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Best Columnar Databases

Shalaka Joshi
SJ
Researched and written by Shalaka Joshi

Columnar databases store data by columns rather than by rows. The data storage format in these solutions makes them faster and more efficient for instant analytical queries. These databases are used mainly in data warehouses to handle and process massive volumes of data from multiple sources by serving as a basis for business intelligence tools. These databases support document creation, retrieval via query, updating and editing, and deletion of information. Columnar stores, because of their data storage format, help minimize resource usage related to queries on big data sets. Businesses interested in implementing a database for data warehousing and big data processing may opt for a columnar database.

There are other database types similar but slightly different than columnar databases software including object-oriented databases software, graph databases, key-value databases, and more.

To qualify for inclusion in the Columnar Databases category, a product must:

Provide data storage
Store data in columnar format
Allow users to retrieve data
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Best Columnar Databases At A Glance

Highest Performer:
Easiest to Use:
Best Free Software:
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Easiest to Use:
Best Free Software:

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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28 Listings in Columnar Databases Available
(1,201)4.5 out of 5
1st Easiest To Use in Columnar Databases 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
    9.1
    Data Model
    Average: 8.7
    8.8
    Data Types
    Average: 8.5
    8.7
    Has the product been a good partner in doing business?
    Average: 8.5
    8.5
    Integrated Cache
    Average: 8.5
  • Seller Details
    Expand/Collapse Seller Details
  • Seller Details
    Seller
    Google
    Company Website
    Year Founded
    1998
    HQ Location
    Mountain View, CA
    Twitter
    @google
    31,508,752 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
9.1
Data Model
Average: 8.7
8.8
Data Types
Average: 8.5
8.7
Has the product been a good partner in doing business?
Average: 8.5
8.5
Integrated Cache
Average: 8.5
Seller Details
Seller
Google
Company Website
Year Founded
1998
HQ Location
Mountain View, CA
Twitter
@google
31,508,752 Twitter followers
LinkedIn® Page
www.linkedin.com
325,307 employees on LinkedIn®
(666)4.6 out of 5
Optimized for quick response
2nd Easiest To Use in Columnar Databases software
View top Consulting Services for Snowflake
Save to My Lists
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
    • 42% 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
    84
    Features
    64
    Data Management
    61
    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
    9.2
    Data Model
    Average: 8.7
    9.2
    Data Types
    Average: 8.5
    9.0
    Has the product been a good partner in doing business?
    Average: 8.5
    9.2
    Integrated Cache
    Average: 8.5
  • Seller Details
    Expand/Collapse Seller Details
  • Seller Details
    Company Website
    Year Founded
    2012
    HQ Location
    San Mateo, CA
    Twitter
    @SnowflakeDB
    159 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
  • 42% 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
84
Features
64
Data Management
61
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
9.2
Data Model
Average: 8.7
9.2
Data Types
Average: 8.5
9.0
Has the product been a good partner in doing business?
Average: 8.5
9.2
Integrated Cache
Average: 8.5
Seller Details
Company Website
Year Founded
2012
HQ Location
San Mateo, CA
Twitter
@SnowflakeDB
159 Twitter followers
LinkedIn® Page
www.linkedin.com
10,207 employees on LinkedIn®

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(397)4.3 out of 5
3rd Easiest To Use in Columnar Databases software
View top Consulting Services for Amazon Redshift
Save to My Lists
Entry Level Price:$1.22 - $3.26 Per hour
  • Overview
    Expand/Collapse Overview
  • Product Description
    How are these determined?Information
    This description is provided by the seller.

