# Best Event Stream Processing Software

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

   Event stream processing software allows for the processing of data on the fly, enabling users to properly store, manage, and analyze their streaming data. In contrast to batch processing which focuses on historical data, stream processing allows for the processing of data in real time. Event stream processing software gives users the ability to examine how their data has changed over time. It also helps users by providing insight into anomalies and trends in the data.

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. If the user is focused on data analysis, above and beyond processing, [stream analytics software](https://www.g2.com/categories/stream-analytics) is a good solution to consider.

To qualify for inclusion in the Event Stream Processing category, a product must:

- Connect to a wide range of core systems and provide the ability to process the data in real time
- Offer the ability to analyze the processing of data to ascertain its performance
- Allow users to visualize the data flow and ensure that data and data delivery is validated





## Category Overview

**Total Products under this Category:** 70


## Trust & Credibility Stats

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

- 30 Analysts and Data Experts
- 2,300+ 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.


## Best Event Stream Processing Software At A Glance

- **Leader:** [Aiven for Apache Kafka](https://www.g2.com/products/aiven-for-apache-kafka/reviews)
- **Highest Performer:** [Ably Realtime](https://www.g2.com/products/ably-realtime/reviews)
- **Easiest to Use:** [Redpanda Data](https://www.g2.com/products/redpanda-data/reviews)
- **Top Trending:** [Redpanda Data](https://www.g2.com/products/redpanda-data/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 company 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%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%252Fconfluent%252Fwishlists%253Fhost_path%253D%25252Fcategories%25252Fevent-stream-processing%25252Fenterprise%2526source%253Dcategory&secure%5Btoken%5D=a60243328e1c992ac7244343d1a70342d0662a67ab3074b05d1f82ff6fddac85&secure%5Burl%5D=http%3A%2F%2Ffactorhouse.io%2F&secure%5Burl_type%5D=custom_url)

---

## Top-Rated Products (Ranked by G2 Score)
  ### 1. [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:** 244

**User Satisfaction Scores:**

- **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)


**Seller Details:**

- **Seller:** [Aiven](https://www.g2.com/sellers/aiven)
- **Company Website:** https://aiven.io/
- **Year Founded:** 2016
- **HQ Location:** Helsinki, Southern Finland
- **Twitter:** @aiven_io (4,084 Twitter followers)
- **LinkedIn® Page:** https://www.linkedin.com/company/10294984/ (439 employees on LinkedIn®)

**Reviewer Demographics:**
  - **Who Uses This:** Software Engineer, Senior Software Engineer
  - **Top Industries:** Computer Software, Information Technology and Services
  - **Company Size:** 44% Mid-Market, 29% Small-Business


#### Pros & Cons

**Pros:**

- Setup Ease (29 reviews)
- Ease of Use (24 reviews)
- Scaling (17 reviews)
- Management Ease (14 reviews)
- Reliability (14 reviews)

**Cons:**

- Expensive (28 reviews)
- Poor Documentation (8 reviews)
- Limited Features (7 reviews)
- Complexity (6 reviews)
- Not User-Friendly (5 reviews)

  ### 2. [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

**User Satisfaction Scores:**

- **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:** 9.1/10 (Category avg: 9.1/10)


**Seller Details:**

- **Seller:** [Confluent](https://www.g2.com/sellers/confluent)
- **Year Founded:** 2014
- **HQ Location:** Mountain View, California
- **Twitter:** @ConfluentInc (43,597 Twitter followers)
- **LinkedIn® Page:** https://www.linkedin.com/company/88873/ (3,706 employees on LinkedIn®)
- **Ownership:** NASDAQ: CFLT

**Reviewer Demographics:**
  - **Who Uses This:** Software Engineer, Senior Software Engineer
  - **Top Industries:** Computer Software, Information Technology and Services
  - **Company Size:** 36% Enterprise, 35% Small-Business


#### Pros & 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)

  ### 3. [Google Cloud Dataflow](https://www.g2.com/products/google-cloud-dataflow/reviews)
  Cloud Dataflow is a fully-managed service for transforming and enriching data in stream (real time) and batch (historical) modes with equal reliability and expressiveness -- no more complex workarounds or compromises needed. And with its serverless approach to resource provisioning and management, you have access to virtually limitless capacity to solve your biggest data processing challenges, while paying only for what you use.


  **Average Rating:** 4.2/5.0
  **Total Reviews:** 43

**User Satisfaction Scores:**

- **Has the product been a good partner in doing business?:** 9.0/10 (Category avg: 8.9/10)
- **Data Sources:** 9.6/10 (Category avg: 8.6/10)
- **Data Processing:** 9.8/10 (Category avg: 8.8/10)
- **Real-Time Processing:** 9.6/10 (Category avg: 9.1/10)


**Seller Details:**

- **Seller:** [Google](https://www.g2.com/sellers/google)
- **Year Founded:** 1998
- **HQ Location:** Mountain View, CA
- **Twitter:** @google (31,885,216 Twitter followers)
- **LinkedIn® Page:** https://www.linkedin.com/company/1441/ (336,169 employees on LinkedIn®)
- **Ownership:** NASDAQ:GOOG

**Reviewer Demographics:**
  - **Top Industries:** Computer Software
  - **Company Size:** 38% Small-Business, 33% Mid-Market


