Best Big Data Processing And Distribution Systems - Page 3

How Many Big Data Processing And Distribution Systems Products Does G2 Track?

Total Products under this Category: 126

Category Stats (Sep 2026)

  • Average Rating: 4.4/5 (↑0.01 vs Aug 2026) The average rating of products in this category, based on all submitted ratings
  • Top Trending Product: Cloudera (+2.21%) - Among all products in this category, Cloudera recorded the largest rating increase compared to last month

Last updated: September 05, 2026

How Does G2 Rank Big Data Processing And Distribution Systems Products?

Why You Can Trust G2's Software Rankings:

  • 30 Analysts and Data Experts
  • 9,500+ Authentic Reviews
  • 126+ 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.

G2 Grid® for Big Data Processing And Distribution Systems

G2 Grid® for Big Data Processing And Distribution Systems plotting products by satisfaction and market presence

Highlighted products: Databricks, Google Cloud BigQuery, IBM watsonx.data, Snowflake, Apache Spark for Azure HDInsight, Amazon EMR, AWS Lake Formation, and Microsoft SQL Server.

Underlying data: [Grid® JSON](https://www.g2.com/categories/big-data-processing-and-distribution/grids.json?focus%5B%5D=databricks&focus%5B%5D=google-cloud-bigquery&focus%5B%5D=ibm-watsonx-data&focus%5B%5D=snowflake&focus%5B%5D=apache-spark-for-azure-hdinsight&focus%5B%5D=amazon-emr&focus%5B%5D=aws-lake-formation&focus%5B%5D=microsoft-sql-server)

Qubole

Qubole is the open data lake company that provides a simple and secure data lake platform for machine learning, streaming, and ad-hoc analytics. No other platform provides the openness and data workload flexibility of Qubole while radically accelerating data lake adoption, reducing time to value, and lowering cloud data lake costs by 50 percent. Qubole’s Platform provides end-to-end data lake services such as cloud infrastructure management, data management, continuous data engineering, analytics, and machine learning with near-zero administration. Qubole is trusted by leading brands such as Expedia, Disney, Oracle, Gannett and Adobe to spur innovation and to transform their businesses for the era of big data. For more information, visit us at www.qubole.com.

Average Rating: 4.0/5.0

Total Reviews: 237

How Do G2 Users Rate Qubole?

  • Has the product been a good partner in doing business?: 8.1/10 (Category avg: 8.8/10)
  • Real-Time Data Collection: 8.0/10 (Category avg: 8.8/10)
  • Machine Scaling: 8.3/10 (Category avg: 8.6/10)
  • Data Preparation: 8.3/10 (Category avg: 8.6/10)

Who Is the Company Behind Qubole?

  • Seller: Qubole
  • Year Founded: 2011
  • HQ Location: Santa Clara, CA
  • Twitter: @qubole
    9,425 Twitter followers
  • LinkedIn® Page: www.linkedin.com
    23 employees on LinkedIn®

Who Uses This Product?

  • Who Uses This: Software Engineer, Data Scientist
  • Top Industries: Computer Software, Information Technology and Services
  • Company Size: 51% Large, 44% Medium

What Are Recent G2 Reviews of Qubole?

What Are G2 Users Discussing About Qubole?

