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Best Big Data Processing And Distribution Systems for Medium-Sized Businesses

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, medium-sized business features, pricing, setup, and installation differ from businesses of other sizes, which is why we match buyers to the right Medium-Sized 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 Medium-Sized 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 Medium-Sized Business Big Data Processing And Distribution Systems category, a product must have at least 10 reviews left by a reviewer from a medium-sized 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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18 Listings in Big Data Processing and Distribution Available
(1,202)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
    147
    Speed
    116
    Scalability
    102
    Query Efficiency
    101
    Integrations
    99
    Cons
    Expensive
    108
    Query Issues
    65
    Learning Curve
    53
    Cost Management
    47
    Cost Issues
    43
  • 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
    31,497,617 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
147
Speed
116
Scalability
102
Query Efficiency
101
Integrations
99
Cons
Expensive
108
Query Issues
65
Learning Curve
53
Cost Management
47
Cost Issues
43
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
31,497,617 Twitter followers
LinkedIn® Page
www.linkedin.com
325,307 employees on LinkedIn®
(626)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
Save to My Lists
  • 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
    265
    Ease of Use
    254
    Integrations
    178
    Collaboration
    142
    Easy Integrations
    139
    Cons
    Learning Curve
    100
    Expensive
    86
    Steep Learning Curve
    86
    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
    83,849 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
265
Ease of Use
254
Integrations
178
Collaboration
142
Easy Integrations
139
Cons
Learning Curve
100
Expensive
86
Steep Learning Curve
86
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
83,849 Twitter followers
LinkedIn® Page
www.linkedin.com
13,680 employees on LinkedIn®

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(657)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
    98
    Features
    69
    Data Management
    64
    Integrations
    59
    Scalability
    59
    Cons
    Expensive
    51
    Cost
    29
    Cost Management
    25
    Learning Curve
    22
    Feature Limitations
    21
  • 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
    152 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
98
Features
69
Data Management
64
Integrations
59
Scalability
59
Cons
Expensive
51
Cost
29
Cost Management
25
Learning Curve
22
Feature Limitations
21
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
152 Twitter followers
LinkedIn® Page
www.linkedin.com
10,207 employees on LinkedIn®
(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
    29
    Features
    20
    Analytics
    18
    Data Management
    17
    Flexibility
    16
    Cons
    Learning Curve
    22
    Expensive
    15
    Complexity
    10
    Difficulty
    10
    Integration Issues
    9
  • 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
    709,117 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
29
Features
20
Analytics
18
Data Management
17
Flexibility
16
Cons
Learning Curve
22
Expensive
15
Complexity
10
Difficulty
10
Integration Issues
9
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
709,117 Twitter followers
LinkedIn® Page
www.linkedin.com
339,241 employees on LinkedIn®
(360)4.3 out of 5
7th 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.

    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
    20
    Speed
    17
    Analytics
    16
    Scalability
    16
    Ease of Use
    13
    Cons
    Learning Curve
    12
    Integration Issues
    6
    Performance Issues
    6
    Poor UI Design
    6
    Complexity
    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
    93,496 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
20
Speed
17
Analytics
16
Scalability
16
Ease of Use
13
Cons
Learning Curve
12
Integration Issues
6
Performance Issues
6
Poor UI Design
6
Complexity
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
93,496 Twitter followers
LinkedIn® Page
www.linkedin.com
9,948 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
    29
    Ease of Use
    28
    Performance
    20
    Easy Integrations
    18
    Integrations
    18
    Cons
    Expensive
    17
    Performance Issues
    10
    Slow Performance
    9
    High Licensing Costs
    8
    Expensive Licensing
    7
  • 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
    8.6
    Real-Time Data Collection
    Average: 8.7
    8.3
    Machine Scaling
    Average: 8.6
    8.6
    Data Preparation
    Average: 8.6
  • Seller Details
    Expand/Collapse Seller Details
  • Seller Details
    Seller
    Microsoft
    Year Founded
    1975
    HQ Location
    Redmond, Washington
    Twitter
    @microsoft
    13,133,301 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
29
Ease of Use
28
Performance
20
Easy Integrations
18
Integrations
18
Cons
Expensive
17
Performance Issues
10
Slow Performance
9
High Licensing Costs
8
Expensive Licensing
7
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
8.6
Real-Time Data Collection
Average: 8.7
8.3
Machine Scaling
Average: 8.6
8.6
Data Preparation
Average: 8.6
Seller Details
Seller
Microsoft
Year Founded
1975
HQ Location
Redmond, Washington
Twitter
@microsoft
13,133,301 Twitter followers
LinkedIn® Page
www.linkedin.com
220,934 employees on LinkedIn®
Ownership
MSFT
(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
    13,133,301 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
13,133,301 Twitter followers
LinkedIn® Page
www.linkedin.com
220,934 employees on LinkedIn®
Ownership
MSFT
(44)4.2 out of 5
View top Consulting Services for Google Cloud Dataflow
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  • Overview
    Expand/Collapse Overview
  • Product Description
    How are these determined?Information
    This description is provided by the seller.

