Best Event Stream Processing Software

How Many Event Stream Processing Software Products Does G2 Track?

Total Products under this Category: 75

Category Stats (Oct 2026)

  • Average Rating: 4.37/5 The average rating of products in this category, based on all submitted ratings

Last updated: October 01, 2026

How Does G2 Rank Event Stream Processing Software Products?

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G2 Grid® for Event Stream Processing Software

G2 Grid® for Event Stream Processing Software plotting products by satisfaction and market presence

Highlighted products: Aiven for Apache Kafka, Redpanda Streaming, Amazon Managed Streaming for Apache Kafka (Amazon MSK), Confluent, Amazon Kinesis Data Streams, Google Cloud Dataflow, IBM Event Streams, and Apache Kafka.

Underlying data: [Grid® JSON](https://www.g2.com/categories/event-stream-processing/grids.json?focus%5B%5D=aiven-for-apache-kafka&focus%5B%5D=redpanda-streaming&focus%5B%5D=amazon-managed-streaming-for-apache-kafka-amazon-msk&focus%5B%5D=confluent&focus%5B%5D=aws-amazon-kinesis-data-streams&focus%5B%5D=google-cloud-dataflow&focus%5B%5D=ibm-event-streams&focus%5B%5D=apache-kafka)

Aiven for Apache Kafka

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: 239

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: 8.3/10 (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
  • Year Founded: 2016
  • HQ Location: Helsinki, Southern Finland
  • Twitter: @aiven_io
    4,104 Twitter followers
  • LinkedIn® Page: www.linkedin.com
    476 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% Medium, 29% Small

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, allowing them to focus on data streaming without hassle.
  • Users value the ease of use of Aiven for Apache Kafka, enjoying a straightforward setup and minimal training requirements.
  • Users appreciate the smooth scaling of Aiven for Apache Kafka, enhancing their workflow without infrastructure worries.
  • Users value the management ease of Aiven for Apache Kafka, facilitating quick deployment and self-management of clusters.
  • Users appreciate the high reliability of Aiven for Apache Kafka, enjoying ease of use and dependable support.
Cons
  • Users note that the pricing increases quickly as usage scales, making it expensive for larger deployments.
  • Users express frustration with poor documentation, which complicates advanced configurations and slows down their workflow.
  • Users find some advanced configuration options limited, hindering teams needing extensive customization and control over their setup.
  • Users find Aiven for Apache Kafka to have significant operational complexity, requiring extensive management that can overwhelm smaller teams.
  • Users find Aiven for Apache Kafka not user-friendly, citing unintuitive configurations and minor UI glitches affecting usability.

What Are Recent G2 Reviews of Aiven for Apache Kafka?

What Are G2 Users Discussing About Aiven for Apache Kafka?

Redpanda Streaming

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: 4.7/5.0

Total Reviews: 53

How Do G2 Users Rate Redpanda Streaming?

  • Has the product been a good partner in doing business?: 9.6/10 (Category avg: 8.9/10)
  • Data Sources: 9.8/10 (Category avg: 8.6/10)
  • Data Processing: 9.9/10 (Category avg: 8.8/10)
  • Real-Time Processing: 9.6/10 (Category avg: 9.1/10)

Who Is the Company Behind Redpanda Streaming?

  • Seller: Redpanda Data
  • Company Website:
  • Year Founded: 2019
  • HQ Location: San Francisco, US
  • Twitter: @redpandadata
    5,337 Twitter followers
  • LinkedIn® Page: www.linkedin.com
    211 employees on LinkedIn®

Who Uses This Product?

  • Top Industries: Computer Software, Financial Services
  • Company Size: 64% Medium, 21% Small

What Do G2 Reviewers Say About Redpanda Streaming?

