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Best Enterprise Big Data Processing And Distribution Systems

Blue Bowen
BB
Researched and written by Blue Bowen

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

In addition to qualifying for inclusion in the Big Data Processing And Distribution Systems category, to qualify for inclusion in the Enterprise Business Big Data Processing And Distribution Systems category, a product must have at least 10 reviews left by a reviewer from an enterprise business.

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G2 takes pride in showing unbiased reviews on user satisfaction in our ratings and reports. We do not allow paid placements in any of our ratings, rankings, or reports. Learn about our scoring methodologies.

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24 Listings in Enterprise Big Data Processing And Distribution Systems Available

(1,201)4.5 out of 5
2nd Easiest To Use in Big Data Processing and Distribution software
View top Consulting Services for Google Cloud BigQuery
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Entry Level Price:Free
  • Overview
    Expand/Collapse Overview
  • Product Description
    How are these determined?Information
    This description is provided by the seller.

    BigQuery is a fully managed, AI-ready data analytics platform that helps you maximize value from your data and is designed to be multi-engine, multi-format, and multi-cloud. Store 10 GiB of data and

    Users
    • Data Engineer
    • Data Analyst
    Industries
    • Information Technology and Services
    • Computer Software
    Market Segment
    • 37% Enterprise
    • 36% Mid-Market
  • Pros and Cons
    Expand/Collapse Pros and Cons
  • Google Cloud BigQuery Pros and Cons
    How are these determined?Information
    Pros and Cons are compiled from review feedback and grouped into themes to provide an easy-to-understand summary of user reviews.
    Pros
    Ease of Use
    169
    Speed
    139
    Fast Querying
    120
    Integrations
    119
    Query Efficiency
    116
    Cons
    Expensive
    126
    Query Issues
    77
    Cost Issues
    58
    Cost Management
    58
    Learning Curve
    54
  • User Satisfaction
    Expand/Collapse User Satisfaction
  • Google Cloud BigQuery features and usability ratings that predict user satisfaction
    8.7
    Has the product been a good partner in doing business?
    Average: 8.7
    8.8
    Real-Time Data Collection
    Average: 8.7
    8.9
    Machine Scaling
    Average: 8.6
    8.9
    Data Preparation
    Average: 8.6
  • Seller Details
    Expand/Collapse Seller Details
  • Seller Details
    Seller
    Google
    Company Website
    Year Founded
    1998
    HQ Location
    Mountain View, CA
    Twitter
    @google
    31,497,057 Twitter followers
    LinkedIn® Page
    www.linkedin.com
    325,307 employees on LinkedIn®
Product Description
How are these determined?Information
This description is provided by the seller.

BigQuery is a fully managed, AI-ready data analytics platform that helps you maximize value from your data and is designed to be multi-engine, multi-format, and multi-cloud. Store 10 GiB of data and

Users
  • Data Engineer
  • Data Analyst
Industries
  • Information Technology and Services
  • Computer Software
Market Segment
  • 37% Enterprise
  • 36% Mid-Market
Google Cloud BigQuery Pros and Cons
How are these determined?Information
Pros and Cons are compiled from review feedback and grouped into themes to provide an easy-to-understand summary of user reviews.
Pros
Ease of Use
169
Speed
139
Fast Querying
120
Integrations
119
Query Efficiency
116
Cons
Expensive
126
Query Issues
77
Cost Issues
58
Cost Management
58
Learning Curve
54
Google Cloud BigQuery features and usability ratings that predict user satisfaction
8.7
Has the product been a good partner in doing business?
Average: 8.7
8.8
Real-Time Data Collection
Average: 8.7
8.9
Machine Scaling
Average: 8.6
8.9
Data Preparation
Average: 8.6
Seller Details
Seller
Google
Company Website
Year Founded
1998
HQ Location
Mountain View, CA
Twitter
@google
31,497,057 Twitter followers
LinkedIn® Page
www.linkedin.com
325,307 employees on LinkedIn®
(633)4.6 out of 5
Optimized for quick response
1st Easiest To Use in Big Data Processing and Distribution software
View top Consulting Services for Databricks Data Intelligence Platform
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  • Overview
    Expand/Collapse Overview
  • Product Description
    How are these determined?Information
    This description is provided by the seller.

    Databricks is the Data and AI company. More than 20,000 organizations worldwide — including Block, Comcast, Condé Nast, Rivian, Shell and over 60% of the Fortune 500 — rely on the Databricks Data Inte

    Users
    • Data Engineer
    • Data Scientist
    Industries
    • Information Technology and Services
    • Financial Services
    Market Segment
    • 46% Enterprise
    • 37% Mid-Market
    User Sentiment
    How are these determined?Information
    These insights, currently in beta, are compiled from user reviews and grouped to display a high-level overview of the software.
    • Databricks Data Intelligence Platform is a unified analytics platform that combines data engineering, analytics, governance, and machine learning capabilities for efficient data processing and management.
    • Users frequently mention the platform's seamless integration of various data tasks, its collaborative environment, and its ability to handle large-scale data efficiently, making it a powerful tool for data-driven teams.
    • Reviewers experienced a steep learning curve, especially for those unfamiliar with Spark or distributed computing, and found the cost structure to be potentially expensive for continuous workloads.
  • Pros and Cons
    Expand/Collapse Pros and Cons
  • Databricks Data Intelligence Platform Pros and Cons
    How are these determined?Information
    Pros and Cons are compiled from review feedback and grouped into themes to provide an easy-to-understand summary of user reviews.
    Pros
    Features
    266
    Ease of Use
    256
    Integrations
    178
    Collaboration
    142
    Easy Integrations
    139
    Cons
    Learning Curve
    101
    Steep Learning Curve
    88
    Expensive
    87
    Missing Features
    62
    UX Improvement
    58
  • User Satisfaction
    Expand/Collapse User Satisfaction
  • Databricks Data Intelligence Platform features and usability ratings that predict user satisfaction
    8.8
    Has the product been a good partner in doing business?
    Average: 8.7
    8.7
    Real-Time Data Collection
    Average: 8.7
    9.0
    Machine Scaling
    Average: 8.6
    8.8
    Data Preparation
    Average: 8.6
  • Seller Details
    Expand/Collapse Seller Details
  • Seller Details
    Company Website
    Year Founded
    1999
    HQ Location
    San Francisco, CA
    Twitter
    @databricks
    84,124 Twitter followers
    LinkedIn® Page
    www.linkedin.com
    13,680 employees on LinkedIn®
Product Description
How are these determined?Information
This description is provided by the seller.

