and reliability.
- Users appreciate the **easy integrations** of Apache Kafka, enabling smooth connections between various applications in their systems.
- Users value the **high scalability and performance** of Apache Kafka, perfect for managing growing data volumes in enterprises.
- Users value the **high scalability and performance** of Apache Kafka, ideal for handling growing data volumes efficiently.

**Cons:**

- Users find the **operational complexity** of Apache Kafka challenging, impacting resource efficiency and queuing capabilities.
- Users find the **data management challenges** of Apache Kafka overwhelming, especially for smaller teams lacking dedicated expertise.
- Users find **debugging issues** in Apache Kafka challenging, often requiring significant time and effort to resolve effectively.
- Users find the **difficult learning curve** for Apache Kafka overwhelming, especially for smaller teams managing its complexities.
- Users find **limited customization** challenging during setup, especially when managing brokers and zookeepers in distributed systems.

#### What Are Recent G2 Reviews of Apache Kafka?

**"[Kafka Delivers Scalable, Durable Real-Time Performance](https://www.g2.com/survey_responses/apache-kafka-review-12660700)"**

**Rating:** 5.0/5.0 stars
*— Aayush M.*

[Read full review](https://www.g2.com/survey_responses/apache-kafka-review-12660700)

---

**"[Reliable Real-Time Data Streaming at Scale with Kafka](https://www.g2.com/survey_responses/apache-kafka-review-12593230)"**

**Rating:** 4.0/5.0 stars
*— Verified User in Retail*

[Read full review](https://www.g2.com/survey_responses/apache-kafka-review-12593230)

---


#### What Are G2 Users Discussing About Apache Kafka?

- [What is your primary use case for Apache Kafka, and how has it impacted your data streaming processes?](https://www.g2.com/discussions/what-is-your-primary-use-case-for-apache-kafka-and-how-has-it-impacted-your-data-streaming-processes)
- [What is Apache Kafka used for?](https://www.g2.com/discussions/apache-kafka-what-is-apache-kafka-used-for) - 1 comment
- [What is Apache Kafka architecture?](https://www.g2.com/discussions/apache-kafka-what-is-apache-kafka-architecture)
- [What is Kafka in software?](https://www.g2.com/discussions/what-is-kafka-in-software)
- [What are the characteristics of Apache Kafka?](https://www.g2.com/discussions/apache-kafka-what-are-the-characteristics-of-apache-kafka)

### 5. [Confluent](https://www.g2.com/products/confluent/reviews)
Cloud-native service for data in motion built by the original creators of Apache Kafka® Today’s consumers have the world at their fingertips and hold an unforgiving expectation for end-to-end real-time brand experiences. Data in motion is the underlying, fundamental ingredient to any truly connected customer experience. It provides a continuous supply of real- time event streams coupled with real-time stream processing to power the data-driven backend operations and rich front-end experiences necessary for any business to succeed within today’s competitive, consumer-driven markets. Set your data in motion while avoiding the headaches of infrastructure management and focus on what matters most: your business. Built by the original creators of Apache Kafka, Confluent Cloud is a fully managed, cloud-native service for connecting and processing all of your real-time data, everywhere it’s needed.


**Average Rating:** 4.4/5.0
**Total Reviews:** 111
**How Do G2 Users Rate Confluent?**

- **Has the product been a good partner in doing business?:** 8.5/10 (Category avg: 8.9/10)
- **Data Sources:** 8.8/10 (Category avg: 8.6/10)
- **Data Processing:** 8.8/10 (Category avg: 8.8/10)
- **Real-Time Processing:** 9.0/10 (Category avg: 9.1/10)

**Who Is the Company Behind Confluent?**

- **Seller:** [IBM](https://www.g2.com/sellers/ibm)
- **Year Founded:** 1911
- **HQ Location:** Armonk, New York, United States
- **Twitter:** @IBMSecurity (74,660 Twitter followers)
- **LinkedIn® Page:** https://www.linkedin.com/company/1009/ (328,202 employees on LinkedIn®)
- **Ownership:** SWX:IBM