    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 workaround

    Users
    No information available
    Industries
    • Computer Software
    Market Segment
    • 39% Small-Business
    • 32% Enterprise
  • Pros and Cons
    Expand/Collapse Pros and Cons
  • Google Cloud Dataflow 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
    Analytics
    1
    Ease of Use
    1
    Easy Management
    1
    Features
    1
    Insights
    1
    Cons
    Cost Management
    1
    Expensive
    1
    Installation Difficulty
    1
    Learning Difficulty
    1
  • User Satisfaction
    Expand/Collapse User Satisfaction
  • Google Cloud Dataflow features and usability ratings that predict user satisfaction
    9.0
    Has the product been a good partner in doing business?
    Average: 8.7
    8.3
    Real-Time Data Collection
    Average: 8.7
    8.8
    Machine Scaling
    Average: 8.6
    8.6
    Data Preparation
    Average: 8.6
  • Seller Details
    Expand/Collapse Seller Details
  • Seller Details
    Seller
    Google
    Year Founded
    1998
    HQ Location
    Mountain View, CA
    Twitter
    @google
    31,497,617 Twitter followers
    LinkedIn® Page
    www.linkedin.com
    325,307 employees on LinkedIn®
    Ownership
    NASDAQ:GOOG
Product Description
How are these determined?Information
This description is provided by the seller.

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 workaround

Users
No information available
Industries
  • Computer Software
Market Segment
  • 39% Small-Business
  • 32% Enterprise
Google Cloud Dataflow 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
Analytics
1
Ease of Use
1
Easy Management
1
Features
1
Insights
1
Cons
Cost Management
1
Expensive
1
Installation Difficulty
1
Learning Difficulty
1
Google Cloud Dataflow features and usability ratings that predict user satisfaction
9.0
Has the product been a good partner in doing business?
Average: 8.7
8.3
Real-Time Data Collection
Average: 8.7
8.8
Machine Scaling
Average: 8.6
8.6
Data Preparation
Average: 8.6
Seller Details
Seller
Google
Year Founded
1998
HQ Location
Mountain View, CA
Twitter
@google
31,497,617 Twitter followers
LinkedIn® Page
www.linkedin.com
325,307 employees on LinkedIn®
Ownership
NASDAQ:GOOG
  • 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
    104
    Speed
    80
    Performance Evaluation
    45
    Scalability
    43
    Performance
    42
    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
104
Speed
80
Performance Evaluation
45
Scalability
43
Performance
42
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®
(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
    SQL Support
    8
    Performance
    7
    Data Management
    6
    Cons
    Poor Customer Support
    6
    Difficulty
    4
    Difficult Setup
    3
    Learning Curve
    3
    Connectivity Issues
    2
  • 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
    5,086 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
SQL Support
8
Performance
7
Data Management
6
Cons
Poor Customer Support
6
Difficulty
4
Difficult Setup
3
Learning Curve
3
Connectivity Issues
2
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
5,086 Twitter followers
LinkedIn® Page
www.linkedin.com
354 employees on LinkedIn®
(112)4.4 out of 5
8th 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.

    Cloud-native service for data in motion built by the original creators of Apache Kafka® Today’s consumers have the world at their fingertips and hold an unforgiving expectation for end-to-end real-ti

    Users
    • Software Engineer
    • Senior Software Engineer
    Industries
    • Computer Software
    • Information Technology and Services
    Market Segment
    • 36% Enterprise
    • 35% Small-Business
  • Pros and Cons
    Expand/Collapse Pros and Cons
  • Confluent 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
    Cloud Computing
    1
    Cloud Services
    1
    Connectors
    1
    Data Integration
    1
    Documentation
    1
    Cons
    Cost Estimation
    1
    Expensive
    1
    Initial Difficulties
    1
    Lack of Features
    1
    Learning Curve
    1
  • User Satisfaction
    Expand/Collapse User Satisfaction
  • Confluent features and usability ratings that predict user satisfaction
    8.5
    Has the product been a good partner in doing business?
    Average: 8.7
    9.0
    Real-Time Data Collection
    Average: 8.7
    8.2
    Machine Scaling
    Average: 8.6
    7.8
    Data Preparation
    Average: 8.6
  • Seller Details
    Expand/Collapse Seller Details
  • Seller Details
    Seller
    Confluent
    Year Founded
    2014
    HQ Location
    Mountain View, California
    Twitter
    @ConfluentInc
    43,527 Twitter followers
    LinkedIn® Page
    www.linkedin.com
    3,654 employees on LinkedIn®
    Ownership
    NASDAQ: CFLT
Product Description
How are these determined?Information
This description is provided by the seller.