Hadoop HDFS

The Hadoop Distributed File System (HDFS) is a scalable and fault-tolerant file system designed to manage large datasets across clusters of commodity hardware. As a core component of the Apache Hadoop ecosystem, HDFS enables efficient storage and retrieval of vast amounts of data, making it ideal for big data applications. Key Features and Functionality: - Fault Tolerance: HDFS replicates data blocks across multiple nodes, ensuring data availability and resilience against hardware failures. - High Throughput: Optimized for streaming data access, HDFS provides high aggregate data bandwidth, facilitating rapid data processing. - Scalability: Capable of scaling horizontally by adding more nodes, HDFS can accommodate petabytes of data, supporting the growth of data-intensive applications. - Data Locality: By processing data on the nodes where it is stored, HDFS minimizes network congestion and enhances processing speed. - Portability: Designed to be compatible across various hardware and operating systems, HDFS offers flexibility in deployment environments. Primary Value and Problem Solved: HDFS addresses the challenges of storing and processing massive datasets by providing a reliable, scalable, and cost-effective solution. Its architecture ensures data integrity and availability, even in the face of hardware failures, while its design allows for efficient data processing by leveraging data locality. This makes HDFS particularly valuable for organizations dealing with big data, enabling them to derive insights and value from their data assets effectively.

Average Rating: 4.4/5.0

Total Reviews: 130

How Do G2 Users Rate Hadoop HDFS?

  • Has the product been a good partner in doing business?: 7.7/10 (Category avg: 8.8/10)
  • Real-Time Data Collection: 8.6/10 (Category avg: 8.8/10)
  • Machine Scaling: 8.3/10 (Category avg: 8.6/10)
  • Data Preparation: 8.4/10 (Category avg: 8.6/10)

Who Is the Company Behind Hadoop HDFS?

Who Uses This Product?

  • Who Uses This: Software Engineer, Data Engineer
  • Top Industries: Computer Software, Information Technology and Services
  • Company Size: 55% Large, 23% Medium

What Do G2 Reviewers Say About Hadoop HDFS?

AI-generated summary from verified user reviews

Pros
  • Users value HDFS for its effective data processing and reliability in handling large files across multiple machines.
  • Users value the data security of HDFS, ensuring reliable storage for large files across multiple machines.
  • Users appreciate the reliable data storage of Hadoop HDFS, excelling in managing large files with fault tolerance.
  • Users value the ability to store large datasets efficiently, ensuring reliable fault tolerance and stability with HDFS.
Cons
  • Users face increased costs due to hardware needs, maintenance, and the complexity of managing HDFS clusters effectively.
  • Users face significant maintenance issues with HDFS, requiring dedicated teams to manage upgrades and ensure smooth operation.
  • Users experience significant performance issues with HDFS, especially when managing scaling and numerous small files.
  • Users find HDFS suffers from poor performance, struggling with scalability and small file handling in modern environments.
  • Users find security issues prevalent in HDFS, necessitating dedicated teams for maintenance and upgrades to ensure stability.

What Are Recent G2 Reviews of Hadoop HDFS?

What Are G2 Users Discussing About Hadoop HDFS?

Apache Apex

Apache Apex is an enterprise grade native YARN big data-in-motion platform designed to unify stream processing as well as batch processing.

Average Rating: 4.4/5.0

Total Reviews: 15

How Do G2 Users Rate Apache Apex?

  • Has the product been a good partner in doing business?: 8.8/10 (Category avg: 8.8/10)
  • Real-Time Data Collection: 9.3/10 (Category avg: 8.8/10)
  • Machine Scaling: 8.8/10 (Category avg: 8.6/10)
  • Data Preparation: 8.7/10 (Category avg: 8.6/10)

Who Is the Company Behind Apache Apex?

Who Uses This Product?

  • Top Industries: Information Technology and Services
  • Company Size: 33% Medium, 33% Large

What Are Recent G2 Reviews of Apache Apex?

What Are G2 Users Discussing About Apache Apex?

Apache Chukwa

Apache Chukwa is an open source data collection system for monitoring large distributed systems.

Average Rating: 4.2/5.0

Total Reviews: 10

How Do G2 Users Rate Apache Chukwa?

  • Has the product been a good partner in doing business?: 6.7/10 (Category avg: 8.8/10)
  • Real-Time Data Collection: 7.6/10 (Category avg: 8.8/10)
  • Machine Scaling: 7.4/10 (Category avg: 8.6/10)
  • Data Preparation: 8.3/10 (Category avg: 8.6/10)

Who Is the Company Behind Apache Chukwa?