#### Pros & Cons

**Pros:**

- Analytics (1 reviews)
- Ease of Use (1 reviews)
- Easy Management (1 reviews)
- Features (1 reviews)
- Insights (1 reviews)

**Cons:**

- Cost Management (1 reviews)
- Expensive (1 reviews)
- Installation Difficulty (1 reviews)
- Learning Difficulty (1 reviews)

  ### 4. [Amazon Managed Streaming for Apache Kafka (Amazon MSK)](https://www.g2.com/products/amazon-managed-streaming-for-apache-kafka-amazon-msk/reviews)
  Amazon Managed Streaming for Apache Kafka (Amazon MSK) is an AWS streaming data service that manages Apache Kafka infrastructure and operations, making it easy for developers and DevOps managers to run Apache Kafka applications and Kafka Connect connectors on AWS, without the need to become experts in operating Apache Kafka. Amazon MSK operates, maintains, and scales Apache Kafka clusters, provides enterprise-grade security features out of the box, and has built-in AWS integrations that accelerate development of streaming data applications. To get started, you can migrate existing Apache Kafka workloads and Kafka Connect connectors into Amazon MSK, or with a few clicks, you can build new ones from scratch. There are no data transfer charges for in-cluster traffic, and no commitments or upfront payments required. You only pay for the resources that you use.


  **Average Rating:** 4.0/5.0
  **Total Reviews:** 21

**User Satisfaction Scores:**

- **Has the product been a good partner in doing business?:** 8.1/10 (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:** 8.8/10 (Category avg: 9.1/10)


**Seller Details:**

- **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 (2,223,984 Twitter followers)
- **LinkedIn® Page:** https://www.linkedin.com/company/amazon-web-services/ (156,424 employees on LinkedIn®)
- **Ownership:** NASDAQ: AMZN

**Reviewer Demographics:**
  - **Top Industries:** Computer Software
  - **Company Size:** 50% Small-Business, 36% Mid-Market


#### Pros & Cons

**Pros:**

- Cloud Services (1 reviews)
- Maintenance Ease (1 reviews)
- Management Ease (1 reviews)
- Reliability (1 reviews)
- Scalability (1 reviews)

**Cons:**

- Expensive (1 reviews)
- Limitations (1 reviews)
- Limited Control (1 reviews)

  ### 5. [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:** 81

**User Satisfaction Scores:**

- **Has the product been a good partner in doing business?:** 8.6/10 (Category avg: 8.9/10)
- **Data Sources:** 9.1/10 (Category avg: 8.6/10)
- **Data Processing:** 9.0/10 (Category avg: 8.8/10)
- **Real-Time Processing:** 9.4/10 (Category avg: 9.1/10)


**Seller Details:**

- **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 (2,223,984 Twitter followers)
- **LinkedIn® Page:** https://www.linkedin.com/company/amazon-web-services/ (156,424 employees on LinkedIn®)
- **Ownership:** NASDAQ: AMZN

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


#### Pros & 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)

  ### 6. [IBM Event Streams](https://www.g2.com/products/ibm-event-streams/reviews)
  IBM Event Streams is a high-throughput, fault-tolerant, event streaming solution. Powered by Apache Kafka, it provides access to enterprise data through event streams, enabling businesses to unlock insights from historical data, and identify and take action on situations in real time and at scale.


  **Average Rating:** 4.3/5.0
  **Total Reviews:** 12

**User Satisfaction Scores:**

- **Has the product been a good partner in doing business?:** 8.3/10 (Category avg: 8.9/10)
- **Data Sources:** 9.4/10 (Category avg: 8.6/10)
- **Data Processing:** 9.4/10 (Category avg: 8.8/10)
- **Real-Time Processing:** 10.0/10 (Category avg: 9.1/10)


**Seller Details:**

- **Seller:** [IBM](https://www.g2.com/sellers/ibm)
- **Year Founded:** 1911
- **HQ Location:** Armonk, NY
- **Twitter:** @IBM (709,023 Twitter followers)
- **LinkedIn® Page:** https://www.linkedin.com/company/1009/ (324,553 employees on LinkedIn®)
- **Ownership:** SWX:IBM

**Reviewer Demographics:**
  - **Company Size:** 54% Enterprise, 23% Mid-Market


#### Pros & Cons

**Pros:**

- Ease of Use (1 reviews)
- User Interface (1 reviews)


  ### 7. [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

**User Satisfaction Scores:**

- **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)


**Seller Details:**

- **Seller:** [IBM](https://www.g2.com/sellers/ibm)
- **Year Founded:** 1911
- **HQ Location:** Armonk, NY
- **Twitter:** @IBM (709,023 Twitter followers)
- **LinkedIn® Page:** https://www.linkedin.com/company/1009/ (324,553 employees on LinkedIn®)
- **Ownership:** SWX:IBM

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


#### Pros & 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)

  ### 8. [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

**User Satisfaction Scores:**

- **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)


**Seller Details:**

- **Seller:** [The Apache Software Foundation](https://www.g2.com/sellers/the-apache-software-foundation)
- **Year Founded:** 1999
- **HQ Location:** Wakefield, MA
- **Twitter:** @TheASF (66,116 Twitter followers)
- **LinkedIn® Page:** https://www.linkedin.com/company/215982/ (2,408 employees on LinkedIn®)