AI-generated summary from verified user reviews

Pros
  • Users highlight the exceptional customer support of Redpanda, finding the team responsive and easy to work with.
  • Users find Redpanda Streaming to be easy to use, facilitating quick setups and seamless integration with other services.
  • Users praise the performance of Redpanda Streaming, highlighting its speed and reliability in enhancing their infrastructure.
  • Users highlight the fast performance of Redpanda Streaming, enhancing development speed and system reliability significantly.
  • Users rave about the reliability and ease of use of Redpanda Streaming, enhancing productivity and support throughout development.
Cons
  • Users find the complexity of the web interface limits their experience, requiring CLI for advanced tasks.
  • Users point out data management issues, struggling with setup complexity and incomplete documentation affecting usability.
  • Users find the missing features in Redpanda Streaming complicate setup and integration, impeding a smoother experience.
  • Users often face poor documentation that complicates setup and integration, requiring guesswork for feature utilization.
  • Users find the poor UI design challenging, often needing to rely on the CLI for complex tasks.

What Are Recent G2 Reviews of Redpanda Streaming?

Amazon Managed Streaming for Apache Kafka (Amazon MSK)

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: 23

How Do G2 Users Rate Amazon Managed Streaming for Apache Kafka (Amazon MSK)?

  • Has the product been a good partner in doing business?: 8.1/10 (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: 8.9/10 (Category avg: 9.1/10)

Who Is the Company Behind Amazon Managed Streaming for Apache Kafka (Amazon MSK)?

  • Seller: Amazon Web Services (AWS)
  • Year Founded: 2006
  • HQ Location: Seattle, WA
  • Twitter: @awscloud
    2,232,483 Twitter followers
  • LinkedIn® Page: www.linkedin.com
    147,094 employees on LinkedIn®
  • Ownership: NASDAQ: AMZN

Who Uses This Product?

  • Top Industries: Computer Software
  • Company Size: 46% Small, 33% Medium

What Do G2 Reviewers Say About Amazon Managed Streaming for Apache Kafka (Amazon MSK)?

AI-generated summary from verified user reviews

Pros
  • Users love how Amazon MSK provides seamless cloud management for Kafka, simplifying scaling and maintenance tasks effortlessly.
  • Users value the maintenance ease of Amazon MSK, which simplifies managing Kafka in a seamless AWS environment.
  • Users appreciate the management ease of Amazon MSK, eliminating the complexities of handling Kafka operations.
  • Users value the reliability of Amazon MSK, appreciating its seamless management of scaling and maintenance.
  • Users appreciate the seamless scalability of Amazon MSK, effectively easing Kafka management and integration with AWS.
Cons
  • Users find the cost prohibitive, especially for smaller workloads or early-stage projects, impacting overall value.
  • Users notice the high cost for smaller workloads and feel it's less flexible than self-managed Kafka.
  • Users find limited control in Amazon MSK, especially regarding cost and flexibility for smaller projects.

What Are Recent G2 Reviews of Amazon Managed Streaming for Apache Kafka (Amazon MSK)?

What Are G2 Users Discussing About Amazon Managed Streaming for Apache Kafka (Amazon MSK)?

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Confluent

Today’s customers expect every digital experience to be immediate, connected, and personalized. That takes more than data at rest - it takes trusted data in motion. Confluent is the complete Data Streaming Platform for keeping data in motion from the moment business change occurs through processing, governance, and serving. Built by the original creators of Apache Kafka®, Confluent connects applications, services, and systems; processes streams in real time with Apache Flink®; and serves trusted, always-current data wherever it is needed across cloud, hybrid, and self-managed environments. With deployment options including fully managed Confluent Cloud, self-managed Confluent Platform and Brint-your-own-cloud Confluent WarpStream, teams can power event-driven applications, real-time analytics, AI, and operational workflows while choosing the operating model that fits their environment and turning live data into better customer experiences and business outcomes.

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: 8.7/10 (Category avg: 8.8/10)
  • Real-Time Processing: 9.0/10 (Category avg: 9.1/10)

Who Is the Company Behind Confluent?

  • Seller: IBM
  • Company Website:
  • Year Founded: 1911
  • HQ Location: Armonk, New York, United States
  • Twitter: @IBMSecurity
    74,660 Twitter followers
  • LinkedIn® Page: www.linkedin.com
    344,328 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: 36% Large, 33% Small

What Do G2 Reviewers Say About Confluent?