Who Uses This Product?

  • Company Size: 70% Medium, 30% Small

What Are Recent G2 Reviews of Apache Chukwa?

What Are G2 Users Discussing About Apache Chukwa?

SQL Buddy

Web based mysql client

Average Rating: 4.2/5.0

Total Reviews: 11

How Do G2 Users Rate SQL Buddy?

  • Has the product been a good partner in doing business?: 9.4/10 (Category avg: 8.8/10)

Who Is the Company Behind SQL Buddy?

  • Seller: WinSCP
  • Year Founded: 2000
  • HQ Location: Praha, CZ
  • Twitter: @winscpnet
    1,760 Twitter followers
  • LinkedIn® Page: www.linkedin.com
    3 employees on LinkedIn®

Who Uses This Product?

  • Company Size: 55% Small, 36% Large

What Are Recent G2 Reviews of SQL Buddy?

What Are G2 Users Discussing About SQL Buddy?

Druid

Apache Druid is an open source real-time analytics database. Druid combines ideas from OLAP/analytic databases, timeseries databases, and search systems to create a complete real-time analytics solution for real-time data. It includes stream and batch ingestion, column-oriented storage, time-optimized partitioning, native OLAP and search indexing, SQL and REST support, flexible schemas; all with true horizontal scalability on a shared nothing, cloud native architecture that makes it easy to deploy, monitor and manage at scale. It is downloadable for free for unlimited use from druid.apache.org and also hosted in the cloud by Imply Data.

Average Rating: 4.3/5.0

Total Reviews: 28

How Do G2 Users Rate Druid?

  • Has the product been a good partner in doing business?: 7.7/10 (Category avg: 8.8/10)
  • Real-Time Data Collection: 8.5/10 (Category avg: 8.8/10)
  • Machine Scaling: 8.5/10 (Category avg: 8.6/10)
  • Data Preparation: 8.7/10 (Category avg: 8.6/10)

Who Is the Company Behind Druid?

  • Seller: Druid
  • Year Founded: 1998
  • HQ Location: Rio de Janeiro, Rio de Janeiro
  • Twitter: @druid
    4 Twitter followers
  • LinkedIn® Page: www.linkedin.com
    89 employees on LinkedIn®

Who Uses This Product?

  • Top Industries: Computer Software
  • Company Size: 52% Large, 29% Medium

What Are Recent G2 Reviews of Druid?

What Are G2 Users Discussing About Druid?

GridGain

GridGain® is an in-memory computing platform solution designed to help organizations manage and process large volumes of data in real-time. Built on the robust Apache® Ignite™ framework, GridGain enables businesses to accelerate their applications, enhance data processing speeds, and scale efficiently to meet the demands of modern digital enterprises. This platform is particularly well-suited for scenarios where rapid data access and processing are critical, such as in financial services, e-commerce, telecommunications, and IoT applications. The target audience for GridGain includes IT professionals, data engineers, and business analysts who require high-performance computing capabilities to support their data-intensive applications. Organizations facing challenges related to data latency, scalability, and the need for real-time analytics will find GridGain to be a valuable solution. By leveraging in-memory computing, users can significantly reduce the time it takes to retrieve and analyze data, enabling them to make faster, data-driven decisions. Key features of the GridGain platform include distributed in-memory storage, advanced data processing capabilities, and seamless integration with existing data sources and applications. The platform supports SQL queries, key-value access, and various data processing frameworks, allowing users to work with data in the format that best suits their needs. Additionally, GridGain provides built-in support for machine learning and streaming analytics, empowering organizations to harness the full potential of their data in real-time. One of the primary benefits of using GridGain is its ability to enhance application performance by reducing latency and increasing throughput. By storing data in-memory rather than on traditional disk storage, GridGain enables faster data access and processing, which is crucial for applications that require immediate insights. Furthermore, the platform's scalability allows organizations to expand their computing resources as needed, ensuring that they can handle growing data volumes without compromising performance. GridGain stands out in the in-memory computing market due to its robust architecture, flexibility, and comprehensive support for various data processing needs. With a proven track record of success among major clients and numerous industry awards, GridGain continues to lead the way in addressing the challenges of Fast Data and helping organizations unlock the full potential of their data assets.