**Who Uses This Product?**
- **Who Uses This:** Senior Software Engineer, Software Engineer
- **Top Industries:** Computer Software, Information Technology and Services
- **Company Size:** 36% Enterprise, 34% Small-Business


#### What Are Confluent's Pros and Cons?

**Pros:**

- Cloud Computing (1 reviews)
- Cloud Services (1 reviews)
- Connectors (1 reviews)
- Data Integration (1 reviews)
- Ease of Use (1 reviews)

**Cons:**

- Cost Estimation (1 reviews)
- Expensive (1 reviews)
- Initial Difficulties (1 reviews)
- Lack of Features (1 reviews)
- Learning Curve (1 reviews)


### What Do G2 Reviewers Say About Confluent?
*AI-generated summary from verified user reviews*

**Pros:**

- Users appreciate the **seamless integration and scalability** of Confluent’s cloud services, enhancing their real-time data processing experience.
- Users appreciate the **simplicity and scalability** of Confluent's cloud services, enhancing their data integration experience significantly.
- Users appreciate the **wide range of connectors** in Confluent, making real-time data integration effortless and efficient.
- Users appreciate the **effortless real-time data integration** with Confluent's intuitive UI and wide range of connectors.
- Users appreciate the **ease of use** of Confluent, making real-time data integration effortlessly manageable.

**Cons:**

- Users find the **cost estimation burdensome** as data grows, causing pricing to increase significantly.
- Users find Confluent to be **expensive** as costs rise with data growth, alongside a steep learning curve.
- Users face a **steep learning curve** and escalating costs as data volume increases, complicating the onboarding process.
- Users find a **lack of features** in Confluent unless they upgrade to the costly Enterprise edition.
- Users find a **steep learning curve** with Confluent, requiring significant time to master the workflow.

#### What Are Recent G2 Reviews of Confluent?

**"[Easy to Configure with Few Skill Requirements](https://www.g2.com/survey_responses/confluent-review-12019498)"**

**Rating:** 5.0/5.0 stars
*— Verified User in Broadcast Media*

[Read full review](https://www.g2.com/survey_responses/confluent-review-12019498)

---

**"[Effortless Kafka Management with Confluent](https://www.g2.com/survey_responses/confluent-review-12744384)"**

**Rating:** 4.5/5.0 stars
*— Abhishek g.*

[Read full review](https://www.g2.com/survey_responses/confluent-review-12744384)

---


#### What Are G2 Users Discussing About Confluent?

- [What is your primary use case for Confluent, and how does it enhance your real-time data streaming?](https://www.g2.com/discussions/what-is-your-primary-use-case-for-confluent-and-how-does-it-enhance-your-real-time-data-streaming) - 1 upvote
- [What is Confluent product?](https://www.g2.com/discussions/what-is-confluent-product)
- [What does Confluent software do?](https://www.g2.com/discussions/what-does-confluent-software-do)
- [What is the difference between Confluent and Kafka?](https://www.g2.com/discussions/what-is-the-difference-between-confluent-and-kafka)
- [Is Confluent SaaS or PaaS?](https://www.g2.com/discussions/is-confluent-saas-or-paas)

### 6. [Red Hat OpenShift Streams for Apache Kafka](https://www.g2.com/products/red-hat-openshift-streams-for-apache-kafka/reviews)
Red Hat® OpenShift® Streams for Apache Kafka is a managed cloud service that provides a streamlined developer experience for building, deploying, and scaling new cloud-native applications or modernizing existing systems.


**Average Rating:** 4.4/5.0
**Total Reviews:** 26
**How Do G2 Users Rate Red Hat OpenShift Streams for Apache Kafka?**

- **Has the product been a good partner in doing business?:** 9.2/10 (Category avg: 8.9/10)
- **Data Sources:** 8.6/10 (Category avg: 8.6/10)
- **Data Processing:** 8.3/10 (Category avg: 8.8/10)
- **Real-Time Processing:** 8.5/10 (Category avg: 9.1/10)