Cloud-native service for data in motion built by the original creators of Apache Kafka® Today’s consumers have the world at their fingertips and hold an unforgiving expectation for end-to-end real-ti

Users
  • Software Engineer
  • Senior Software Engineer
Industries
  • Computer Software
  • Information Technology and Services
Market Segment
  • 36% Enterprise
  • 35% Small-Business
Confluent 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
Cloud Computing
1
Cloud Services
1
Connectors
1
Data Integration
1
Documentation
1
Cons
Cost Estimation
1
Expensive
1
Initial Difficulties
1
Lack of Features
1
Learning Curve
1
Confluent features and usability ratings that predict user satisfaction
8.5
Has the product been a good partner in doing business?
Average: 8.7
9.0
Real-Time Data Collection
Average: 8.7
8.2
Machine Scaling
Average: 8.6
7.8
Data Preparation
Average: 8.6
Seller Details
Seller
Confluent
Year Founded
2014
HQ Location
Mountain View, California
Twitter
@ConfluentInc
43,527 Twitter followers
LinkedIn® Page
www.linkedin.com
3,654 employees on LinkedIn®
Ownership
NASDAQ: CFLT
  • Overview
    Expand/Collapse Overview
  • Product Description
    How are these determined?Information
    This description is provided by the seller.

    Posit was founded with the mission to create open-source software for data science, scientific research, and technical communication. We don’t just say this: it’s fundamentally baked into our corporat

    Users
    • Research Assistant
    • Graduate Research Assistant
    Industries
    • Higher Education
    • Information Technology and Services
    Market Segment
    • 49% Enterprise
    • 27% Mid-Market
  • Pros and Cons
    Expand/Collapse Pros and Cons
  • Posit 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
    7
    Open Source
    5
    Features
    4
    Easy Integrations
    3
    Cloud Computing
    2
    Cons
    Slow Performance
    4
    Learning Curve
    2
    Performance Issues
    2
    Poor UI Design
    2
    Slow Loading
    2
  • User Satisfaction
    Expand/Collapse User Satisfaction
  • Posit features and usability ratings that predict user satisfaction
    8.5
    Has the product been a good partner in doing business?
    Average: 8.7
    9.0
    Real-Time Data Collection
    Average: 8.7
    7.9
    Machine Scaling
    Average: 8.6
    8.7
    Data Preparation
    Average: 8.6
  • Seller Details
    Expand/Collapse Seller Details
  • Seller Details
    Seller
    Posit
    Year Founded
    2009
    HQ Location
    Boston, MA
    Twitter
    @posit_pbc
    122,534 Twitter followers
    LinkedIn® Page
    www.linkedin.com
    459 employees on LinkedIn®
Product Description
How are these determined?Information
This description is provided by the seller.

Posit was founded with the mission to create open-source software for data science, scientific research, and technical communication. We don’t just say this: it’s fundamentally baked into our corporat

Users
  • Research Assistant
  • Graduate Research Assistant
Industries
  • Higher Education
  • Information Technology and Services
Market Segment
  • 49% Enterprise
  • 27% Mid-Market
Posit 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
7
Open Source
5
Features
4
Easy Integrations
3
Cloud Computing
2
Cons
Slow Performance
4
Learning Curve
2
Performance Issues
2
Poor UI Design
2
Slow Loading
2
Posit features and usability ratings that predict user satisfaction
8.5
Has the product been a good partner in doing business?
Average: 8.7
9.0
Real-Time Data Collection
Average: 8.7
7.9
Machine Scaling
Average: 8.6
8.7
Data Preparation
Average: 8.6
Seller Details
Seller
Posit
Year Founded
2009
HQ Location
Boston, MA
Twitter
@posit_pbc
122,534 Twitter followers
LinkedIn® Page
www.linkedin.com
459 employees on LinkedIn®
(216)4.3 out of 5
13th 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
    21,628 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
21,628 Twitter followers
LinkedIn® Page
www.linkedin.com
23,200 employees on LinkedIn®
Ownership
NASDAQ:OTEX
(64)4.1 out of 5
12th 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.

    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
    2,217,364 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
2,217,364 Twitter followers
LinkedIn® Page
www.linkedin.com
143,584 employees on LinkedIn®
Ownership
NASDAQ: AMZN
(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
    25
    Integrations
    22
    Ease of Use
    20
    Large Datasets
    20
    Query Efficiency
    20
    Cons
    Learning Curve
    16
    Slow Performance
    16
    Query Issues
    14
    Difficult Setup
    13
    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
    3,469 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
25
Integrations
22
Ease of Use
20
Large Datasets
20
Query Efficiency
20
Cons
Learning Curve
16
Slow Performance
16
Query Issues
14
Difficult Setup
13
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
3,469 Twitter followers
LinkedIn® Page
www.linkedin.com
478 employees on LinkedIn®

Frequently asked questions about Big Data Processing And Distribution Systems

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