    Tens of thousands of customers use Amazon Redshift, a fast, fully managed, petabyte-scale data warehouse service that makes it simple and cost-effective to efficiently analyze all your data using your

    Users
    • Data Engineer
    • Senior Data Engineer
    Industries
    • Information Technology and Services
    • Computer Software
    Market Segment
    • 40% Enterprise
    • 38% Mid-Market
  • Pros and Cons
    Expand/Collapse Pros and Cons
  • Amazon Redshift 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
    Integrations
    6
    Speed
    6
    Fast Querying
    5
    Large Datasets
    5
    Cons
    Complexity
    5
    Feature Limitations
    5
    Software Limitations
    5
    Query Issues
    4
    Query Optimization
    4
  • User Satisfaction
    Expand/Collapse User Satisfaction
  • Amazon Redshift features and usability ratings that predict user satisfaction
    8.4
    Data Model
    Average: 8.7
    8.4
    Data Types
    Average: 8.5
    8.7
    Has the product been a good partner in doing business?
    Average: 8.5
    8.2
    Integrated Cache
    Average: 8.5
  • Seller Details
    Expand/Collapse Seller Details
  • Seller Details
    Year Founded
    2006
    HQ Location
    Seattle, WA
    Twitter
    @awscloud
    2,217,637 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.

Tens of thousands of customers use Amazon Redshift, a fast, fully managed, petabyte-scale data warehouse service that makes it simple and cost-effective to efficiently analyze all your data using your

Users
  • Data Engineer
  • Senior Data Engineer
Industries
  • Information Technology and Services
  • Computer Software
Market Segment
  • 40% Enterprise
  • 38% Mid-Market
Amazon Redshift 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
Integrations
6
Speed
6
Fast Querying
5
Large Datasets
5
Cons
Complexity
5
Feature Limitations
5
Software Limitations
5
Query Issues
4
Query Optimization
4
Amazon Redshift features and usability ratings that predict user satisfaction
8.4
Data Model
Average: 8.7
8.4
Data Types
Average: 8.5
8.7
Has the product been a good partner in doing business?
Average: 8.5
8.2
Integrated Cache
Average: 8.5
Seller Details
Year Founded
2006
HQ Location
Seattle, WA
Twitter
@awscloud
2,217,637 Twitter followers
LinkedIn® Page
www.linkedin.com
143,584 employees on LinkedIn®
Ownership
NASDAQ: AMZN
(20)4.4 out of 5
View top Consulting Services for ClickHouse
Save to My Lists
Entry Level Price:Starting at $1.00
  • Overview
    Expand/Collapse Overview
  • Product Description
    How are these determined?Information
    This description is provided by the seller.

    ClickHouse is the fastest and most resource efficient real-time database and data warehouse. ClickHouse is optimized to serve a wide range of data-intensive workloads, from powering interactive user-f

    Users
    No information available
    Industries
    • Information Technology and Services
    Market Segment
    • 45% Small-Business
    • 45% Mid-Market
  • Pros and Cons
    Expand/Collapse Pros and Cons
  • ClickHouse 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
    Integrations
    2
    Query Efficiency
    2
    Query Speed
    2
    Speed
    2
    Cons
    Beginner Unfriendliness
    1
    Complex Usage
    1
    Query Optimization
    1
    Required Expertise
    1
    Training Required
    1
  • User Satisfaction
    Expand/Collapse User Satisfaction
  • ClickHouse features and usability ratings that predict user satisfaction
    9.2
    Data Model
    Average: 8.7
    9.0
    Data Types
    Average: 8.5
    10.0
    Has the product been a good partner in doing business?
    Average: 8.5
    8.1
    Integrated Cache
    Average: 8.5
  • Seller Details
    Expand/Collapse Seller Details
  • Seller Details
    Year Founded
    2021
    HQ Location
    Palo Alto, US
    Twitter
    @ClickhouseDB
    14,055 Twitter followers
    LinkedIn® Page
    www.linkedin.com
    360 employees on LinkedIn®
Product Description
How are these determined?Information
This description is provided by the seller.