Average Rating: 4.6/5.0

Total Reviews: 15

How Do G2 Users Rate GridGain?

  • Has the product been a good partner in doing business?: 9.7/10 (Category avg: 8.8/10)
  • Real-Time Data Collection: 9.2/10 (Category avg: 8.8/10)
  • Machine Scaling: 9.4/10 (Category avg: 8.6/10)
  • Data Preparation: 7.9/10 (Category avg: 8.6/10)

Who Is the Company Behind GridGain?

  • Seller: GridGain Systems, Inc.
  • Year Founded: 2007
  • HQ Location: Foster City, California
  • Twitter: @gridgain
    5,510 Twitter followers
  • LinkedIn® Page: www.linkedin.com
    86 employees on LinkedIn®

Who Uses This Product?

  • Top Industries: Information Technology and Services
  • Company Size: 73% Small, 20% Medium

What Do G2 Reviewers Say About GridGain?

AI-generated summary from verified user reviews

Pros
  • Users commend GridGain for its fast communication, enabling real-time data access and significantly enhancing application performance.
  • Users admire the real-time analytics of GridGain, enabling rapid data access and transformative performance enhancements.
  • Users value the real-time processing of GridGain, enhancing speed and efficiency in handling large-scale data tasks.
  • Users admire the robust scalability of GridGain, enhancing performance for real-time, large-scale data processing.
  • Users find GridGain to have exceptional ease of use, simplifying application management and enhancing data accessibility dramatically.
Cons
  • Users face a steep learning curve with GridGain, requiring substantial technical expertise and clearer documentation for ease of use.
  • Users experience a steep learning curve with GridGain, finding its complexity challenging for newcomers to distributed systems.
  • Users find the complex implementation of GridGain challenging due to its steep learning curve and technical expertise requirements.
  • Users find the difficult setup of GridGain to be a significant barrier, especially for those new to distributed systems.
  • Users find GridGain to be expensive, especially with many advanced features locked behind paywalls.

What Are Recent G2 Reviews of GridGain?

Apache Beam

Apache Beam is an open source unified programming model designed to define and execute data processing pipelines, including ETL, batch and stream processing.

Average Rating: 4.1/5.0

Total Reviews: 14

How Do G2 Users Rate Apache Beam?

  • Has the product been a good partner in doing business?: 7.1/10 (Category avg: 8.8/10)
  • Real-Time Data Collection: 7.7/10 (Category avg: 8.8/10)
  • Machine Scaling: 8.3/10 (Category avg: 8.6/10)
  • Data Preparation: 8.1/10 (Category avg: 8.6/10)

Who Is the Company Behind Apache Beam?

Who Uses This Product?

  • Company Size: 44% Medium, 38% Small

What Are Recent G2 Reviews of Apache Beam?