Databricks is the Data and AI company. More than 20,000 organizations worldwide — including Block, Comcast, Condé Nast, Rivian, Shell and over 60% of the Fortune 500 — rely on the Databricks Data Inte

Users
  • Data Engineer
  • Data Scientist
Industries
  • Information Technology and Services
  • Financial Services
Market Segment
  • 46% Enterprise
  • 37% Mid-Market
User Sentiment
How are these determined?Information
These insights, currently in beta, are compiled from user reviews and grouped to display a high-level overview of the software.
  • Databricks Data Intelligence Platform is a unified analytics platform that combines data engineering, analytics, governance, and machine learning capabilities for efficient data processing and management.
  • Users frequently mention the platform's seamless integration of various data tasks, its collaborative environment, and its ability to handle large-scale data efficiently, making it a powerful tool for data-driven teams.
  • Reviewers experienced a steep learning curve, especially for those unfamiliar with Spark or distributed computing, and found the cost structure to be potentially expensive for continuous workloads.
Databricks Data Intelligence Platform Pros and Cons
How are these determined?Information
Pros and Cons are compiled from review feedback and grouped into themes to provide an easy-to-understand summary of user reviews.
Pros
Features
266
Ease of Use
256
Integrations
178
Collaboration
142
Easy Integrations
139
Cons
Learning Curve
101
Steep Learning Curve
88
Expensive
87
Missing Features
62
UX Improvement
58
Databricks Data Intelligence Platform features and usability ratings that predict user satisfaction
8.8
Has the product been a good partner in doing business?
Average: 8.7
8.7
Real-Time Data Collection
Average: 8.7
9.0
Machine Scaling
Average: 8.6
8.8
Data Preparation
Average: 8.6
Seller Details
Company Website
Year Founded
1999
HQ Location
San Francisco, CA
Twitter
@databricks
84,124 Twitter followers
LinkedIn® Page
www.linkedin.com
13,680 employees on LinkedIn®

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(665)4.6 out of 5
Optimized for quick response
3rd Easiest To Use in Big Data Processing and Distribution software
View top Consulting Services for Snowflake
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Entry Level Price:$2 Compute/Hour
  • Overview
    Expand/Collapse Overview
  • Product Description
    How are these determined?Information
    This description is provided by the seller.

    Snowflake makes enterprise AI easy, efficient and trusted. Thousands of companies around the globe, including hundreds of the world’s largest, use Snowflake’s AI Data Cloud to share data, build applic

    Users
    • Data Engineer
    • Data Analyst
    Industries
    • Information Technology and Services
    • Computer Software
    Market Segment
    • 45% Enterprise
    • 43% Mid-Market
  • Pros and Cons
    Expand/Collapse Pros and Cons
  • Snowflake Pros and Cons
    How are these determined?Information
    Pros and Cons are compiled from review feedback and grouped into themes to provide an easy-to-understand summary of user reviews.
    Pros
    Ease of Use
    85
    Features
    65
    Data Management
    62
    Integrations
    57
    Scalability
    54
    Cons
    Expensive
    46
    Cost
    26
    Cost Management
    23
    Learning Curve
    22
    Feature Limitations
    20
  • User Satisfaction
    Expand/Collapse User Satisfaction
  • Snowflake features and usability ratings that predict user satisfaction
    9.0
    Has the product been a good partner in doing business?
    Average: 8.7
    8.9
    Real-Time Data Collection
    Average: 8.7
    9.1
    Machine Scaling
    Average: 8.6
    9.0
    Data Preparation
    Average: 8.6
  • Seller Details
    Expand/Collapse Seller Details
  • Seller Details
    Company Website
    Year Founded
    2012
    HQ Location
    San Mateo, CA
    Twitter
    @SnowflakeDB
    158 Twitter followers
    LinkedIn® Page
    www.linkedin.com
    10,207 employees on LinkedIn®
Product Description
How are these determined?Information
This description is provided by the seller.

Snowflake makes enterprise AI easy, efficient and trusted. Thousands of companies around the globe, including hundreds of the world’s largest, use Snowflake’s AI Data Cloud to share data, build applic

Users
  • Data Engineer
  • Data Analyst
Industries
  • Information Technology and Services
  • Computer Software
Market Segment
  • 45% Enterprise
  • 43% Mid-Market
Snowflake Pros and Cons
How are these determined?Information
Pros and Cons are compiled from review feedback and grouped into themes to provide an easy-to-understand summary of user reviews.
Pros
Ease of Use
85
Features
65
Data Management
62
Integrations
57
Scalability
54
Cons
Expensive
46
Cost
26
Cost Management
23
Learning Curve
22
Feature Limitations
20
Snowflake features and usability ratings that predict user satisfaction
9.0
Has the product been a good partner in doing business?
Average: 8.7
8.9
Real-Time Data Collection
Average: 8.7
9.1
Machine Scaling
Average: 8.6
9.0
Data Preparation
Average: 8.6
Seller Details
Company Website
Year Founded
2012
HQ Location
San Mateo, CA
Twitter
@SnowflakeDB
158 Twitter followers
LinkedIn® Page
www.linkedin.com
10,207 employees on LinkedIn®
(2,252)4.4 out of 5
9th Easiest To Use in Big Data Processing and Distribution software
View top Consulting Services for Microsoft SQL Server
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  • Overview
    Expand/Collapse Overview
  • Product Description
    How are these determined?Information
    This description is provided by the seller.