ClickHouse is the fastest and most resource efficient real-time database and data warehouse. ClickHouse is optimized to serve a wide range of data-intensive workloads, from powering interactive user-f

Users
No information available
Industries
  • Information Technology and Services
Market Segment
  • 45% Small-Business
  • 45% Mid-Market
ClickHouse 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
Integrations
2
Query Efficiency
2
Query Speed
2
Speed
2
Cons
Beginner Unfriendliness
1
Complex Usage
1
Query Optimization
1
Required Expertise
1
Training Required
1
ClickHouse features and usability ratings that predict user satisfaction
9.2
Data Model
Average: 8.7
9.0
Data Types
Average: 8.5
10.0
Has the product been a good partner in doing business?
Average: 8.5
8.1
Integrated Cache
Average: 8.5
Seller Details
Year Founded
2021
HQ Location
Palo Alto, US
Twitter
@ClickhouseDB
14,055 Twitter followers
LinkedIn® Page
www.linkedin.com
360 employees on LinkedIn®
(224)4.4 out of 5
View top Consulting Services for MariaDB
Save to My Lists
  • Overview
    Expand/Collapse Overview
  • Product Description
    How are these determined?Information
    This description is provided by the seller.

    MariaDB frees companies from the costs, constraints and complexity of proprietary databases, enabling them to reinvest in what matters most – rapidly developing innovative, customer-facing application

    Users
    • Software Engineer
    • Senior Software Engineer
    Industries
    • Information Technology and Services
    • Computer Software
    Market Segment
    • 43% Small-Business
    • 33% Mid-Market
  • Pros and Cons
    Expand/Collapse Pros and Cons
  • MariaDB 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
    2
    Easy Integrations
    2
    Query Speed
    2
    Backup Services
    1
    Connectivity
    1
    Cons
    Beginner Unfriendliness
    1
    Connectivity Issues
    1
    Difficult Learning
    1
    Error Handling
    1
    Feature Limitations
    1
  • User Satisfaction
    Expand/Collapse User Satisfaction
  • MariaDB features and usability ratings that predict user satisfaction
    8.8
    Data Model
    Average: 8.7
    8.9
    Data Types
    Average: 8.5
    8.1
    Has the product been a good partner in doing business?
    Average: 8.5
    9.0
    Integrated Cache
    Average: 8.5
  • Seller Details
    Expand/Collapse Seller Details
  • Seller Details
    Seller
    MariaDB
    Year Founded
    2014
    HQ Location
    Espoo, Finland
    Twitter
    @mariadb
    454,732 Twitter followers
    LinkedIn® Page
    www.linkedin.com
    316 employees on LinkedIn®
    Ownership
    NYSE: MRDB
Product Description
How are these determined?Information
This description is provided by the seller.

MariaDB frees companies from the costs, constraints and complexity of proprietary databases, enabling them to reinvest in what matters most – rapidly developing innovative, customer-facing application

Users
  • Software Engineer
  • Senior Software Engineer
Industries
  • Information Technology and Services
  • Computer Software
Market Segment
  • 43% Small-Business
  • 33% Mid-Market
MariaDB 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
2
Easy Integrations
2
Query Speed
2
Backup Services
1
Connectivity
1
Cons
Beginner Unfriendliness
1
Connectivity Issues
1
Difficult Learning
1
Error Handling
1
Feature Limitations
1
MariaDB features and usability ratings that predict user satisfaction
8.8
Data Model
Average: 8.7
8.9
Data Types
Average: 8.5
8.1
Has the product been a good partner in doing business?
Average: 8.5
9.0
Integrated Cache
Average: 8.5
Seller Details
Seller
MariaDB
Year Founded
2014
HQ Location
Espoo, Finland
Twitter
@mariadb
454,732 Twitter followers
LinkedIn® Page
www.linkedin.com
316 employees on LinkedIn®
Ownership
NYSE: MRDB
  • Overview
    Expand/Collapse Overview
  • Product Description
    How are these determined?Information
    This description is provided by the seller.