AI-generated summary from verified user reviews

Pros
  • Users appreciate the simplicity and scalability of Confluent's managed cloud services, enhancing real-time data integration.
  • Users appreciate the effortless integration of Confluent's cloud services, enhancing their experience with Kafka and Flink.
  • Users appreciate the wide range of connectors in Confluent, enhancing real-time data integration effortlessly.
  • Users appreciate the effortless data integration offered by Confluent, enhancing real-time processing with robust tools and scalability.
  • Users appreciate the ease of use of Confluent, enjoying simplified data integration and a user-friendly interface.
Cons
  • Users note the high cost estimation with data growth and a steep learning curve for effective use.
  • Users find Confluent expensive as costs rise with data volume, and learning the system can be time-consuming.
  • Users face initial difficulties with a steep learning curve and costly pricing as data volumes increase.
  • Users find a lack of features in Confluent, especially in lower tiers, leading to increased costs and complexity.
  • Users face a steep learning curve with Confluent, requiring significant time to master its workflow and features.

What Are Recent G2 Reviews of Confluent?

What Are G2 Users Discussing About Confluent?

Amazon Kinesis Data Streams

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

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)
  • Year Founded: 2006
  • HQ Location: Seattle, WA
  • Twitter: @awscloud
    2,232,483 Twitter followers
  • LinkedIn® Page: www.linkedin.com
    147,094 employees on LinkedIn®
  • Ownership: NASDAQ: AMZN

Who Uses This Product?

  • Who Uses This: Software Engineer
  • Top Industries: Computer Software, Information Technology and Services
  • Company Size: 38% Large, 37% Medium

What Do G2 Reviewers Say About Amazon Kinesis Data Streams?

AI-generated summary from verified user reviews

Pros
  • Users value the real-time data processing capabilities of Amazon Kinesis Data Streams for efficient and scalable analytics.
  • Users value the real-time data processing capability of Amazon Kinesis Data Streams for its reliability and seamless integration.
  • Users appreciate the real-time data processing capability of Amazon Kinesis Data Streams, ensuring low-latency and reliable performance.
  • Users appreciate the real-time data processing capability of Amazon Kinesis Data Streams, highlighting its stability and seamless integration.
  • Users value the seamless API integration of Amazon Kinesis Data Streams with other AWS services, enhancing convenience and efficiency.
Cons
  • Users find the difficult setup of Amazon Kinesis Data Streams challenging, particularly for newcomers and complex configurations.
  • Users find Amazon Kinesis Data Streams expensive as costs can escalate quickly without proper management and monitoring.
  • Users find the resource-intensive learning curve challenging, especially for beginners and when managing costs effectively.
  • Users find the complexity of setup and cost management challenging, especially for newcomers to streaming architectures.
  • Users find the complexity of configuration across AWS data services a challenge when using Kinesis Data Streams.

What Are Recent G2 Reviews of Amazon Kinesis Data Streams?

What Are G2 Users Discussing About Amazon Kinesis Data Streams?

Google Cloud Dataflow

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: 42

How Do G2 Users Rate Google Cloud Dataflow?

  • 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)

Who Is the Company Behind Google Cloud Dataflow?

  • Seller: Google
  • Year Founded: 1998
  • HQ Location: Mountain View, CA
  • Twitter: @google
    31,899,995 Twitter followers
  • LinkedIn® Page: www.linkedin.com
    301,144 employees on LinkedIn®
  • Ownership: NASDAQ:GOOG

Who Uses This Product?

  • Top Industries: Computer Software
  • Company Size: 39% Small, 34% Medium

What Do G2 Reviewers Say About Google Cloud Dataflow?

AI-generated summary from verified user reviews

Pros
  • Users appreciate the ease of use and efficiency in processing streaming events with Google Cloud Dataflow.
  • Users find Google Cloud Dataflow's ease of use invaluable for efficiently building and monitoring streaming pipelines.
  • Users appreciate the easy management of Google Cloud Dataflow, facilitating seamless integration and efficient streaming pipeline processing.
  • Users appreciate the ease of use and integration of Google Cloud Dataflow for processing streaming events efficiently.
  • Users value the ease of use for processing streaming events with Google Cloud Dataflow, facilitating efficient pipeline building.
Cons
  • Users find Google Cloud Dataflow to be costly compared to alternatives, impacting their decision-making process.
  • Users find Google Cloud Dataflow to be expensive compared to alternatives like Apache Flink, impacting their decision.
  • Users find the installation difficult with challenges like implementing watermarks compared to other solutions.
  • Users find learning difficulty in implementing Google Cloud Dataflow, especially with complex features like watermarks.