**Who Is the Company Behind Red Hat OpenShift Streams for Apache Kafka?**

- **Seller:** [Red Hat](https://www.g2.com/sellers/red-hat)
- **Year Founded:** 1993
- **HQ Location:** Raleigh, NC
- **Twitter:** @RedHat (300,769 Twitter followers)
- **LinkedIn® Page:** https://www.linkedin.com/company/3545/ (19,413 employees on LinkedIn®)

**Who Uses This Product?**
- **Top Industries:** Computer Software
- **Company Size:** 42% Small-Business, 38% Enterprise



#### What Are Recent G2 Reviews of Red Hat OpenShift Streams for Apache Kafka?

**"[RedHat OpenShift Streams is easier, optimized, efficient and scalable to manage & deploy application](https://www.g2.com/survey_responses/red-hat-openshift-streams-for-apache-kafka-review-8086771)"**

**Rating:** 5.0/5.0 stars
*— Verified User in Computer Software*

[Read full review](https://www.g2.com/survey_responses/red-hat-openshift-streams-for-apache-kafka-review-8086771)

---

**"[powerful and highly scalable platform](https://www.g2.com/survey_responses/red-hat-openshift-streams-for-apache-kafka-review-7841600)"**

**Rating:** 4.0/5.0 stars
*— Wahidun N.*

[Read full review](https://www.g2.com/survey_responses/red-hat-openshift-streams-for-apache-kafka-review-7841600)

---


#### What Are G2 Users Discussing About Red Hat OpenShift Streams for Apache Kafka?

- [What is Red Hat OpenShift Streams for Apache Kafka used for?](https://www.g2.com/discussions/what-is-red-hat-openshift-streams-for-apache-kafka-used-for)

### 7. [Spark Streaming](https://www.g2.com/products/spark-streaming/reviews)
Spark Streaming brings Apache Spark's language-integrated API to stream processing, letting you write streaming jobs the same way you write batch jobs. It supports Java, Scala and Python. Spark Streaming recovers both lost work and operator state (e.g. sliding windows) out of the box, without any extra code on your part.


**Average Rating:** 4.2/5.0
**Total Reviews:** 38
**How Do G2 Users Rate Spark Streaming?**

- **Has the product been a good partner in doing business?:** 8.5/10 (Category avg: 8.9/10)
- **Data Sources:** 9.0/10 (Category avg: 8.6/10)
- **Data Processing:** 9.2/10 (Category avg: 8.8/10)
- **Real-Time Processing:** 9.0/10 (Category avg: 9.1/10)

**Who Is the Company Behind Spark Streaming?**

- **Seller:** [The Apache Software Foundation](https://www.g2.com/sellers/the-apache-software-foundation)
- **Year Founded:** 1999
- **HQ Location:** Wakefield, MA
- **Twitter:** @TheASF (66,168 Twitter followers)
- **LinkedIn® Page:** https://www.linkedin.com/company/215982/ (2,470 employees on LinkedIn®)

**Who Uses This Product?**
- **Top Industries:** Information Technology and Services, Computer Software
- **Company Size:** 43% Mid-Market, 30% Small-Business



#### What Are Recent G2 Reviews of Spark Streaming?

**"[A Heartfelt Thanks for the Amazing Amazon Apache Spark Streaming](https://www.g2.com/survey_responses/spark-streaming-review-8197254)"**

**Rating:** 5.0/5.0 stars
*— Sai kiran S.*

[Read full review](https://www.g2.com/survey_responses/spark-streaming-review-8197254)

---

**"[Best tool for building large scale data pipelines](https://www.g2.com/survey_responses/spark-streaming-review-8899059)"**

**Rating:** 4.5/5.0 stars
*— K Madhusudan C.*

[Read full review](https://www.g2.com/survey_responses/spark-streaming-review-8899059)

---


#### What Are G2 Users Discussing About Spark Streaming?

- [What is Spark Streaming used for?](https://www.g2.com/discussions/what-is-spark-streaming-used-for)
- [What is the difference between spark streaming and structured streaming?](https://www.g2.com/discussions/what-is-the-difference-between-spark-streaming-and-structured-streaming)
- [How does Kafka integrate with spark streaming?](https://www.g2.com/discussions/how-does-kafka-integrate-with-spark-streaming)
- [What are the main features of Apache spark?](https://www.g2.com/discussions/what-are-the-main-features-of-apache-spark)
- [What is spark streaming checkpoint?](https://www.g2.com/discussions/what-is-spark-streaming-checkpoint)