Tinybird

Tinybird is a fully managed ClickHouse® service designed for software developers and AI-native product teams by enabling them to create large-scale real-time analytics projects with minimal effort. Tinybird makes integrating the open source ClickHouse database into applications simpler, faster, and more reliable, allowing engineers to focus on feature development rather than infrastructure management. Tinybird eliminates the complexities associated with traditional database management, making it an ideal choice for teams looking to leverage the power of ClickHouse without the overhead of server maintenance and scaling concerns. The target audience for Tinybird includes software developers, data engineers, technical founders, and AI-native product teams building real-time analytics capabilities in their applications. With the increasing demand for real-time data processing, Tinybird caters to teams that need to deliver insights quickly and efficiently. Use cases for Tinybird span various industries, including SaaS, e-commerce, finance, crypto, AI, and IoT, where real-time data analysis is crucial for decision-making and operational efficiency. By providing a managed service, Tinybird allows software engineers to deploy analytics features in days rather than months, significantly accelerating project timelines. Key features of Tinybird include a hosted ClickHouse database plus managed data ingestion and API layers, which simplify the process of integrating analytics into applications. The built-in authentication tools enhance security and data privacy, with support for row-level access policies using JWTs. Free observability logs storage and querying allow users to keep tabs on usage and performance. AI-native features, including Tinybird Code - a CLI agent with deep ClickHouse expertise - plus the Tinybird MCP Server, make integrating analytics features into LLM apps simpler and more robust. Additionally, Tinybird's architecture is designed to handle scaling automatically, allowing teams to focus on their core development tasks without worrying about understanding a new database or worrying about infrastructure details. For those who desire infrastructure control, Tinybird offers self-managed deployment, for free. This unique combination of features enables users to ship data-driven features rapidly while maintaining high performance and reliability. Tinybird stands out in the real-time analytics database landscape by providing the performance of one of the world's fastest OLAP databases without the associated complexity. By abstracting the technical challenges of managing clusters and provisioning resources, Tinybird empowers teams to innovate and iterate on their products more quickly. The service's emphasis on ease of use and rapid deployment makes it an attractive option for organizations looking to harness the power of real-time analytics without the burden of extensive operational overhead. With Tinybird, users can unlock the potential of their data and drive impactful insights, all while enjoying a seamless and efficient development experience.

Average Rating: 4.1/5.0

Total Reviews: 14

How Do G2 Users Rate Tinybird?

  • Has the product been a good partner in doing business?: 10.0/10 (Category avg: 8.8/10)
  • Real-Time Data Collection: 10.0/10 (Category avg: 8.8/10)
  • Machine Scaling: 9.4/10 (Category avg: 8.6/10)
  • Data Preparation: 9.4/10 (Category avg: 8.6/10)

Who Is the Company Behind Tinybird?

  • Seller: Tinybird
  • Year Founded: 2019
  • HQ Location: New York, US
  • LinkedIn® Page: www.linkedin.com
    52 employees on LinkedIn®

Who Uses This Product?

  • Top Industries: Computer Software
  • Company Size: 50% Medium, 36% Small

What Do G2 Reviewers Say About Tinybird?

AI-generated summary from verified user reviews

Pros
  • Users find Tinybird to be incredibly easy to use, enabling seamless integration and efficient data analytics development.
  • Users value the ease of integration and real-time analytics offered by Tinybird, enhancing their data experience.
  • Users love the easy integrations of Tinybird, enabling seamless connections and fast development of real-time analytics.
  • Users appreciate Tinybird's ease of integration and exploration, making data analytics simple and efficient for developers.
  • Users value the easy integrations with apps like Confluent Cloud for streamlined real-time analytics and development.
Cons
  • Users report poor customer support, highlighting slow response times and insufficient documentation for new users.
  • Users note a lack of features in Tinybird, limiting integrations and hindering data flow and scalability.
  • Users experience a steep learning curve with Tinybird, making navigation and feature utilization challenging for newcomers.
  • Users experience a learning difficulty with Tinybird, facing challenges in navigation and utilizing its features effectively.
  • Users face limited customization with Tinybird, which restricts adaptability and complicates integration with other platforms.

What Are Recent G2 Reviews of Tinybird?

What Are G2 Users Discussing About Tinybird?

Apache Storm

Apache Storm is a free and open source distributed realtime computation system. Storm makes it easy to reliably process unbounded streams of data, doing for realtime processing what Hadoop did for batch processing.

Average Rating: 3.7/5.0

Total Reviews: 12

How Do G2 Users Rate Apache Storm?