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


#### Pros & 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)

  ### 9. [RudderStack](https://www.g2.com/products/rudderstack/reviews)
  RudderStack is the leading warehouse native CDP designed to help organizations efficiently collect, unify, and activate customer data across various channels. This end-to-end solution empowers data teams to streamline their data management processes, enabling businesses to leverage insights for growth and improved customer engagement. By integrating seamlessly with existing systems, RudderStack facilitates a comprehensive view of customer interactions, which is crucial for informed decision-making. Targeted primarily at data teams, RudderStack serves a diverse range of industries, including retail, finance, healthcare, media and technology. Its user-friendly interface and robust capabilities make it suitable for organizations looking to enhance their data strategy without the need for extensive technical expertise. Key features of RudderStack include its ability to integrate with various data sources and destinations, ensuring that organizations can centralize their customer data effectively. The platform supports a wide array of integrations with popular tools and services, allowing users to connect their existing tech stack effortlessly. Additionally, RudderStack offers advanced data transformation capabilities, enabling teams to clean and enrich their data before utilizing it for analytics or marketing campaigns. One of the standout benefits of RudderStack is its warehouse-native architecture, which allows businesses to store their customer data directly in their data warehouse. This approach not only enhances data security but also provides organizations with greater control over their data. By eliminating the need for third-party data storage solutions, RudderStack helps businesses reduce costs and improve data accessibility. Furthermore, the platform's flexibility allows for real-time data updates, ensuring that teams are always working with the most current information. Overall, RudderStack is a powerful tool for organizations aiming to harness the full potential of their customer data. With its comprehensive features and focus on unifying data from various sources, it stands out in the competitive landscape of customer data platforms, making it a valuable asset for businesses looking to drive growth and enhance customer experiences. Over 30,000 sites and apps run RudderStack including Crate & Barrel, Foot Locker, Glassdoor, Stripe, Allbirds, and more. RudderStack acquired Blendo in 2020


  **Average Rating:** 4.7/5.0
  **Total Reviews:** 51

**User Satisfaction Scores:**

- **Has the product been a good partner in doing business?:** 9.5/10 (Category avg: 8.9/10)
- **Data Sources:** 9.7/10 (Category avg: 8.6/10)
- **Data Processing:** 9.4/10 (Category avg: 8.8/10)
- **Real-Time Processing:** 9.8/10 (Category avg: 9.1/10)


**Seller Details:**

- **Seller:** [RudderStack](https://www.g2.com/sellers/rudderstack)
- **Company Website:** https://www.rudderstack.com
- **Year Founded:** 2019
- **HQ Location:** San Francisco, California
- **Twitter:** @RudderStack (1,685 Twitter followers)
- **LinkedIn® Page:** https://www.linkedin.com/company/rudderlabs/about (127 employees on LinkedIn®)

**Reviewer Demographics:**
  - **Who Uses This:** Data Engineer
  - **Top Industries:** Computer Software, Information Technology and Services
  - **Company Size:** 54% Mid-Market, 46% Small-Business


#### Pros & Cons

**Pros:**

- Ease of Use (18 reviews)
- Customer Support (16 reviews)
- Easy Integration (11 reviews)
- Easy Setup (9 reviews)
- Easy Integrations (8 reviews)

**Cons:**

- Learning Curve (10 reviews)
- Limited Customization (5 reviews)
- Complexity (4 reviews)
- Insufficient Guidance (4 reviews)
- Onboarding Difficulties (4 reviews)

  ### 10. [Ably Realtime](https://www.g2.com/products/ably-realtime/reviews)
  Ably helps teams deliver resilient AI UX and high-performance live experiences that stay fast and in sync worldwide. We provide the global realtime layer for AI agents, chat, notifications, live dashboards, and collaboration - engineered to handle peak demand without self-managed infrastructure. Teams like HubSpot and Intercom use Ably to avoid the cost and complexity of building and operating realtime systems, while still getting predictable performance at serious scale, handling 2T+ API operations per month. Ably’s Pub/Sub, Chat, and AI Transport products are unified by design, with developer-friendly APIs and SDKs that integrate across your stack.


  **Average Rating:** 4.8/5.0
  **Total Reviews:** 67

**User Satisfaction Scores:**

- **Has the product been a good partner in doing business?:** 9.4/10 (Category avg: 8.9/10)
- **Data Sources:** 8.1/10 (Category avg: 8.6/10)
- **Data Processing:** 9.0/10 (Category avg: 8.8/10)
- **Real-Time Processing:** 9.2/10 (Category avg: 9.1/10)


**Seller Details:**

- **Seller:** [Ably Realtime](https://www.g2.com/sellers/ably-realtime)
- **Year Founded:** 2016
- **HQ Location:** London, GB
- **Twitter:** @ablyrealtime (1,856 Twitter followers)
- **LinkedIn® Page:** https://www.linkedin.com/company/ably-realtime (119 employees on LinkedIn®)

**Reviewer Demographics:**
  - **Who Uses This:** Software Engineer
  - **Top Industries:** Information Technology and Services, Computer Software
  - **Company Size:** 45% Small-Business, 28% Mid-Market


#### Pros & Cons

**Pros:**

- Customer Support (14 reviews)
- Ease of Use (14 reviews)
- Easy Integrations (13 reviews)
- Reliability (11 reviews)
- Fast Communication (8 reviews)

**Cons:**

- Expensive (6 reviews)
- Pricing Issues (4 reviews)
- Data Management Issues (2 reviews)
- Learning Curve (2 reviews)
- Limitations (2 reviews)