## What Is Event Stream Processing Software?

[Big Data Software](https://www.g2.com/categories/big-data)

## What Software Categories Are Similar to Event Stream Processing Software?

- [Big Data Processing And Distribution Systems](https://www.g2.com/categories/big-data-processing-and-distribution)
- [ETL Tools](https://www.g2.com/categories/etl-tools)
- [Stream Analytics Software](https://www.g2.com/categories/stream-analytics)


---

## How Do You Choose the Right Event Stream Processing Software?

### What You Should Know About Event Stream Processing Software

### What is Event Stream Processing Software?

Data is stored and subsequently processed with traditional data processing tools. This method is not effective when data is constantly changing, as by the time the data has been stored and analyzed, it has likely already changed and become obsolete.

Event stream processing, also known as stream processing, helps ease these concerns by processing the data when it is on the move. As opposed to batch processing, which focuses on data at rest, stream processing allows for the processing of an uninterrupted flow of records. With event stream processing, the data is constantly arriving, with the focus being on identifying how the data has changed over time or detecting anomalies in the historical data, or both.

Key Benefits of Event Stream Processing Software

- Allow for extremely low latency
- Analyze data in real time
- Scale data processing, giving the user the ability to handle any amount of streaming data and process data from numerous sources

### Why Use Event Stream Processing Software?

Event stream processing software is incomplete without the ability to manipulate data as it arrives. This software assists with on-the-fly processing, letting users aggregate, perform joins of data within a stream, and more. Users leverage stream processing tools to process data transferred among a whole range of internet of things (IoT) endpoints and devices, including smart cars, machinery, or home appliances. Real-time data processing is key when companies want deeper insight into their data; it is also helpful when time is of the essence—for example, in the case of retail companies looking to keep a constant and consistent record of their inventory across multiple channels.

**Gain insights from data —** Users leverage event stream processing software as a buffer to connect a company’s many data sources to a data storage solution, such as a data lake. From movie watching on a streaming service to taxi rides on a ride-hailing app, this data can be used for pattern identification and to inform business decisions.

**Real time integration—** Through the continuous collection of data from data sources, such as databases, sensors, messaging systems, and logs, users are able to ensure their applications which rely on this data are up to date.

**Control data flows —** Event stream processing software makes it easier to create, visualize, monitor, and maintain data flows.

### Who Uses Event Stream Processing Software?

Business users working with data use event stream processing software which gives them access to data in real time.

**Developers —** Developers looking to build event streaming applications that rely on the flow of big data benefit from event stream processing software. For example, batch processing does not serve an application well that is aimed at providing recommendations based on real-time data. Therefore, developers rely on event stream processing software to best handle this data and process it effectively and efficiently.

**Analysts —** To analyze big data as it comes, analysts need to utilize a tool that processes the data. With event stream processing software, they are equipped with the proper tools to integrate the data into their analytics platforms.

**Machine learning engineers —** Data is a key component of the training and development of machine learning models. Having the right data processing software in place is an important part of this process.

### Kinds of Event Stream Processing software

There are different methods or manners in which the stream processing takes place.

**At-rest analytics —** Like log analysis, at rest-analytics looks back on historical data to find trends.

**In-stream analytics —** A more complex form of analysis occurs with in-stream analytics in which data streams between or across devices are analyzed.

**Edge analytics —** This method has the added benefit of potentially lowering the latency for data that is processed on device (for example an IoT device), as the data does not necessarily need to be sent to the cloud.

### Event Stream Processing Software Features

Event stream processing software, with processing at its core, provides users with the capabilities they need to integrate their data for purposes such as analytics and application development. The following features help to facilitate these tasks:

**Connectors —** With connectors to a wide range of core systems (e.g., via an API), users extend the reach of existing enterprise assets.

**Metrics —** Metrics help users analyze the processing to ascertain its performance.

**Change data capture (CDC) —** CDC turns databases into a streaming data source where each new transaction is delivered to event stream processing software instantaneously.