  • Has the product been a good partner in doing business?: 8.0/10 (Category avg: 8.8/10)
  • Real-Time Data Collection: 6.7/10 (Category avg: 8.8/10)
  • Machine Scaling: 8.3/10 (Category avg: 8.6/10)
  • Data Preparation: 8.3/10 (Category avg: 8.6/10)

Who Is the Company Behind Apache Storm?

Who Uses This Product?

  • Company Size: 58% Small, 33% Large

What Are Recent G2 Reviews of Apache Storm?

Prophecy

Prophecy is the agentic data prep and analysis platform that introduces a new data lifecycle—generate, refine, deploy—where AI agents and data teams collaborate through visual, code, and document interfaces to accelerate work and deliver trusted pipelines to production. Leading enterprises rely on Prophecy to power their most demanding data workloads. - Generate a first draft in minutes: Prophecy’s AI agents, built on specialized Claude Code, are experts at generating workflows for your data, accelerating tasks like data transformation and automating others like documentation. - Refine with ease and speed: Our visual analytics workflows (or code, document formats) enable users to quickly understand the AI generated output, and to refine them to 100% complete. Deploy robustly: We provide robust deployment to production built on software best practices. The deployed workflows run at scale, with governance, on your cloud data platform. What are the key features of Prophecy? - Market Leading Data Agents: Specialized Claude Code based AI agents that understand your data and apply data specific skills to generate the best results. - Visual Inspect & Refine: AI generates results as visual data workflows, so business users can quickly inspect the logic, refine it to match their intent, and validate the final output. - Integrated Data Execution: You schedule and monitor workflows. Each reads/writes data using built-in high-performance connectors, and run transforms in Prophecy or your SQL or Spark platforms. - Complete Data Lifecycle: The visual workflows can be deployed to production as high-performance code that runs at scale with governance on Databricks, Snowflake or BigQuery that can be shared. Prophecy finds application across industries such as finance, healthcare, and retail, where data-driven decisions are crucial. Analysts become more productive, and business users now self-serve. Learn more at https://www.prophecy.ai/

Average Rating: 4.6/5.0

Total Reviews: 31

How Do G2 Users Rate Prophecy?

  • Has the product been a good partner in doing business?: 9.3/10 (Category avg: 8.8/10)
  • Real-Time Data Collection: 10.0/10 (Category avg: 8.8/10)
  • Machine Scaling: 9.5/10 (Category avg: 8.6/10)
  • Data Preparation: 9.8/10 (Category avg: 8.6/10)

Who Is the Company Behind Prophecy?

  • Seller: Prophecy
  • Year Founded: 2017
  • HQ Location: Palo Alto, CA
  • Twitter: @Prophecy_io
    370 Twitter followers
  • LinkedIn® Page: www.linkedin.com
    173 employees on LinkedIn®

Who Uses This Product?

  • Who Uses This: Senior Data Engineer
  • Top Industries: Financial Services, Insurance
  • Company Size: 68% Large, 19% Medium

What Do G2 Reviewers Say About Prophecy?

AI-generated summary from verified user reviews

Pros
  • Users find Prophecy's ease of use appealing, thanks to its elegant UI and flexible, low-code features.
  • Users value the high-quality code generation of Prophecy, enhancing productivity and simplifying data pipeline design.
  • Users value the exceptional customer support from Prophecy, appreciating timely assistance and knowledgeable staff for technical issues.
  • Users commend Prophecy for its powerful data pipeline features, enhancing productivity and simplifying complex ETL processes.
  • Users benefit from the automation in Prophecy, simplifying pipeline design and enhancing collaboration throughout the process.
Cons
  • Users note feature limitations, including missing complex extensions and a slow interface that hinder overall usability.
  • Users find the learning curve steep, requiring time to master Prophecy's interface and best practices for optimized pipelines.
  • Users express concerns over missing features in Prophecy, highlighting the need for better customization and data source support.
  • Users note a steep learning curve with Prophecy, requiring time to master best practices for optimized pipelines.
  • Users find the difficulty in identifying root causes and understanding syntax a barrier to effectively using Prophecy.