    SQL Server 2017 brings the power of SQL Server to Windows, Linux and Docker containers for the first time ever, enabling developers to build intelligent applications using their preferred language and

    Users
    • Software Engineer
    • Software Developer
    Industries
    • Information Technology and Services
    • Computer Software
    Market Segment
    • 46% Enterprise
    • 37% Mid-Market
  • Pros and Cons
    Expand/Collapse Pros and Cons
  • Microsoft SQL Server Pros and Cons
    How are these determined?Information
    Pros and Cons are compiled from review feedback and grouped into themes to provide an easy-to-understand summary of user reviews.
    Pros
    Database Management
    28
    Ease of Use
    28
    Performance
    21
    Easy Integrations
    19
    Features
    18
    Cons
    Expensive
    16
    High Licensing Costs
    9
    Performance Issues
    9
    Slow Performance
    9
    Expensive Licensing
    8
  • User Satisfaction
    Expand/Collapse User Satisfaction
  • Microsoft SQL Server features and usability ratings that predict user satisfaction
    8.4
    Has the product been a good partner in doing business?
    Average: 8.7
    8.5
    Real-Time Data Collection
    Average: 8.7
    8.2
    Machine Scaling
    Average: 8.6
    8.5
    Data Preparation
    Average: 8.6
  • Seller Details
    Expand/Collapse Seller Details
  • Seller Details
    Seller
    Microsoft
    Year Founded
    1975
    HQ Location
    Redmond, Washington
    Twitter
    @microsoft
    13,105,074 Twitter followers
    LinkedIn® Page
    www.linkedin.com
    220,934 employees on LinkedIn®
    Ownership
    MSFT
Product Description
How are these determined?Information
This description is provided by the seller.

SQL Server 2017 brings the power of SQL Server to Windows, Linux and Docker containers for the first time ever, enabling developers to build intelligent applications using their preferred language and

Users
  • Software Engineer
  • Software Developer
Industries
  • Information Technology and Services
  • Computer Software
Market Segment
  • 46% Enterprise
  • 37% Mid-Market
Microsoft SQL Server Pros and Cons
How are these determined?Information
Pros and Cons are compiled from review feedback and grouped into themes to provide an easy-to-understand summary of user reviews.
Pros
Database Management
28
Ease of Use
28
Performance
21
Easy Integrations
19
Features
18
Cons
Expensive
16
High Licensing Costs
9
Performance Issues
9
Slow Performance
9
Expensive Licensing
8
Microsoft SQL Server features and usability ratings that predict user satisfaction
8.4
Has the product been a good partner in doing business?
Average: 8.7
8.5
Real-Time Data Collection
Average: 8.7
8.2
Machine Scaling
Average: 8.6
8.5
Data Preparation
Average: 8.6
Seller Details
Seller
Microsoft
Year Founded
1975
HQ Location
Redmond, Washington
Twitter
@microsoft
13,105,074 Twitter followers
LinkedIn® Page
www.linkedin.com
220,934 employees on LinkedIn®
Ownership
MSFT
(93)4.3 out of 5
Optimized for quick response
6th Easiest To Use in Big Data Processing and Distribution software
Save to My Lists
  • Overview
    Expand/Collapse Overview
  • Product Description
    How are these determined?Information
    This description is provided by the seller.

    Manage the entire data for AI lifecycle through a single user experience to power the next generation of Gen-AI applications. IBM watsonx.data empowers organizations to simplify and scale unstructure

    Users
    • Software Engineer
    Industries
    • Information Technology and Services
    • Computer Software
    Market Segment
    • 37% Enterprise
    • 29% Small-Business
  • Pros and Cons
    Expand/Collapse Pros and Cons
  • IBM watsonx.data Pros and Cons
    How are these determined?Information
    Pros and Cons are compiled from review feedback and grouped into themes to provide an easy-to-understand summary of user reviews.
    Pros
    Ease of Use
    47
    Features
    31
    Data Management
    29
    Analytics
    24
    Flexibility
    22
    Cons
    Learning Curve
    29
    Complexity
    18
    Expensive
    18
    Difficulty
    14
    Integration Issues
    14
  • User Satisfaction
    Expand/Collapse User Satisfaction
  • IBM watsonx.data features and usability ratings that predict user satisfaction
    8.0
    Has the product been a good partner in doing business?
    Average: 8.7
    8.6
    Real-Time Data Collection
    Average: 8.7
    8.4
    Machine Scaling
    Average: 8.6
    8.6
    Data Preparation
    Average: 8.6
  • Seller Details
    Expand/Collapse Seller Details
  • Seller Details
    Seller
    IBM
    Company Website
    Year Founded
    1911
    HQ Location
    Armonk, NY
    Twitter
    @IBM
    709,128 Twitter followers
    LinkedIn® Page
    www.linkedin.com
    339,241 employees on LinkedIn®
Product Description
How are these determined?Information
This description is provided by the seller.

Manage the entire data for AI lifecycle through a single user experience to power the next generation of Gen-AI applications. IBM watsonx.data empowers organizations to simplify and scale unstructure

Users
  • Software Engineer
Industries
  • Information Technology and Services
  • Computer Software
Market Segment
  • 37% Enterprise
  • 29% Small-Business
IBM watsonx.data Pros and Cons
How are these determined?Information
Pros and Cons are compiled from review feedback and grouped into themes to provide an easy-to-understand summary of user reviews.
Pros
Ease of Use
47
Features
31
Data Management
29
Analytics
24
Flexibility
22
Cons
Learning Curve
29
Complexity
18
Expensive
18
Difficulty
14
Integration Issues
14
IBM watsonx.data features and usability ratings that predict user satisfaction
8.0
Has the product been a good partner in doing business?
Average: 8.7
8.6
Real-Time Data Collection
Average: 8.7
8.4
Machine Scaling
Average: 8.6
8.6
Data Preparation
Average: 8.6
Seller Details
Seller
IBM
Company Website
Year Founded
1911
HQ Location
Armonk, NY
Twitter
@IBM
709,128 Twitter followers
LinkedIn® Page
www.linkedin.com
339,241 employees on LinkedIn®
(64)4.1 out of 5
12th Easiest To Use in Big Data Processing and Distribution software
View top Consulting Services for Amazon EMR
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  • Overview
    Expand/Collapse Overview
  • Product Description
    How are these determined?Information
    This description is provided by the seller.