  ### 11. [Redpanda Data](https://www.g2.com/products/redpanda-data/reviews)
  Redpanda is the streaming platform that simplifies building real-time AI applications. It’s a simple, fast, and secure solution that lets modern engineering teams ship streaming, analytics, and agentic AI apps without the complexity or cost of traditional Kafka-based systems. It comes with 300+ built-in connectors, Kafka-API compatibility and industry-leading data and AI governance with a Bring-Your- Own-Cloud (BYOC) deployment option. Global leaders including Activision Blizzard, Cisco, Moody's, Texas Instruments, Vodafone and 2 of the top 5 banks in the U.S. rely on Redpanda to process hundreds of terabytes of data a day. Backed by premier venture investors Lightspeed, GV and Haystack VC, Redpanda is a diverse, people-first organization with teams distributed around the globe.


  **Average Rating:** 4.8/5.0
  **Total Reviews:** 22

**User Satisfaction Scores:**

- **Has the product been a good partner in doing business?:** 9.6/10 (Category avg: 8.9/10)
- **Data Sources:** 9.5/10 (Category avg: 8.6/10)
- **Data Processing:** 9.8/10 (Category avg: 8.8/10)
- **Real-Time Processing:** 9.3/10 (Category avg: 9.1/10)


**Seller Details:**

- **Seller:** [Redpanda Data](https://www.g2.com/sellers/redpanda-data)
- **Company Website:** https://redpanda.com/
- **Year Founded:** 2019
- **HQ Location:** San Francisco, US
- **Twitter:** @redpandadata (5,322 Twitter followers)
- **LinkedIn® Page:** https://www.linkedin.com/company/redpanda-data/ (195 employees on LinkedIn®)

**Reviewer Demographics:**
  - **Top Industries:** Computer Software
  - **Company Size:** 64% Mid-Market, 36% Small-Business


#### Pros & Cons

**Pros:**

- Customer Support (14 reviews)
- Ease of Use (13 reviews)
- Performance (8 reviews)
- Speed (7 reviews)
- Features (6 reviews)

**Cons:**

- Complexity (2 reviews)
- Data Management Issues (2 reviews)
- Missing Features (2 reviews)
- Poor Documentation (2 reviews)
- Poor UI Design (2 reviews)

  ### 12. [Svix](https://www.g2.com/products/svix/reviews)
  Svix is the enterprise ready webhooks sending service. With Svix, you can build a secure, reliable, and scalable webhook platform in minutes.


  **Average Rating:** 5.0/5.0
  **Total Reviews:** 14

**User Satisfaction Scores:**

- **Has the product been a good partner in doing business?:** 10.0/10 (Category avg: 8.9/10)
- **Data Sources:** 8.9/10 (Category avg: 8.6/10)
- **Data Processing:** 8.9/10 (Category avg: 8.8/10)
- **Real-Time Processing:** 10.0/10 (Category avg: 9.1/10)


**Seller Details:**

- **Seller:** [Svix](https://www.g2.com/sellers/svix)
- **Year Founded:** 2021
- **HQ Location:** New York, US
- **Twitter:** @SvixHQ (656 Twitter followers)
- **LinkedIn® Page:** https://www.linkedin.com/company/svix/ (11 employees on LinkedIn®)

**Reviewer Demographics:**
  - **Top Industries:** Computer Software
  - **Company Size:** 50% Mid-Market, 50% Small-Business


#### Pros & Cons

**Pros:**

- Communication Efficiency (1 reviews)
- Data Management (1 reviews)
- Ease of Use (1 reviews)
- Easy Integrations (1 reviews)
- Feature Innovation (1 reviews)

**Cons:**

- Complexity (1 reviews)
- Expensive (1 reviews)
- UX Improvement (1 reviews)

  ### 13. [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

**User Satisfaction Scores:**

- **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)


**Seller Details:**

- **Seller:** [Red Hat](https://www.g2.com/sellers/red-hat)
- **Year Founded:** 1993
- **HQ Location:** Raleigh, NC
- **Twitter:** @RedHat (299,757 Twitter followers)
- **LinkedIn® Page:** https://www.linkedin.com/company/3545/ (19,305 employees on LinkedIn®)

**Reviewer Demographics:**
  - **Top Industries:** Computer Software
  - **Company Size:** 42% Small-Business, 38% Enterprise


  ### 14. [IBM Cloud Pak for Integration](https://www.g2.com/products/ibm-cloud-pak-for-integration/reviews)
  IBM Cloud Pak for Integration is a set of capabilities to speed integration and scale automation, built for any hybrid cloud, within a single, unified experience. Unlock business data and assets as APIs, connect cloud and on-premise applications, reliably move data with enterprise messaging, deliver real-time event interactions, transfer data across any cloud and deploy and scale with cloud-native architecture and shared foundational services — all with end-to-end enterprise-grade security and encryption, making up the broadest set of integration capabilities available on the market today.