What Are Recent G2 Reviews of Prophecy?

HVR

HVR is a real-time data replication solution designed to move large volumes of data FAST and efficiently in hybrid environments for real-time analytics. With HVR, discover the benefits of using log-based change data capture for replicating data from common DBMS such as SQL Server, Oracle, SAP Hana, and more to sources such as AWS, Azure, Teradata and more.

Average Rating: 4.2/5.0

Total Reviews: 13

How Do G2 Users Rate HVR?

  • Has the product been a good partner in doing business?: 9.8/10 (Category avg: 8.8/10)
  • Real-Time Data Collection: 9.3/10 (Category avg: 8.8/10)
  • Machine Scaling: 8.3/10 (Category avg: 8.6/10)
  • Data Preparation: 7.8/10 (Category avg: 8.6/10)

Who Is the Company Behind HVR?

  • Seller: Fivetran
  • Year Founded: 2012
  • HQ Location: Oakland, CA
  • Twitter: @fivetran
    5,767 Twitter followers
  • LinkedIn® Page: www.linkedin.com
    1,902 employees on LinkedIn®

Who Uses This Product?

  • Company Size: 77% Large, 15% Medium

What Are Recent G2 Reviews of HVR?

What Are G2 Users Discussing About HVR?

Hazelcast Platform

Hazelcast Platform is the Live Data Platform that delivers data at the speed of relevance, providing the in‑memory foundation for applications that act on data the instant it's created—ensuring businesses never miss a moment of opportunity. By converging distributed caching, compute, stream processing, and real‑time AI into one low‑latency runtime, Hazelcast delivers sub‑millisecond performance, linear scalability, and enterprise resilience. Global 2000 firms trust Hazelcast to simplify architectures, reduce costs, and power mission‑critical, time‑sensitive applications.

Average Rating: 4.3/5.0

Total Reviews: 12

How Do G2 Users Rate Hazelcast Platform?

  • Has the product been a good partner in doing business?: 8.3/10 (Category avg: 8.8/10)
  • Real-Time Data Collection: 8.3/10 (Category avg: 8.8/10)
  • Machine Scaling: 10.0/10 (Category avg: 8.6/10)
  • Data Preparation: 10.0/10 (Category avg: 8.6/10)

Who Is the Company Behind Hazelcast Platform?

  • Seller: Hazelcast
  • Year Founded: 2010
  • HQ Location: Palo Alto, US
  • Twitter: @hazelcast
    9,354 Twitter followers
  • LinkedIn® Page: www.linkedin.com
    148 employees on LinkedIn®

Who Uses This Product?

  • Company Size: 54% Small, 23% Large

What Do G2 Reviewers Say About Hazelcast Platform?

AI-generated summary from verified user reviews

Pros
  • Users appreciate the ease of use of Hazelcast Platform, noting its speed and minimal memory requirements.
  • Users appreciate the fast processing of Hazelcast Platform, noting its efficiency in resolving distributed systems challenges.
  • Users appreciate the flexibility of Hazelcast Platform, finding it fast and efficient for distributed systems challenges.
  • Users appreciate the fast performance of Hazelcast Platform, effectively solving issues in distributed systems with minimal memory usage.
  • Users appreciate the fast performance and low memory usage of Hazelcast Platform, which simplifies distributed system management.
Cons
  • Users find the learning curve to be steep, requiring extra time to navigate and understand the platform effectively.
  • Users note the navigation difficulty in Hazelcast Platform, requiring extra time to find features effectively.
  • Users find Hazelcast Platform not user-friendly, requiring extra time to navigate and locate features efficiently.
  • Users find the poor UI of Hazelcast Platform makes navigation and coordination frustrating and time-consuming.
  • Users find the time-consuming nature of locating and coordinating resources in Hazelcast to be a drawback.