What Are Recent G2 Reviews of Google Cloud Dataflow?

What Are G2 Users Discussing About Google Cloud Dataflow?

Apache Kafka

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?

Who Uses This Product?

  • Who Uses This: Software Engineer, Senior Software Engineer
  • Top Industries: Computer Software, Information Technology and Services
  • Company Size: 47% Large, 33% Medium

What Do G2 Reviewers Say About Apache Kafka?

AI-generated summary from verified user reviews

Pros
  • Users value the high scalability of Apache Kafka, which excels in managing growing data volumes efficiently.
  • Users praise the high scalability and performance of Apache Kafka, making it perfect for enterprise data growth.
  • Users value the high scalability and performance of Apache Kafka, making it perfect for growing enterprise data needs.
  • Users praise real-time data processing in Apache Kafka for its speed, reliability, and scalability across systems.
  • Users commend the reliability of Apache Kafka, praising its durability, fault tolerance, and scalability for data processing.
Cons
  • Users struggle with operational complexity and high resource consumption, finding Kafka's message queuing features limited.
  • Users feel that data management issues in Apache Kafka require extensive expertise, which can overwhelm smaller teams.
  • Users find debugging issues in Apache Kafka challenging, requiring significant effort and effective tools for resolution.
  • Users find the difficult learning curve of Apache Kafka overwhelming for smaller teams, requiring dedicated expertise for management.
  • Users find limited customization challenging, especially with complex setups and manual management of brokers and zookeepers.

What Are Recent G2 Reviews of Apache Kafka?

What Are G2 Users Discussing About Apache Kafka?

IBM Event Streams

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

How Do G2 Users Rate IBM Event Streams?

  • 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)

Who Is the Company Behind IBM Event Streams?

  • Seller: IBM
  • Year Founded: 1911
  • HQ Location: Armonk, New York, United States
  • Twitter: @IBMSecurity
    74,660 Twitter followers
  • LinkedIn® Page: www.linkedin.com
    344,328 employees on LinkedIn®
  • Ownership: SWX:IBM

Who Uses This Product?

  • Company Size: 54% Large, 23% Medium

What Do G2 Reviewers Say About IBM Event Streams?

AI-generated summary from verified user reviews

Pros
  • Users find the user-friendly UI of IBM Event Streams simplifies Kafka's complexities, enabling quick delivery of solutions.
  • Users appreciate the user-friendly interface of IBM Event Streams, simplifying Kafka complexities for efficient event-driven solutions.

What Are Recent G2 Reviews of IBM Event Streams?

IBM StreamSets

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: 113

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
  • Year Founded: 1911
  • HQ Location: Armonk, New York, United States
  • Twitter: @IBMSecurity
    74,660 Twitter followers
  • LinkedIn® Page: www.linkedin.com
    344,328 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: 43% Large, 34% Medium

What Do G2 Reviewers Say About IBM StreamSets?

AI-generated summary from verified user reviews

Pros
  • Users find IBM StreamSets to offer ease of use with its intuitive interface and beginner-friendly pipeline creation.
  • Users appreciate the user-friendly drag-and-drop interface of IBM StreamSets, enhancing pipeline visualization and debugging efficiency.
  • Users love the effective data management capabilities of IBM StreamSets, simplifying pipeline creation and monitoring across environments.
  • Users appreciate the simplicity of data integration workflows in IBM StreamSets, enjoying its intuitive visual pipeline design.
  • Users appreciate the wide range of integrations in IBM StreamSets, enhancing real-time data handling and simplifying workflows.
Cons
  • Users struggle with the steep learning curve of IBM StreamSets, highlighting the need for deeper technical knowledge and better guidance.
  • Users find the cost of IBM StreamSets to be a concern, especially for smaller teams with limited budgets.
  • Users find the learning difficulty of advanced features in StreamSets challenging, impacting onboarding and overall experience.
  • Users experience slow performance with IBM StreamSets, particularly when managing large data volumes or complex configurations.
  • Users struggle with the steep learning curve of IBM StreamSets, requiring deep technical knowledge to use advanced features.