    Amazon EMR is a web-based service that simplifies big data processing, providing a managed Hadoop framework that makes it easy, fast, and cost-effective to distribute and process vast amounts of data

    Users
    No information available
    Industries
    • Financial Services
    • Computer Software
    Market Segment
    • 59% Enterprise
    • 22% Small-Business
  • Pros and Cons
    Expand/Collapse Pros and Cons
  • Amazon EMR Pros and Cons
    How are these determined?Information
    Pros and Cons are compiled from review feedback and grouped into themes to provide an easy-to-understand summary of user reviews.
    Pros
    Data Integration
    1
    Large Datasets
    1
    Cons
    Poor Performance
    1
    Slow Performance
    1
  • User Satisfaction
    Expand/Collapse User Satisfaction
  • Amazon EMR features and usability ratings that predict user satisfaction
    8.9
    Has the product been a good partner in doing business?
    Average: 8.7
    8.1
    Real-Time Data Collection
    Average: 8.7
    8.7
    Machine Scaling
    Average: 8.6
    8.7
    Data Preparation
    Average: 8.6
  • Seller Details
    Expand/Collapse Seller Details
  • Seller Details
    Year Founded
    2006
    HQ Location
    Seattle, WA
    Twitter
    @awscloud
    2,217,439 Twitter followers
    LinkedIn® Page
    www.linkedin.com
    143,584 employees on LinkedIn®
    Ownership
    NASDAQ: AMZN
Product Description
How are these determined?Information
This description is provided by the seller.

Amazon EMR is a web-based service that simplifies big data processing, providing a managed Hadoop framework that makes it easy, fast, and cost-effective to distribute and process vast amounts of data

Users
No information available
Industries
  • Financial Services
  • Computer Software
Market Segment
  • 59% Enterprise
  • 22% Small-Business
Amazon EMR Pros and Cons
How are these determined?Information
Pros and Cons are compiled from review feedback and grouped into themes to provide an easy-to-understand summary of user reviews.
Pros
Data Integration
1
Large Datasets
1
Cons
Poor Performance
1
Slow Performance
1
Amazon EMR features and usability ratings that predict user satisfaction
8.9
Has the product been a good partner in doing business?
Average: 8.7
8.1
Real-Time Data Collection
Average: 8.7
8.7
Machine Scaling
Average: 8.6
8.7
Data Preparation
Average: 8.6
Seller Details
Year Founded
2006
HQ Location
Seattle, WA
Twitter
@awscloud
2,217,439 Twitter followers
LinkedIn® Page
www.linkedin.com
143,584 employees on LinkedIn®
Ownership
NASDAQ: AMZN
  • Overview
    Expand/Collapse Overview
  • Product Description
    How are these determined?Information
    This description is provided by the seller.

    Kyvos is a semantic layer for AI and BI. It gives enterprises a single, consistent, business-friendly view of their data for trusted AI and BI — eliminating metric drift across BI tools, and groun

    Users
    • Senior Software Engineer
    • Software Engineer
    Industries
    • Information Technology and Services
    • Computer Software
    Market Segment
    • 51% Mid-Market
    • 44% Enterprise
    User Sentiment
    How are these determined?Information
    These insights, currently in beta, are compiled from user reviews and grouped to display a high-level overview of the software.
    • Kyvos is a data analysis tool that enables users to analyze large datasets, standardize business metrics, and provide secure access to organizational data.
    • Reviewers appreciate Kyvos's ability to handle large volumes of data, its user-friendly interface, and its role-based access controls that ensure data security.
    • Users experienced a steep learning curve with Kyvos, and some minor tweaks were needed in dashboards during the initial rollout.
  • Pros and Cons
    Expand/Collapse Pros and Cons
  • Kyvos Semantic Layer Pros and Cons
    How are these determined?Information
    Pros and Cons are compiled from review feedback and grouped into themes to provide an easy-to-understand summary of user reviews.
    Pros
    Ease of Use
    112
    Speed
    85
    Performance
    48
    Performance Evaluation
    47
    Analytics
    45
    Cons
    Learning Curve
    33
    Difficult Setup
    32
    Complexity
    10
    Feature Limitations
    7
    Learning Difficulty
    7
  • User Satisfaction
    Expand/Collapse User Satisfaction
  • Kyvos Semantic Layer features and usability ratings that predict user satisfaction
    9.7
    Has the product been a good partner in doing business?
    Average: 8.7
    0.0
    No information available
    0.0
    No information available
    0.0
    No information available
  • Seller Details
    Expand/Collapse Seller Details
  • Seller Details
    Company Website
    Year Founded
    2014
    HQ Location
    Los Gatos, CA
    Twitter
    @KyvosInsights
    696 Twitter followers
    LinkedIn® Page
    www.linkedin.com
    134 employees on LinkedIn®
Product Description
How are these determined?Information
This description is provided by the seller.

Kyvos is a semantic layer for AI and BI. It gives enterprises a single, consistent, business-friendly view of their data for trusted AI and BI — eliminating metric drift across BI tools, and groun

Users
  • Senior Software Engineer
  • Software Engineer
Industries
  • Information Technology and Services
  • Computer Software
Market Segment
  • 51% Mid-Market
  • 44% Enterprise
User Sentiment
How are these determined?Information
These insights, currently in beta, are compiled from user reviews and grouped to display a high-level overview of the software.
  • Kyvos is a data analysis tool that enables users to analyze large datasets, standardize business metrics, and provide secure access to organizational data.
  • Reviewers appreciate Kyvos's ability to handle large volumes of data, its user-friendly interface, and its role-based access controls that ensure data security.
  • Users experienced a steep learning curve with Kyvos, and some minor tweaks were needed in dashboards during the initial rollout.
Kyvos Semantic Layer Pros and Cons
How are these determined?Information
Pros and Cons are compiled from review feedback and grouped into themes to provide an easy-to-understand summary of user reviews.
Pros
Ease of Use
112
Speed
85
Performance
48
Performance Evaluation
47
Analytics
45
Cons
Learning Curve
33
Difficult Setup
32
Complexity
10
Feature Limitations
7
Learning Difficulty
7
Kyvos Semantic Layer features and usability ratings that predict user satisfaction
9.7
Has the product been a good partner in doing business?
Average: 8.7
0.0
No information available
0.0
No information available
0.0
No information available
Seller Details
Company Website
Year Founded
2014
HQ Location
Los Gatos, CA
Twitter
@KyvosInsights
696 Twitter followers
LinkedIn® Page
www.linkedin.com
134 employees on LinkedIn®
(39)4.5 out of 5
10th Easiest To Use in Big Data Processing and Distribution software
Save to My Lists
  • Overview
    Expand/Collapse Overview
  • Product Description
    How are these determined?Information
    This description is provided by the seller.