**Data validation—** Data validation allows users to visualize the data flow and ensure their data and data delivery is validated.

**Pre-built data pipelines —** Some tools provide pre-built data pipelines to enable operational workloads in the cloud.

### Trends Related to Event Stream Processing Software

Although data has been around in some form for a long while, the sheer volume, velocity, and variety due to innovations like IoT is unprecedented. As such, technology like artificial intelligence (AI) is helping to make data management and processing manageable.

**Internet of things (IoT) —** With the proliferation of IoT comes the proliferation of varied data types. Event stream processing software must facilitate the processing of these multifarious data types. Also, IoT data is typically fast moving and frequently changing. It is critical that these solutions provide the ability to ingest and integrate this kind of data.

**Embedded AI —** Machine and deep learning functionality is getting increasingly embedded in nearly all types of software, irrespective of whether the user is aware of it or not. The use of embedded AI inside software like CRM, marketing automation, and analytics solutions is allowing users to streamline processes, automate certain tasks, and gain a competitive edge with predictive capabilities.

Data integration tools like event stream processing software will become increasingly more important, as AI is fueled by data. Embedded AI may gradually pick up and it may do so in the way cloud deployment and mobile capabilities have over the past decade or so. Eventually, vendors may not need to highlight their product benefits from machine learning as it may just be assumed and expected.

**Self service offerings —** As with other types of data tools (such as analytics platforms), there is an increasing trend for software to be of the self-service nature. This means that nonprofessionals should be able to use the tool easily with little to no IT support for setting it up. With drag-and-drop interfaces or highly customizable setups, average business users are being empowered by statistical analysis capabilities.

### Potential Issues with Event Stream Processing Software

**Data organization —** It may be challenging to organize data in a way that is easily accessible and harness big data sets that contain historical and real-time data. Companies often need to build a data warehouse or a data lake that combines all the disparate data sources for easy access. This requires highly skilled employees.

**Deployment issues —** Search software requires lots of work by a skilled development team or vendor support staff to properly deploy the solution, especially if the data is particularly messy. Some data may lack compatibility with different products while some solutions may be geared for different types of data. For example, some solutions may not be optimized for unstructured data, whilst others may be the best fit for numerical data.

### Software and Services Related to Event Stream Processing Software

The following solutions can be used in conjunction with or instead of the products in this category to be able to integrate and analyze data.

**Stream analytics software —** [Stream analytics software](https://www.g2.com/categories/stream-analytics) helps users looking for tools specifically geared toward analyzing, as opposed to just processing data in real time. These tools help users analyze data in transfer through APIs, between applications, and more. This software is helpful with IoT data that needs frequent analysis in real time.

**Big data integration platforms —** [Big data integration platforms](https://www.g2.com/categories/big-data-integration-platform) are robust and help users manage and store big data clusters and use them within cloud applications.

**Analytics platforms —** [Analytics platforms](https://www.g2.com/categories/analytics-platforms) include big data integrations, but are broader-focused tools which facilitate five elements: data preparation, data modeling, data blending, data visualization, and insights delivery.

**Log analysis software —** [Log analysis software](https://www.g2.com/categories/log-analysis) is a tool that gives users the ability to analyze log files. This type of software includes visualizations and is particularly useful for monitoring and alerting purposes.

**Data preparation software —** Key solutions necessary for easy data analysis is [data preparation software](https://www.g2.com/categories/data-preparation) and other related data management tools. These solutions allow users to discover, combine, clean, and enrich data for simple analysis. Data preparation tools are used by IT or data analysts tasked with using business intelligence tools. Some business intelligence platforms offer data preparation features but businesses with a wide range of data sources often opt for a dedicated data preparation tool.

**Data warehouses—** Most companies have a large number of disparate data sources. To best integrate all their data, they implement [data warehouse software](https://www.g2.com/categories/data-warehouse). Data warehouses house data from multiple databases and business applications, that allow business intelligence and analytics tools to pull all company data from a single repository. This organization is critical to the quality of the data that is ingested by analytics software.