  **Average Rating:** 4.2/5.0
  **Total Reviews:** 39

**User Satisfaction Scores:**

- **Has the product been a good partner in doing business?:** 7.3/10 (Category avg: 8.9/10)
- **Data Sources:** 8.3/10 (Category avg: 8.6/10)
- **Data Processing:** 8.6/10 (Category avg: 8.8/10)
- **Real-Time Processing:** 8.1/10 (Category avg: 9.1/10)


**Seller Details:**

- **Seller:** [IBM](https://www.g2.com/sellers/ibm)
- **Year Founded:** 1911
- **HQ Location:** Armonk, NY
- **Twitter:** @IBM (709,023 Twitter followers)
- **LinkedIn® Page:** https://www.linkedin.com/company/1009/ (324,553 employees on LinkedIn®)
- **Ownership:** SWX:IBM

**Reviewer Demographics:**
  - **Top Industries:** Information Technology and Services, Computer Software
  - **Company Size:** 36% Enterprise, 36% Mid-Market


  ### 15. [Axual](https://www.g2.com/products/axual/reviews)
  Axual presents a suite of Kafka solutions tailored for enterprises, offering both cloud and on-premise deployment options. Axual Governance simplifies the management of existing Kafka clusters with a user-friendly interface, visual data mapping and robust Role-Based Access Control (RBAC), ensuring secure and streamlined data oversight. Complementing this, Axual Platform extends these capabilities by including a managed Kafka cluster with advanced streaming capabilities. This comprehensive platform is designed for high-performance, real-time data processing, making it ideal for enterprises and large scale organizations seeking efficient and scalable data management solutions. Together, Axual Governance and Axual Platform provide versatile, powerful tools for Kafka operations, adaptable to any enterprise environment.


  **Average Rating:** 4.5/5.0
  **Total Reviews:** 14

**User Satisfaction Scores:**

- **Has the product been a good partner in doing business?:** 9.8/10 (Category avg: 8.9/10)
- **Data Sources:** 7.4/10 (Category avg: 8.6/10)
- **Data Processing:** 9.0/10 (Category avg: 8.8/10)
- **Real-Time Processing:** 9.4/10 (Category avg: 9.1/10)


**Seller Details:**

- **Seller:** [Axual](https://www.g2.com/sellers/axual)
- **Year Founded:** 2015
- **HQ Location:** Jaarbeursplein, Utrecht
- **Twitter:** @axual (67 Twitter followers)
- **LinkedIn® Page:** http://www.linkedin.com/company/axual (44 employees on LinkedIn®)

**Reviewer Demographics:**
  - **Company Size:** 57% Enterprise, 21% Mid-Market


  ### 16. [SAS Viya](https://www.g2.com/products/sas-sas-viya/reviews)
  SAS Viya is a cloud-native data and AI platform that enables teams to build, deploy and scale explainable AI that drives trusted, confident decisions. It unites the entire data and AI life cycle and empowers teams to innovate quickly while balancing speed, automation and governance by design. Viya unifies data management, advanced analytics and decisioning in a single platform, so organizations can move from experimentation to production with confidence, delivering measurable business impact that is secure, explainable and scalable across any environment. Key capabilities required to deliver trusted decisions include: • End-to-end clarity across the data and AI life cycle, with built-in lineage, auditability and continuous monitoring to support defensible decisions. • Governance by design, enabling consistent oversight across data, models and decisions to reduce risk and accelerate adoption. • Explainable AI at scale, so insights and outcomes can be understood, validated and trusted by business and regulators alike. • Operationalized analytics, ensuring value continues beyond deployment through monitoring, retraining and life cycle management. • Flexible, cloud-native deployment, allowing organizations to start anywhere and scale everywhere while maintaining control.


  **Average Rating:** 4.3/5.0
  **Total Reviews:** 711

**User Satisfaction Scores:**

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


**Seller Details:**

- **Seller:** [SAS Institute Inc.](https://www.g2.com/sellers/sas-institute-inc-df6dde22-a5e5-4913-8b21-4fa0c6c5c7c2)
- **Company Website:** https://www.sas.com/
- **Year Founded:** 1976
- **HQ Location:** Cary, NC
- **Twitter:** @SASsoftware (60,996 Twitter followers)
- **LinkedIn® Page:** https://www.linkedin.com/company/1491/ (18,238 employees on LinkedIn®)

**Reviewer Demographics:**
  - **Who Uses This:** Student, Statistical Programmer
  - **Top Industries:** Pharmaceuticals, Computer Software
  - **Company Size:** 33% Enterprise, 33% Small-Business


#### Pros & Cons

**Pros:**

- Ease of Use (316 reviews)
- Features (218 reviews)
- Analytics (196 reviews)
- Data Analysis (166 reviews)
- User Interface (147 reviews)

**Cons:**

- Learning Difficulty (151 reviews)
- Learning Curve (144 reviews)
- Complexity (143 reviews)
- Difficult Learning (117 reviews)
- Expensive (108 reviews)