    Azure Data Lake Store is secured, massively scalable, and built to the open HDFS standard, allowing you to run massively-parallel analytics.

    Users
    • Senior Data Engineer
    Industries
    • Information Technology and Services
    Market Segment
    • 46% Enterprise
    • 33% Mid-Market
  • Pros and Cons
    Expand/Collapse Pros and Cons
  • Azure Data Lake Store Pros and Cons
    How are these determined?Information
    Pros and Cons are compiled from review feedback and grouped into themes to provide an easy-to-understand summary of user reviews.
    Pros
    Easy Integrations
    2
    Fast Processing
    2
    Data Integration
    1
    Data Management
    1
    Ease of Use
    1
    Cons
    Difficulty
    1
    Limited Features
    1
    Poor Documentation
    1
  • User Satisfaction
    Expand/Collapse User Satisfaction
  • Azure Data Lake Store features and usability ratings that predict user satisfaction
    8.7
    Has the product been a good partner in doing business?
    Average: 8.7
    9.1
    Real-Time Data Collection
    Average: 8.7
    8.9
    Machine Scaling
    Average: 8.6
    9.1
    Data Preparation
    Average: 8.6
  • Seller Details
    Expand/Collapse Seller Details
  • Seller Details
    Seller
    Microsoft
    Year Founded
    1975
    HQ Location
    Redmond, Washington
    Twitter
    @microsoft
    13,105,074 Twitter followers
    LinkedIn® Page
    www.linkedin.com
    220,934 employees on LinkedIn®
    Ownership
    MSFT
Product Description
How are these determined?Information
This description is provided by the seller.

Azure Data Lake Store is secured, massively scalable, and built to the open HDFS standard, allowing you to run massively-parallel analytics.

Users
  • Senior Data Engineer
Industries
  • Information Technology and Services
Market Segment
  • 46% Enterprise
  • 33% Mid-Market
Azure Data Lake Store Pros and Cons
How are these determined?Information
Pros and Cons are compiled from review feedback and grouped into themes to provide an easy-to-understand summary of user reviews.
Pros
Easy Integrations
2
Fast Processing
2
Data Integration
1
Data Management
1
Ease of Use
1
Cons
Difficulty
1
Limited Features
1
Poor Documentation
1
Azure Data Lake Store features and usability ratings that predict user satisfaction
8.7
Has the product been a good partner in doing business?
Average: 8.7
9.1
Real-Time Data Collection
Average: 8.7
8.9
Machine Scaling
Average: 8.6
9.1
Data Preparation
Average: 8.6
Seller Details
Seller
Microsoft
Year Founded
1975
HQ Location
Redmond, Washington
Twitter
@microsoft
13,105,074 Twitter followers
LinkedIn® Page
www.linkedin.com
220,934 employees on LinkedIn®
Ownership
MSFT
(360)4.3 out of 5
7th Easiest To Use in Big Data Processing and Distribution software
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  • Overview
    Expand/Collapse Overview
  • Product Description
    How are these determined?Information
    This description is provided by the seller.

    At Teradata, we believe that people thrive when empowered with better information. That’s why we built the most complete cloud analytics and data platform for AI. By delivering harmonized data, trust

    Users
    • Data Engineer
    • Software Engineer
    Industries
    • Information Technology and Services
    • Financial Services
    Market Segment
    • 70% Enterprise
    • 21% Mid-Market
    User Sentiment
    How are these determined?Information
    These insights, currently in beta, are compiled from user reviews and grouped to display a high-level overview of the software.
    • Teradata Vantage is a database solution that provides data analysis, SQL queries, and data integration capabilities.
    • Reviewers frequently mention the product's high performance, scalability, and efficient handling of complex SQL and analytic joins, as well as the responsiveness of the support team.
    • Users mentioned issues such as the complexity of the Teradata studio software, the need for cost optimisation, the requirement for specialised skills and training, and the high cost and steep learning curve of the product.
  • Pros and Cons
    Expand/Collapse Pros and Cons
  • Teradata Vantage Pros and Cons
    How are these determined?Information
    Pros and Cons are compiled from review feedback and grouped into themes to provide an easy-to-understand summary of user reviews.
    Pros
    Performance
    19
    Scalability
    16
    Speed
    16
    Analytics
    15
    Large Datasets
    12
    Cons
    Learning Curve
    11
    Complexity
    5
    Integration Issues
    5
    Performance Issues
    5
    Poor UI Design
    5
  • User Satisfaction
    Expand/Collapse User Satisfaction
  • Teradata Vantage features and usability ratings that predict user satisfaction
    8.2
    Has the product been a good partner in doing business?
    Average: 8.7
    7.9
    Real-Time Data Collection
    Average: 8.7
    8.7
    Machine Scaling
    Average: 8.6
    9.0
    Data Preparation
    Average: 8.6
  • Seller Details
    Expand/Collapse Seller Details
  • Seller Details
    Seller
    Teradata
    Company Website
    Year Founded
    1979
    HQ Location
    San Diego, CA
    Twitter
    @Teradata
    93,477 Twitter followers
    LinkedIn® Page
    www.linkedin.com
    9,948 employees on LinkedIn®
Product Description
How are these determined?Information
This description is provided by the seller.