What Are Recent G2 Reviews of Hazelcast Platform?

What Are G2 Users Discussing About Hazelcast Platform?

Decodable

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

How Do G2 Users Rate Decodable?

  • Has the product been a good partner in doing business?: 10.0/10 (Category avg: 8.8/10)
  • Real-Time Data Collection: 8.3/10 (Category avg: 8.8/10)
  • Machine Scaling: 8.9/10 (Category avg: 8.6/10)
  • Data Preparation: 6.7/10 (Category avg: 8.6/10)

Who Is the Company Behind Decodable?

  • Seller: Decodable
  • Year Founded: 2021
  • HQ Location: San Francisco, US
  • Twitter: @Decodableco
    2,639 Twitter followers
  • LinkedIn® Page: www.linkedin.com
    6 employees on LinkedIn®

Who Uses This Product?

  • Company Size: 44% Small, 38% Medium

What Do G2 Reviewers Say About Decodable?

AI-generated summary from verified user reviews

Pros
  • Users value the automation capabilities of Decodable, enabling quick migration and seamless real-time data processing.
  • Users find Decodable to be a very easy to use platform, streamlining pipeline migration and testing effortlessly.
  • Users value the easy setup of Decodable, enabling quick workflow migrations with minimal adjustments needed.
  • Users appreciate the ease of use and quick assembly of Decodable, enhancing their real-time data management experience.
  • Users find Decodable's implementation ease impressive, enabling quick pipeline migration with minimal adjustments needed.
Cons
  • Users find the FAQ poorly organized, often requiring support contact, though responses are prompt and helpful.
  • Users experience performance issues with Decodable, noting slow processing speeds even for small tasks.
  • Users find the poorly organized FAQ requires contacting support, although responses are quick and helpful.
  • Users report poor performance with Decodable, processing only 1 to 2 records per second on streams.
  • Users find the resource intensive learning in Decodable limits efficiency, processing only 1 to 2 records per second.

What Are Recent G2 Reviews of Decodable?

GeoSpock DB

GeoSpock enables data fusion for the connected world with GeoSpock DB – the space-time analytics database. GeoSpock DB is a unique, cloud-native database optimised for querying for real-world use cases, able to fuse multiple sources of Internet of Things (IoT) data together to unlock its full value, whilst simultaneously reducing complexity and cost. GeoSpock DB enables efficient storage, data fusion, and rapid programmatic access to data, and allows you to run ANSI SQL queries and connect to standard analytics tools via flexible JDBC/ODBC connectors. Users are able to perform deep analysis and share insights using familiar toolsets, with plug and play support for common BI tools (such as Tableau™, Amazon QuickSight™, and Microsoft Power BI™), and Data Science and Machine Learning environments (including Python Notebooks and Apache Spark). The database can also be integrated with proprietary applications, web services, and internal tools – with compatibility for open-source and customisable visualisation libraries such as Kepler and Cesium.js.

Average Rating: 4.0/5.0

Total Reviews: 10

How Do G2 Users Rate GeoSpock DB?

  • Real-Time Data Collection: 7.5/10 (Category avg: 8.8/10)
  • Machine Scaling: 8.3/10 (Category avg: 8.6/10)
  • Data Preparation: 8.3/10 (Category avg: 8.6/10)

Who Is the Company Behind GeoSpock DB?

  • Seller: GeoSpock
  • Year Founded: 2013
  • HQ Location: Cambridge, GB
  • Twitter: @GeoSpock
    953 Twitter followers
  • LinkedIn® Page: www.linkedin.com
    2 employees on LinkedIn®

Who Uses This Product?

  • Company Size: 70% Large, 20% Medium

What Are Recent G2 Reviews of GeoSpock DB?

What Are G2 Users Discussing About GeoSpock DB?

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