What Are Recent G2 Reviews of IBM StreamSets?

What Are G2 Users Discussing About IBM StreamSets?

Amazon Kinesis Data Firehose

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: 21

How Do G2 Users Rate Amazon Kinesis Data Firehose?

  • 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)

Who Is the Company Behind Amazon Kinesis Data Firehose?

  • Seller: Amazon Web Services (AWS)
  • Year Founded: 2006
  • HQ Location: Seattle, WA
  • Twitter: @awscloud
    2,232,483 Twitter followers
  • LinkedIn® Page: www.linkedin.com
    147,094 employees on LinkedIn®
  • Ownership: NASDAQ: AMZN

Who Uses This Product?

  • Top Industries: Information Technology and Services
  • Company Size: 44% Medium, 36% Large

What Are Recent G2 Reviews of Amazon Kinesis Data Firehose?

RudderStack

RudderStack’s agentic CDP enables you to collect, unify, and activate customer data from an integrated platform that wraps around your data warehouse as the system of record. Our infrastructure is battle tested with proven reliability at peak loads up to 1M events/second and 99.95% uptime. Proactive governance tools enable you to enforce data quality and compliance in pipeline, so downstream systems always get activation ready data. And our AI capabilities transform both how you work with customer data and what you can do with it. With RudderStack, your whole business can trust and use customer data. Data teams ship faster, business teams self-serve rich customer context, and agents consistently deliver powerful, privacy safe 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

How Do G2 Users Rate RudderStack?

  • 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)

Who Is the Company Behind RudderStack?

  • Seller: RudderStack
  • Company Website:
  • Year Founded: 2019
  • HQ Location: San Francisco, California
  • Twitter: @RudderStack
    1,695 Twitter followers
  • LinkedIn® Page: www.linkedin.com
    126 employees on LinkedIn®

Who Uses This Product?

  • Who Uses This: Data Engineer
  • Top Industries: Computer Software, Information Technology and Services
  • Company Size: 54% Medium, 46% Small

What Do G2 Reviewers Say About RudderStack?

AI-generated summary from verified user reviews

Pros
  • Users appreciate the ease of use of RudderStack, enabling quick setup and smooth data integration effortlessly.
  • Users appreciate the excellent customer support from RudderStack, highlighting their helpfulness and partnership in projects.
  • Users commend the easy integration capabilities of RudderStack, enabling seamless connection to various data tools.
  • Users rave about the easy setup of RudderStack, highlighting quick implementation and a user-friendly interface.
  • Users appreciate the easy integrations of RudderStack, facilitating quick connections and seamless data management.
Cons
  • Users find the learning curve steep, citing confusion with the interface and schema inconsistencies during setup.
  • Users find the limited customization options restrictive, impacting functionality and overall satisfaction with RudderStack.
  • Users find the complexity of the setup in RudderStack challenging, especially those with less technical experience.
  • Users feel there is a lack of adequate guidance with RudderStack, impacting troubleshooting and integration understanding.
  • Users find onboarding difficult due to complex setups and inadequate documentation, requiring support for issues.

What Are Recent G2 Reviews of RudderStack?

Amazon Kinesis Data Analytics

Amazon Kinesis Data Analytics is the easiest way to transform and analyze streaming data in real time with Apache Flink. Kinesis Data Analytics reduces the complexity of building, managing, and integrating Apache Flink applications with other AWS services. Kinesis Data Analytics takes care of everything required to run streaming applications continuously, and scales automatically to match the volume and throughput of your incoming data. With Kinesis Data Analytics, there are no servers to manage, no minimum fee or setup cost, and you only pay for the resources your streaming applications consume.

Average Rating: 4.1/5.0

Total Reviews: 14

How Do G2 Users Rate Amazon Kinesis Data Analytics?