At Teradata, we believe that people thrive when empowered with better information. That’s why we built the most complete cloud analytics and data platform for AI. By delivering harmonized data, trust

Users
  • Data Engineer
  • Software Engineer
Industries
  • Information Technology and Services
  • Financial Services
Market Segment
  • 70% Enterprise
  • 21% Mid-Market
User Sentiment
How are these determined?Information
These insights, currently in beta, are compiled from user reviews and grouped to display a high-level overview of the software.
  • Teradata Vantage is a database solution that provides data analysis, SQL queries, and data integration capabilities.
  • Reviewers frequently mention the product's high performance, scalability, and efficient handling of complex SQL and analytic joins, as well as the responsiveness of the support team.
  • Users mentioned issues such as the complexity of the Teradata studio software, the need for cost optimisation, the requirement for specialised skills and training, and the high cost and steep learning curve of the product.
Teradata Vantage Pros and Cons
How are these determined?Information
Pros and Cons are compiled from review feedback and grouped into themes to provide an easy-to-understand summary of user reviews.
Pros
Performance
19
Scalability
16
Speed
16
Analytics
15
Large Datasets
12
Cons
Learning Curve
11
Complexity
5
Integration Issues
5
Performance Issues
5
Poor UI Design
5
Teradata Vantage features and usability ratings that predict user satisfaction
8.2
Has the product been a good partner in doing business?
Average: 8.7
7.9
Real-Time Data Collection
Average: 8.7
8.7
Machine Scaling
Average: 8.6
9.0
Data Preparation
Average: 8.6
Seller Details
Seller
Teradata
Company Website
Year Founded
1979
HQ Location
San Diego, CA
Twitter
@Teradata
93,477 Twitter followers
LinkedIn® Page
www.linkedin.com
9,948 employees on LinkedIn®
(93)4.4 out of 5
Optimized for quick response
5th Easiest To Use in Big Data Processing and Distribution software
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  • Overview
    Expand/Collapse Overview
  • Product Description
    How are these determined?Information
    This description is provided by the seller.

    Starburst is the data platform for analytics, applications, and AI, unifying data across clouds and on-premises to accelerate AI innovation. Organizations—from startups to Fortune 500 enterprises in 6

    Users
    No information available
    Industries
    • Information Technology and Services
    • Financial Services
    Market Segment
    • 47% Enterprise
    • 31% Small-Business
  • Pros and Cons
    Expand/Collapse Pros and Cons
  • Starburst Pros and Cons
    How are these determined?Information
    Pros and Cons are compiled from review feedback and grouped into themes to provide an easy-to-understand summary of user reviews.
    Pros
    Fast Querying
    24
    Integrations
    22
    Ease of Use
    21
    Query Efficiency
    20
    Large Datasets
    19
    Cons
    Learning Curve
    16
    Query Issues
    14
    Slow Performance
    14
    Difficult Setup
    12
    Complexity
    11
  • User Satisfaction
    Expand/Collapse User Satisfaction
  • Starburst features and usability ratings that predict user satisfaction
    9.0
    Has the product been a good partner in doing business?
    Average: 8.7
    8.0
    Real-Time Data Collection
    Average: 8.7
    8.3
    Machine Scaling
    Average: 8.6
    8.2
    Data Preparation
    Average: 8.6
  • Seller Details
    Expand/Collapse Seller Details
  • Seller Details
    Seller
    Starburst
    Company Website
    Year Founded
    2017
    HQ Location
    Boston, MA
    Twitter
    @starburstdata
    3,466 Twitter followers
    LinkedIn® Page
    www.linkedin.com
    478 employees on LinkedIn®
Product Description
How are these determined?Information
This description is provided by the seller.

Starburst is the data platform for analytics, applications, and AI, unifying data across clouds and on-premises to accelerate AI innovation. Organizations—from startups to Fortune 500 enterprises in 6

Users
No information available
Industries
  • Information Technology and Services
  • Financial Services
Market Segment
  • 47% Enterprise
  • 31% Small-Business
Starburst Pros and Cons
How are these determined?Information
Pros and Cons are compiled from review feedback and grouped into themes to provide an easy-to-understand summary of user reviews.
Pros
Fast Querying
24
Integrations
22
Ease of Use
21
Query Efficiency
20
Large Datasets
19
Cons
Learning Curve
16
Query Issues
14
Slow Performance
14
Difficult Setup
12
Complexity
11
Starburst features and usability ratings that predict user satisfaction
9.0
Has the product been a good partner in doing business?
Average: 8.7
8.0
Real-Time Data Collection
Average: 8.7
8.3
Machine Scaling
Average: 8.6
8.2
Data Preparation
Average: 8.6
Seller Details
Seller
Starburst
Company Website
Year Founded
2017
HQ Location
Boston, MA
Twitter
@starburstdata
3,466 Twitter followers
LinkedIn® Page
www.linkedin.com
478 employees on LinkedIn®
(24)4.9 out of 5
4th Easiest To Use in Big Data Processing and Distribution software
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Entry Level Price:Free
  • Overview
    Expand/Collapse Overview
  • Product Description
    How are these determined?Information
    This description is provided by the seller.

    Ilum: A Data Platform Built by Data Engineers, for Data Engineers Ilum is a Data Lakehouse platform that unifies data management, distributed processing, analytics, and AI workflows for AI engineer

    Users
    No information available
    Industries
    • Telecommunications
    Market Segment
    • 50% Enterprise
    • 33% Mid-Market
    User Sentiment
    How are these determined?Information
    These insights, currently in beta, are compiled from user reviews and grouped to display a high-level overview of the software.
    • Ilum is a data platform that can run on-premise or in the cloud, providing data warehousing, data science, and data ops capabilities.
    • Users like the flexibility of Ilum, its seamless integration with other tools, quick implementation, and the responsive customer support team.
    • Reviewers mentioned that Ilum could benefit from additional modules focused on ETL, more visual options for customizing dashboards, and requires some basic knowledge of K8S for initial setup.
  • Pros and Cons
    Expand/Collapse Pros and Cons
  • ILUM Pros and Cons
    How are these determined?Information
    Pros and Cons are compiled from review feedback and grouped into themes to provide an easy-to-understand summary of user reviews.
    Pros
    Ease of Use
    17
    Features
    17
    Integrations
    17
    Setup Ease
    16
    Easy Integrations
    15
    Cons
    Complex Setup
    9
    Difficult Setup
    9
    Learning Curve
    9
    UX Improvement
    8
    Complexity
    7
  • User Satisfaction
    Expand/Collapse User Satisfaction
  • ILUM features and usability ratings that predict user satisfaction
    9.7
    Has the product been a good partner in doing business?
    Average: 8.7
    10.0
    Real-Time Data Collection
    Average: 8.7
    10.0
    Machine Scaling
    Average: 8.6
    9.8
    Data Preparation
    Average: 8.6
  • Seller Details
    Expand/Collapse Seller Details
  • Seller Details
    Seller
    Ilum
    Company Website
    Year Founded
    2019
    HQ Location
    Santa Fe, US
    Twitter
    @IlumCloud
    19 Twitter followers
    LinkedIn® Page
    www.linkedin.com
    3 employees on LinkedIn®
Product Description
How are these determined?Information
This description is provided by the seller.