  ### 17. [Nexla](https://www.g2.com/products/nexla/reviews)
  Nexla is an enterprise-grade, AI-powered data integration platform designed to help organizations unlock data from any source and transform it into production-ready data products for AI and agents. With support for 550+ pre-built connectors and multiple integration styles, including ELT, ETL, streaming, APIs, and agentic RAG, the platform enables teams to build and manage data flows without writing code. Trusted by leading enterprises, Nexla processes over one trillion records per month across industries, ​​showcasing its ability to handle large volumes of data while maintaining performance and reliability. Innovators like Autodesk, DoorDash, Instacart, Johnson & Johnson, LinkedIn, and LiveRamp rely on Nexla to keep mission-critical data flowing seamlessly across their enterprises. Key features of Nexla include flexible deployment across cloud, hybrid, and on-premises environments, ensuring compliance with enterprise-grade security standards such as SOC 2 Type II, GDPR, CCPA, and HIPAA. Nexla delivers 10x faster implementation than traditional alternatives, turning data challenges and variety into competitive advantages. Try our AI Data Engineer at https://express.dev Increase the impact of your data engineering team with next-gen data integration: ✅ Eliminate costly replications & reduce storage bills ✅ Increase engineering productivity & capacity for innovation ✅ Empower users with Pro/Low/No-code collaboration ✅ Cut out maintenance with data validation, quality monitoring, & alerts ✅ Build production-ready custom GenAI applications Go beyond one traditional integration pattern, and invest in data architecture that supports: ✅ Any integration pattern (ELT, ETL, API / API proxy, & RAG - Retrieval Augmented Generation) ✅ Bi-directional connectors out of the box & on demand ✅ Any processing speed (streaming, real-time, batch) ✅ Unstructured, structured, or semi-structured data ✅ Complete data lineage search & tagging for governance ✅ Metadata-driven architecture for agility & scale Nexla is a Gartner Cool Vendor and pairs perfectly with the technologies you rely on: ✅ Compute: AWS, Azure, Google Cloud, On-Premise ✅ Storage: S3, Redshift, BigQuery, Snowflake, Oracle, Databricks, Kafka, Redis, MongoDB, Postgres, MySQL ✅ Applications: SAP, Salesforce, Marketo, Hubspot, Amazon Seller Central, Google Ads, API, Salesforce ✅ Catalogs: Alation, Collibra, data.world ✅ Webhooks, emails, FTP & APIs ✅ Vector database & LLM: Pinecone, GPT, Falcon, LLaMDa And many more Differentiators & Awards 🏆 2025 Highest Rating Gartner Peer Insights™ Voice of the Customer for Data Integration Tools 🏆 2024 Highest Rating Gartner Peer Insights™ Voice of the Customer for Data Integration Tools 🏆 2023 Highest Rating Gartner Peer Insights™ Voice of the Customer for Data Integration Tools 🏆 2022 Highest Rating Gartner Peer Insights™ Voice of the Customer for Data Integration Tools


  **Average Rating:** 4.6/5.0
  **Total Reviews:** 63

**User Satisfaction Scores:**

- **Has the product been a good partner in doing business?:** 9.1/10 (Category avg: 8.9/10)
- **Data Sources:** 9.3/10 (Category avg: 8.6/10)
- **Data Processing:** 9.3/10 (Category avg: 8.8/10)
- **Real-Time Processing:** 9.4/10 (Category avg: 9.1/10)


**Seller Details:**

- **Seller:** [Nexla](https://www.g2.com/sellers/nexla)
- **Company Website:** https://www.nexla.com/
- **Year Founded:** 2016
- **HQ Location:** San Mateo, California
- **Twitter:** @NexlaInc (947 Twitter followers)
- **LinkedIn® Page:** https://www.linkedin.com/company/nexla/ (76 employees on LinkedIn®)

**Reviewer Demographics:**
  - **Top Industries:** Computer Software, Insurance
  - **Company Size:** 41% Mid-Market, 33% Small-Business


#### Pros & Cons

**Pros:**

- Ease of Use (21 reviews)
- Automation (14 reviews)
- Data Management (14 reviews)
- Integrations (13 reviews)
- Data Integration (10 reviews)

**Cons:**

- Learning Difficulty (7 reviews)
- Slow Performance (7 reviews)
- Difficult Learning (6 reviews)
- Learning Curve (6 reviews)
- Poor Documentation (6 reviews)

  ### 18. [Tray.ai](https://www.g2.com/products/tray-ai/reviews)
  Tray.ai offers a composable AI integration and automation platform that transforms AI into standout business performance. The Tray Universal Automation Cloud is an AI-ready platform that eliminates the need for disparate tools, enabling seamless integration and automation of complex business processes. Our platform supports all AI, integration, and automation initiatives from a single place. Developers benefit from a code-first, headless environment, freeing them from mundane tasks and allowing focus on business outcomes. The Tray Build IDE and AI Palette accelerate delivery for business technologists, providing easy access to 3rd party connectors and native AI capabilities. As enterprises strive for competitive advantage, our platform helps IT teams deploy AI effectively, connecting systems, automating processes, and integrating data to handle even the most demanding AI use cases. Built for high-change environments, Tray.ai excels in rapid prototyping, testing, and deployment. The fastest way to turn AI into business performance.™


  **Average Rating:** 4.5/5.0
  **Total Reviews:** 153

**User Satisfaction Scores:**

- **Has the product been a good partner in doing business?:** 9.0/10 (Category avg: 8.9/10)
- **Data Sources:** 9.2/10 (Category avg: 8.6/10)
- **Data Processing:** 8.3/10 (Category avg: 8.8/10)
- **Real-Time Processing:** 8.6/10 (Category avg: 9.1/10)


**Seller Details:**

- **Seller:** [Tray.io](https://www.g2.com/sellers/tray-io)
- **Year Founded:** 2012
- **HQ Location:** San Francisco, CA
- **Twitter:** @tray (3,075 Twitter followers)
- **LinkedIn® Page:** https://www.linkedin.com/company/2659008/ (136 employees on LinkedIn®)