  • Has the product been a good partner in doing business?: 7.5/10 (Category avg: 8.9/10)
  • Data Sources: 9.2/10 (Category avg: 8.6/10)
  • Data Processing: 9.2/10 (Category avg: 8.8/10)
  • Real-Time Processing: 10.0/10 (Category avg: 9.1/10)

Who Is the Company Behind Amazon Kinesis Data Analytics?

  • Seller: Amazon Web Services (AWS)
  • Year Founded: 2006
  • HQ Location: Seattle, WA
  • Twitter: @awscloud
    2,232,483 Twitter followers
  • LinkedIn® Page: www.linkedin.com
    147,094 employees on LinkedIn®
  • Ownership: NASDAQ: AMZN

Who Uses This Product?

  • Company Size: 67% Large, 27% Small

What Do G2 Reviewers Say About Amazon Kinesis Data Analytics?

AI-generated summary from verified user reviews

Pros
  • Users appreciate the scalable and flexible analytics solutions of Amazon Kinesis, benefiting from real-time data analysis.
  • Users appreciate the scalable and flexible solutions of AWS Analytics for efficient data analysis and integration.
  • Users appreciate the cost-efficient pay-as-you-go model of Amazon Kinesis Data Analytics, making data analysis affordable and accessible.
  • Users appreciate the seamless integration of Amazon Kinesis Data Analytics, which simplifies workflows across AWS services.
  • Users value the seamless integration with other AWS services, enhancing their data analysis workflows significantly.
Cons
  • Users face complexity in tool selection and setup, making it challenging for newcomers to effectively utilize the service.
  • Users face complexity issues with tool selection, setup, and steep learning curves, impacting their overall experience.
  • Users face complex setup challenges in AWS Analytics, leading to a steep learning curve and cost management difficulties.
  • Users face challenges with cost management, requiring careful monitoring and navigating complexities in tool selection and setup.
  • Users face a steep learning curve with Amazon Kinesis Data Analytics, making setup and tool selection challenging for newcomers.

What Are Recent G2 Reviews of Amazon Kinesis Data Analytics?

Informatica Data Integration and Engineering

Cloud Data Integration (CDI) is a comprehensive, AI-powered ETL and ELT solution designed to easily move, transform, and synchronize data between various sources and target systems across any cloud, anywhere, at scale. Built on a modern technology stack, CDI offers easy, efficient and cost-effective data ingestion, transformation, synchronization, and replication for a multi-cloud and serverless world for everyone and everywhere. It covers diverse integration patterns, ensuring you have well-architected and seamlessly automated data pipelines for all your advanced analytics and AI needs.

Average Rating: 4.3/5.0

Total Reviews: 309

How Do G2 Users Rate Informatica Data Integration and Engineering?

  • Has the product been a good partner in doing business?: 8.4/10 (Category avg: 8.9/10)
  • Data Sources: 8.3/10 (Category avg: 8.6/10)
  • Data Processing: 8.8/10 (Category avg: 8.8/10)
  • Real-Time Processing: 7.5/10 (Category avg: 9.1/10)

Who Is the Company Behind Informatica Data Integration and Engineering?

  • Seller: Informatica
  • Company Website:
  • Year Founded: 1993
  • HQ Location: Redwood City, CA
  • Twitter: @Informatica
    99,643 Twitter followers
  • LinkedIn® Page: www.linkedin.com
    2,473 employees on LinkedIn®

Who Uses This Product?

  • Who Uses This: Data Engineer, Data Analyst
  • Top Industries: Information Technology and Services, Computer Software
  • Company Size: 57% Large, 28% Medium

What Do G2 Reviewers Say About Informatica Data Integration and Engineering?

AI-generated summary from verified user reviews

Pros
  • Users find Informatica Data Integration's ease of use remarkable, favoring its intuitive interface and drag-and-drop functionality.
  • Users value the efficiency of Informatica Data Integration, enabling reliable and scalable ETL processes seamlessly.
  • Users value the ease of use and extensive connectivity of Informatica Cloud Data Integration for efficient ETL processes.
  • Users value the time-saving capabilities of Informatica Data Integration, benefiting from efficient cloud access and automation.
  • Users appreciate the automation features of Informatica Data Integration, enhancing efficiency in data workflows and scheduling.
Cons
  • Users find the complexity of setup and configuration challenging, particularly for beginners navigating the platform.
  • Users find the complex usability of Informatica Data Integration challenging, especially during setup and performance optimization.
  • Users find that debugging can be difficult, as it often requires significant effort and expertise to manage effectively.
  • Users find the difficult setup process challenging, especially for newcomers to the Informatica platform.
  • Users find the error messages frustrating and lacking documentation, complicating their experience with the tool.