Ilum: A Data Platform Built by Data Engineers, for Data Engineers Ilum is a Data Lakehouse platform that unifies data management, distributed processing, analytics, and AI workflows for AI engineer

Users
No information available
Industries
  • Telecommunications
Market Segment
  • 50% Enterprise
  • 33% Mid-Market
User Sentiment
How are these determined?Information
These insights, currently in beta, are compiled from user reviews and grouped to display a high-level overview of the software.
  • Ilum is a data platform that can run on-premise or in the cloud, providing data warehousing, data science, and data ops capabilities.
  • Users like the flexibility of Ilum, its seamless integration with other tools, quick implementation, and the responsive customer support team.
  • Reviewers mentioned that Ilum could benefit from additional modules focused on ETL, more visual options for customizing dashboards, and requires some basic knowledge of K8S for initial setup.
ILUM Pros and Cons
How are these determined?Information
Pros and Cons are compiled from review feedback and grouped into themes to provide an easy-to-understand summary of user reviews.
Pros
Ease of Use
17
Features
17
Integrations
17
Setup Ease
16
Easy Integrations
15
Cons
Complex Setup
9
Difficult Setup
9
Learning Curve
9
UX Improvement
8
Complexity
7
ILUM features and usability ratings that predict user satisfaction
9.7
Has the product been a good partner in doing business?
Average: 8.7
10.0
Real-Time Data Collection
Average: 8.7
10.0
Machine Scaling
Average: 8.6
9.8
Data Preparation
Average: 8.6
Seller Details
Seller
Ilum
Company Website
Year Founded
2019
HQ Location
Santa Fe, US
Twitter
@IlumCloud
19 Twitter followers
LinkedIn® Page
www.linkedin.com
3 employees on LinkedIn®
(69)4.6 out of 5
11th Easiest To Use in Big Data Processing and Distribution software
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  • Overview
    Expand/Collapse Overview
  • Product Description
    How are these determined?Information
    This description is provided by the seller.

    Dremio is the intelligent lakehouse platform trusted by thousands of global enterprises like Amazon, Unilever, Shell, and S&P Global. Dremio amplifies AI and analytics initiatives by eliminating t

    Users
    No information available
    Industries
    • Financial Services
    • Information Technology and Services
    Market Segment
    • 49% Enterprise
    • 41% Mid-Market
  • Pros and Cons
    Expand/Collapse Pros and Cons
  • Dremio Pros and Cons
    How are these determined?Information
    Pros and Cons are compiled from review feedback and grouped into themes to provide an easy-to-understand summary of user reviews.
    Pros
    Ease of Use
    13
    Integrations
    10
    Performance
    7
    SQL Support
    7
    Data Management
    6
    Cons
    Difficulty
    5
    Poor Customer Support
    5
    Learning Curve
    4
    Difficult Setup
    3
    Poor Documentation
    3
  • User Satisfaction
    Expand/Collapse User Satisfaction
  • Dremio features and usability ratings that predict user satisfaction
    9.1
    Has the product been a good partner in doing business?
    Average: 8.7
    0.0
    No information available
    9.1
    Machine Scaling
    Average: 8.6
    8.7
    Data Preparation
    Average: 8.6
  • Seller Details
    Expand/Collapse Seller Details
  • Seller Details
    Seller
    Dremio
    Year Founded
    2015
    HQ Location
    Santa Clara, California
    Twitter
    @dremio
    5,084 Twitter followers
    LinkedIn® Page
    www.linkedin.com
    354 employees on LinkedIn®
Product Description
How are these determined?Information
This description is provided by the seller.

Dremio is the intelligent lakehouse platform trusted by thousands of global enterprises like Amazon, Unilever, Shell, and S&P Global. Dremio amplifies AI and analytics initiatives by eliminating t

Users
No information available
Industries
  • Financial Services
  • Information Technology and Services
Market Segment
  • 49% Enterprise
  • 41% Mid-Market
Dremio Pros and Cons
How are these determined?Information
Pros and Cons are compiled from review feedback and grouped into themes to provide an easy-to-understand summary of user reviews.
Pros
Ease of Use
13
Integrations
10
Performance
7
SQL Support
7
Data Management
6
Cons
Difficulty
5
Poor Customer Support
5
Learning Curve
4
Difficult Setup
3
Poor Documentation
3
Dremio features and usability ratings that predict user satisfaction
9.1
Has the product been a good partner in doing business?
Average: 8.7
0.0
No information available
9.1
Machine Scaling
Average: 8.6
8.7
Data Preparation
Average: 8.6
Seller Details
Seller
Dremio
Year Founded
2015
HQ Location
Santa Clara, California
Twitter
@dremio
5,084 Twitter followers
LinkedIn® Page
www.linkedin.com
354 employees on LinkedIn®
(34)4.4 out of 5
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  • Overview
    Expand/Collapse Overview
  • Product Description
    How are these determined?Information
    This description is provided by the seller.

    Azure Synapse Analytics is a cloud-based Enterprise Data Warehouse (EDW) that leverages Massively Parallel Processing (MPP) to quickly run complex queries across petabytes of data.

    Users
    No information available
    Industries
    • Information Technology and Services
    Market Segment
    • 41% Mid-Market
    • 35% Enterprise
  • User Satisfaction
    Expand/Collapse User Satisfaction
  • Azure Synapse Analytics features and usability ratings that predict user satisfaction
    8.3
    Has the product been a good partner in doing business?
    Average: 8.7
    7.8
    Real-Time Data Collection
    Average: 8.7
    8.1
    Machine Scaling
    Average: 8.6
    8.3
    Data Preparation
    Average: 8.6
  • Seller Details
    Expand/Collapse Seller Details
  • Seller Details
    Seller
    Microsoft
    Year Founded
    1975
    HQ Location
    Redmond, Washington
    Twitter
    @microsoft
    13,105,074 Twitter followers
    LinkedIn® Page
    www.linkedin.com
    220,934 employees on LinkedIn®
    Ownership
    MSFT
Product Description
How are these determined?Information
This description is provided by the seller.