**Reviewer Demographics:**
  - **Top Industries:** Computer Software, Information Technology and Services
  - **Company Size:** 56% Mid-Market, 34% Small-Business


#### Pros & Cons

**Pros:**

- Easy Integrations (9 reviews)
- Ease of Use (7 reviews)
- Integrations (6 reviews)
- Automation (5 reviews)
- Connectors (5 reviews)

**Cons:**

- Missing Features (4 reviews)
- Complex Pricing (3 reviews)
- Expensive (3 reviews)
- Learning Curve (3 reviews)
- Poor Documentation (3 reviews)

  ### 19. [Decodable](https://www.g2.com/products/decodable/reviews)
  Decodable radically simplifies real-time ETL with a powerful, easy-to-use real-time ETL platform. By removing the challenges of building and maintaining infrastructure and pipelines, Decodable enables data teams to eliminate overhead, easily connect sources, perform real-time transformations, and reliably deliver data to any destination.


  **Average Rating:** 4.7/5.0
  **Total Reviews:** 16

**User Satisfaction Scores:**

- **Has the product been a good partner in doing business?:** 10.0/10 (Category avg: 8.9/10)
- **Data Sources:** 9.0/10 (Category avg: 8.6/10)
- **Data Processing:** 8.7/10 (Category avg: 8.8/10)
- **Real-Time Processing:** 9.3/10 (Category avg: 9.1/10)


**Seller Details:**

- **Seller:** [Decodable](https://www.g2.com/sellers/decodable)
- **Year Founded:** 2021
- **HQ Location:** San Francisco, US
- **Twitter:** @Decodableco (2,663 Twitter followers)
- **LinkedIn® Page:** https://www.linkedin.com/company/decodable/ (8 employees on LinkedIn®)

**Reviewer Demographics:**
  - **Company Size:** 44% Small-Business, 38% Mid-Market


#### Pros & Cons

**Pros:**

- Automation (2 reviews)
- Ease of Use (2 reviews)
- Easy Setup (2 reviews)
- Features (2 reviews)
- Implementation Ease (2 reviews)

**Cons:**

- Not User-Friendly (1 reviews)
- Performance Issues (1 reviews)
- Poor Customer Support (1 reviews)
- Poor Performance (1 reviews)
- Resource Intensive Learning (1 reviews)

  ### 20. [Amazon Kinesis Data Firehose](https://www.g2.com/products/amazon-kinesis-data-firehose/reviews)
  Amazon Kinesis Data Firehose is the easiest way to reliably load real-time streams into data lakes, warehouses, and analytics services. Kinesis Data Firehose can capture, transform, and load streaming data into Amazon S3, Amazon Redshift, Amazon OpenSearch Service, and Splunk, enabling near real-time analytics with existing business intelligence tools and dashboards you’re already using today. It is a fully managed service that automatically scales to match the throughput of your data and requires no ongoing administration. It can also batch, compress, and encrypt the data before loading it, minimizing the amount of storage used at the destination and increasing security.


  **Average Rating:** 4.2/5.0
  **Total Reviews:** 20

**User Satisfaction Scores:**

- **Has the product been a good partner in doing business?:** 8.9/10 (Category avg: 8.9/10)
- **Data Sources:** 7.5/10 (Category avg: 8.6/10)
- **Data Processing:** 8.3/10 (Category avg: 8.8/10)
- **Real-Time Processing:** 8.1/10 (Category avg: 9.1/10)


**Seller Details:**

- **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 (2,223,984 Twitter followers)
- **LinkedIn® Page:** https://www.linkedin.com/company/amazon-web-services/ (156,424 employees on LinkedIn®)
- **Ownership:** NASDAQ: AMZN

**Reviewer Demographics:**
  - **Top Industries:** Information Technology and Services
  - **Company Size:** 46% Mid-Market, 33% Enterprise


  ### 21. [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

**User Satisfaction Scores:**

- **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)


**Seller Details:**

- **Seller:** [The Apache Software Foundation](https://www.g2.com/sellers/the-apache-software-foundation)
- **Year Founded:** 1999
- **HQ Location:** Wakefield, MA
- **Twitter:** @TheASF (66,116 Twitter followers)
- **LinkedIn® Page:** https://www.linkedin.com/company/215982/ (2,408 employees on LinkedIn®)

**Reviewer Demographics:**
  - **Top Industries:** Information Technology and Services, Computer Software
  - **Company Size:** 43% Mid-Market, 30% Small-Business


  ### 22. [Instaclustr Managed Kafka](https://www.g2.com/products/instaclustr-managed-kafka/reviews)
  NetApp® Instaclustr for Apache Kafka® is a managed event streaming platform that enables organizations to deploy, operate, and scale Apache Kafka clusters for distributed data processing. It is designed for IT operations teams, DevOps engineers, software architects, and businesses that require reliable, secure, and scalable streaming infrastructure without the complexity of self-managing open source technologies. NetApp Instaclustr for Apache Kafka supports enterprises and technology-driven organizations that need to ingest, process, and analyze large volumes of data in real time. Common use cases include log aggregation, real-time analytics, data pipeline orchestration, and event-driven application architectures. The platform provides automated provisioning, monitoring, scaling, and maintenance of Apache Kafka clusters across public cloud environments and on-premises data centers. Instaclustr offers multiple deployment models, including fully managed clusters, enterprise support, consulting, and training services. Key features and benefits: - Managed Kafka clusters with automated deployment, configuration, and scaling - 24x7 expert support backed by service level agreements (SLAs) - Professional services for architecture, migration, and optimization - Certified training for technical teams on Apache Kafka best practices - Security and compliance controls, including SOC 2, ISO 27001, ISO 27018, GDPR, PCI-DSS, HIPAA NetApp Instaclustr for Apache Kafka helps organizations address challenges such as limited in-house expertise, integration complexity, and the need for reliable, scalable, and secure event streaming operations.