What Are Recent G2 Reviews of Informatica Data Integration and Engineering?

What Are G2 Users Discussing About Informatica Data Integration and Engineering?

PubNub

PubNub is a real-time platform for developers who build in-app chat and live features. The Chat SDK includes typing indicators, presence, message history, read receipts, reactions, and threads. PubNub supports unlimited subscribers per channel. PubNub assigns each message a server-side timetoken. Messages on a channel form one ordered sequence. End-to-end delivery latency is sub-100ms. DAZN uses PubNub to power chat and Watch Party experiences for 10 million users. PubNub charges by Monthly Active Users or transactions, depending on the plan. PubNub does not bill per connection or per IP address. PubNub does not count peak concurrent connections. You can start free, with no credit card. PubNub is a HIPAA-compliant real-time network with ISO/IEC 27001 certification and SOC 2 Type II compliance. We guarantee up to 99.999% availability. For more information, contact Sales. Start with the Chat SDK docs: https://www.pubnub.com/docs/chat/overview

Average Rating: 4.4/5.0

Total Reviews: 22

How Do G2 Users Rate PubNub?

  • 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: 8.1/10 (Category avg: 8.8/10)
  • Real-Time Processing: 8.1/10 (Category avg: 9.1/10)

Who Is the Company Behind PubNub?

  • Seller: PubNub
  • Company Website:
  • Year Founded: 2010
  • HQ Location: San Francisco, California
  • Twitter: @PubNub
    17,872 Twitter followers
  • LinkedIn® Page: www.linkedin.com
    122 employees on LinkedIn®

Who Uses This Product?

  • Top Industries: Computer Software, Information Technology and Services
  • Company Size: 50% Small, 33% Large

What Do G2 Reviewers Say About PubNub?

AI-generated summary from verified user reviews

Pros
  • Users value the secure chat functionality of PubNub, enabling seamless and interactive communication with file sharing.
  • Users highlight the responsive customer support of PubNub, making installation and troubleshooting seamless and efficient.
  • Users value the easy API integration of PubNub, enabling seamless real-time applications across various platforms.
  • Users value the reliable API quality of PubNub, making real-time application development straightforward and efficient.
  • Users commend PubNub for its robust data security, enhancing secure communication and real-time interactions across platforms.
Cons
  • Users find the short notice for changes from PubNub frustrating and request better communication practices.
  • Users find the 30-day notice for data deletion too short, impacting trust and requiring better communication.
  • Users express concerns about insufficient advance notice on data management changes, impacting their planning and data retention strategies.
  • Users face difficult navigation in documentation, leading to coding delays and queries that hinder efficiency.
  • Users caution that the cost of PubNub can escalate quickly, impacting those on a tight budget.

What Are Recent G2 Reviews of PubNub?

IBM Cloud Pak for Integration

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: 40

How Do G2 Users Rate IBM Cloud Pak for Integration?

  • Has the product been a good partner in doing business?: 7.5/10 (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)

Who Is the Company Behind IBM Cloud Pak for Integration?

  • Seller: IBM
  • Year Founded: 1911
  • HQ Location: Armonk, New York, United States
  • Twitter: @IBMSecurity
    74,660 Twitter followers
  • LinkedIn® Page: www.linkedin.com
    344,328 employees on LinkedIn®
  • Ownership: SWX:IBM

Who Uses This Product?

  • Top Industries: Information Technology and Services, Computer Software
  • Company Size: 35% Large, 35% Medium

What Are Recent G2 Reviews of IBM Cloud Pak for Integration?

What Are G2 Users Discussing About IBM Cloud Pak for Integration?

Bijou Barry
BB
Researched and written by Bijou Barry
Updated October 3, 2024

Event Stream Processing Topics

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Learn More 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.

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.