Azure Synapse Analytics is a cloud-based Enterprise Data Warehouse (EDW) that leverages Massively Parallel Processing (MPP) to quickly run complex queries across petabytes of data.

Users
No information available
Industries
  • Information Technology and Services
Market Segment
  • 41% Mid-Market
  • 35% Enterprise
Azure Synapse Analytics features and usability ratings that predict user satisfaction
8.3
Has the product been a good partner in doing business?
Average: 8.7
7.8
Real-Time Data Collection
Average: 8.7
8.1
Machine Scaling
Average: 8.6
8.3
Data Preparation
Average: 8.6
Seller Details
Seller
Microsoft
Year Founded
1975
HQ Location
Redmond, Washington
Twitter
@microsoft
13,105,074 Twitter followers
LinkedIn® Page
www.linkedin.com
220,934 employees on LinkedIn®
Ownership
MSFT
(216)4.3 out of 5
14th Easiest To Use in Big Data Processing and Distribution software
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Entry Level Price:Free
  • Overview
    Expand/Collapse Overview
  • Product Description
    How are these determined?Information
    This description is provided by the seller.

    Vertica is the unified analytics platform, based on a massively scalable architecture with a broad set of analytical functions spanning event and time series, pattern matching, geospatial, and built-i

    Users
    • Senior Software Engineer
    • Data Engineer
    Industries
    • Computer Software
    • Information Technology and Services
    Market Segment
    • 44% Enterprise
    • 39% Mid-Market
  • User Satisfaction
    Expand/Collapse User Satisfaction
  • OpenText Vertica features and usability ratings that predict user satisfaction
    8.3
    Has the product been a good partner in doing business?
    Average: 8.7
    8.6
    Real-Time Data Collection
    Average: 8.7
    8.3
    Machine Scaling
    Average: 8.6
    8.4
    Data Preparation
    Average: 8.6
  • Seller Details
    Expand/Collapse Seller Details
  • Seller Details
    Seller
    OpenText
    Year Founded
    1991
    HQ Location
    Waterloo, ON
    Twitter
    @OpenText
    21,626 Twitter followers
    LinkedIn® Page
    www.linkedin.com
    23,200 employees on LinkedIn®
    Ownership
    NASDAQ:OTEX
Product Description
How are these determined?Information
This description is provided by the seller.

Vertica is the unified analytics platform, based on a massively scalable architecture with a broad set of analytical functions spanning event and time series, pattern matching, geospatial, and built-i

Users
  • Senior Software Engineer
  • Data Engineer
Industries
  • Computer Software
  • Information Technology and Services
Market Segment
  • 44% Enterprise
  • 39% Mid-Market
OpenText Vertica features and usability ratings that predict user satisfaction
8.3
Has the product been a good partner in doing business?
Average: 8.7
8.6
Real-Time Data Collection
Average: 8.7
8.3
Machine Scaling
Average: 8.6
8.4
Data Preparation
Average: 8.6
Seller Details
Seller
OpenText
Year Founded
1991
HQ Location
Waterloo, ON
Twitter
@OpenText
21,626 Twitter followers
LinkedIn® Page
www.linkedin.com
23,200 employees on LinkedIn®
Ownership
NASDAQ:OTEX
Entry Level Price:Starting at $29,000.00
  • Overview
    Expand/Collapse Overview
  • Product Description
    How are these determined?Information
    This description is provided by the seller.

    Control-M from BMC Software is a digital operations orchestration platform designed to help organizations connect applications, data pipelines, and infrastructure processes within a unified ecosystem.

    Users
    No information available
    Industries
    • Information Technology and Services
    • Financial Services
    Market Segment
    • 56% Enterprise
    • 21% Mid-Market
  • Pros and Cons
    Expand/Collapse Pros and Cons
  • Control-M Pros and Cons
    How are these determined?Information
    Pros and Cons are compiled from review feedback and grouped into themes to provide an easy-to-understand summary of user reviews.
    Pros
    Ease of Use
    14
    Features
    11
    Time-saving
    10
    Task Automation
    9
    Efficiency
    8
    Cons
    Complexity
    10
    Difficult Learning
    6
    Learning Curve
    6
    Poor UI Design
    6
    Slow Performance
    6
  • User Satisfaction
    Expand/Collapse User Satisfaction
  • Control-M features and usability ratings that predict user satisfaction
    9.0
    Has the product been a good partner in doing business?
    Average: 8.7
    8.6
    Real-Time Data Collection
    Average: 8.7
    8.0
    Machine Scaling
    Average: 8.6
    7.3
    Data Preparation
    Average: 8.6
  • Seller Details
    Expand/Collapse Seller Details
  • Seller Details
    Company Website
    Year Founded
    1980
    HQ Location
    Houston, TX
    Twitter
    @BMCSoftware
    48,229 Twitter followers
    LinkedIn® Page
    www.linkedin.com
    9,064 employees on LinkedIn®
Product Description
How are these determined?Information
This description is provided by the seller.

Control-M from BMC Software is a digital operations orchestration platform designed to help organizations connect applications, data pipelines, and infrastructure processes within a unified ecosystem.

Users
No information available
Industries
  • Information Technology and Services
  • Financial Services
Market Segment
  • 56% Enterprise
  • 21% Mid-Market
Control-M Pros and Cons
How are these determined?Information
Pros and Cons are compiled from review feedback and grouped into themes to provide an easy-to-understand summary of user reviews.
Pros
Ease of Use
14
Features
11
Time-saving
10
Task Automation
9
Efficiency
8
Cons
Complexity
10
Difficult Learning
6
Learning Curve
6
Poor UI Design
6
Slow Performance
6
Control-M features and usability ratings that predict user satisfaction
9.0
Has the product been a good partner in doing business?
Average: 8.7
8.6
Real-Time Data Collection
Average: 8.7
8.0
Machine Scaling
Average: 8.6
7.3
Data Preparation
Average: 8.6
Seller Details
Company Website
Year Founded
1980
HQ Location
Houston, TX
Twitter
@BMCSoftware
48,229 Twitter followers
LinkedIn® Page
www.linkedin.com
9,064 employees on LinkedIn®

Frequently asked questions about Big Data Processing And Distribution Systems

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