  **Average Rating:** 4.3/5.0
  **Total Reviews:** 11

**User Satisfaction Scores:**

- **Has the product been a good partner in doing business?:** 8.9/10 (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:** 9.2/10 (Category avg: 9.1/10)


**Seller Details:**

- **Seller:** [NetApp](https://www.g2.com/sellers/netapp)
- **Year Founded:** 1992
- **HQ Location:** Sunnyvale, California
- **Twitter:** @NetApp (118,257 Twitter followers)
- **LinkedIn® Page:** https://www.linkedin.com/company/2105/ (12,677 employees on LinkedIn®)
- **Ownership:** NASDAQ

**Reviewer Demographics:**
  - **Company Size:** 55% Enterprise, 27% Mid-Market


  ### 23. [TIBCO BusinessEvents](https://www.g2.com/products/tibco-businessevents/reviews)
  Your enterprise is surrounded by hundreds of thousands of events that occur continuously. Hidden amongst them can be stalled business processes, opportunities for value creation, potential fraud, dissatisfied customers, failing equipment, and more. TIBCO BusinessEvents proactively identifies these critical events, responds intelligently in real-time to navigate the fast-moving business environments and optimize outcomes. Effective decision-making in your business requires a comprehensive understanding of various event types, ranging from historical, current, and expected yet absent events. TIBCO BusinessEvents provides contextual Event Processing and excels in this area. TIBCO BusinessEvents enables your business to handle vast volumes of events that large, complex businesses encounter daily, satisfying the rigorous demands of today’s high-traffic business environment. It is an essential capability of an event-driven architecture (EDA).


  **Average Rating:** 4.3/5.0
  **Total Reviews:** 17

**User Satisfaction Scores:**

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


**Seller Details:**

- **Seller:** [Cloud Software Group](https://www.g2.com/sellers/cloud-software-group)
- **HQ Location:** Fort Lauderdale, FL
- **Twitter:** @cloudsoftware (123 Twitter followers)
- **LinkedIn® Page:** https://www.linkedin.com/company/cloudsoftwaregroup/ (9,677 employees on LinkedIn®)

**Reviewer Demographics:**
  - **Company Size:** 47% Enterprise, 35% Small-Business


#### Pros & Cons

**Pros:**

- Decision Making (1 reviews)
- Ease of Use (1 reviews)
- Efficiency (1 reviews)
- Real-time Analytics (1 reviews)
- Real-time Data (1 reviews)

**Cons:**

- Complexity (1 reviews)
- Expensive (1 reviews)
- Poor Guidance (1 reviews)
- Setup Difficulties (1 reviews)

  ### 24. [InfinyOn Cloud](https://www.g2.com/products/infinyon-cloud/reviews)
  InfinyOn, a real-time data streaming company, has architected a programmable platform for data in motion that is built on Rust and enables continuous intelligence for connected apps. SmartModules enable enterprises to intelligently program their data pipelines as the data flows between producers and consumers in real-time. With Fluvio OSS or InfinyOn Cloud, enterprises can quickly correlate events, apply business intelligence, and derive value as they occur. Our mission is to accelerate the world's transition to the real-time economy.


  **Average Rating:** 4.8/5.0
  **Total Reviews:** 15

**User Satisfaction Scores:**

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


**Seller Details:**

- **Seller:** [InfinyOn](https://www.g2.com/sellers/infinyon)
- **Year Founded:** 2019
- **HQ Location:** Santa Clara, US
- **Twitter:** @infinyon (418 Twitter followers)
- **LinkedIn® Page:** https://www.linkedin.com/company/infinyon/ (10 employees on LinkedIn®)

**Reviewer Demographics:**
  - **Top Industries:** Information Technology and Services
  - **Company Size:** 73% Small-Business, 20% Mid-Market


  ### 25. [Akka](https://www.g2.com/products/akka/reviews)
  Akka is a platform to build and run apps that are elastic, agile, and resilient. Industry titans and disruptors rely on Akka when application responsiveness must be guaranteed. Engineering teams use a simple SDK and powerful libraries to build transactional, durable, and real-time services that distribute logic and data together. Operations are fully automated in serverless and BYOC environments, and a self-hosted option is available.


  **Average Rating:** 4.2/5.0
  **Total Reviews:** 23


**Seller Details:**

- **Seller:** [akka.io](https://www.g2.com/sellers/akka-io)
- **Year Founded:** 2011
- **HQ Location:** San Francisco, US
- **Twitter:** @akka_io_ (26,297 Twitter followers)
- **LinkedIn® Page:** https://www.linkedin.com/company/akka-io/ (75 employees on LinkedIn®)

**Reviewer Demographics:**
  - **Who Uses This:** Software Engineer
  - **Top Industries:** Computer Software
  - **Company Size:** 40% Small-Business, 30% Mid-Market




## Parent Category

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



## Related Categories

- [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)



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## Buyer Guide

### 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.