    An Open-Source Database System

    Users
    No information available
    Industries
    • Computer Software
    Market Segment
    • 56% Small-Business
    • 38% Mid-Market
  • Pros and Cons
    Expand/Collapse Pros and Cons
  • MonetDB 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
    8
    Features
    5
    Speed
    5
    Performance
    4
    Usability
    3
    Cons
    Complex Setup
    3
    Connectivity Issues
    2
    Limited Customization
    1
    Limited Features
    1
    Poor Documentation
    1
  • User Satisfaction
    Expand/Collapse User Satisfaction
  • MonetDB features and usability ratings that predict user satisfaction
    8.6
    Data Model
    Average: 8.7
    8.6
    Data Types
    Average: 8.5
    8.3
    Has the product been a good partner in doing business?
    Average: 8.5
    8.3
    Integrated Cache
    Average: 8.5
  • Seller Details
    Expand/Collapse Seller Details
  • Seller Details
    Seller
    MonetDB
    Year Founded
    2013
    HQ Location
    Amsterdam, NL
    LinkedIn® Page
    www.linkedin.com
    8 employees on LinkedIn®
Product Description
How are these determined?Information
This description is provided by the seller.

An Open-Source Database System

Users
No information available
Industries
  • Computer Software
Market Segment
  • 56% Small-Business
  • 38% Mid-Market
MonetDB 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
8
Features
5
Speed
5
Performance
4
Usability
3
Cons
Complex Setup
3
Connectivity Issues
2
Limited Customization
1
Limited Features
1
Poor Documentation
1
MonetDB features and usability ratings that predict user satisfaction
8.6
Data Model
Average: 8.7
8.6
Data Types
Average: 8.5
8.3
Has the product been a good partner in doing business?
Average: 8.5
8.3
Integrated Cache
Average: 8.5
Seller Details
Seller
MonetDB
Year Founded
2013
HQ Location
Amsterdam, NL
LinkedIn® Page
www.linkedin.com
8 employees on LinkedIn®
(216)4.3 out of 5
4th Easiest To Use in Columnar Databases software
Save to My Lists
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
    8.4
    Data Model
    Average: 8.7
    8.0
    Data Types
    Average: 8.5
    8.3
    Has the product been a good partner in doing business?
    Average: 8.5
    8.5
    Integrated Cache
    Average: 8.5
  • Seller Details
    Expand/Collapse Seller Details
  • Seller Details
    Seller
    OpenText
    Year Founded
    1991
    HQ Location
    Waterloo, ON
    Twitter
    @OpenText
    21,629 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
8.4
Data Model
Average: 8.7
8.0
Data Types
Average: 8.5
8.3
Has the product been a good partner in doing business?
Average: 8.5
8.5
Integrated Cache
Average: 8.5
Seller Details
Seller
OpenText
Year Founded
1991
HQ Location
Waterloo, ON
Twitter
@OpenText
21,629 Twitter followers
LinkedIn® Page
www.linkedin.com
23,200 employees on LinkedIn®
Ownership
NASDAQ:OTEX
Entry Level Price:Free
  • Overview
    Expand/Collapse Overview
  • Product Description
    How are these determined?Information
    This description is provided by the seller.

    The real-time database for analytics, search, and AI. Store any type of data and combine the simplicity of SQL with the scalability of NoSQL. CrateDB is an open source, multi-model, distributed and co

    Users
    • Software Engineer
    • Data Engineer
    Industries
    • Computer Software
    • Information Technology and Services
    Market Segment
    • 55% Small-Business
    • 31% Mid-Market
  • Pros and Cons
    Expand/Collapse Pros and Cons
  • CrateDB 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
    10
    Easy Integrations
    10
    SQL Usage
    10
    Features
    8
    Scalability
    8
    Cons
    Lack of Features
    3
    Poor Documentation
    3
    Software Limitations
    3
    Complex Configuration
    2
    Insufficient Training
    2
  • User Satisfaction
    Expand/Collapse User Satisfaction
  • CrateDB features and usability ratings that predict user satisfaction
    9.0
    Data Model
    Average: 8.7
    9.2
    Data Types
    Average: 8.5
    9.3
    Has the product been a good partner in doing business?
    Average: 8.5
    10.0
    Integrated Cache
    Average: 8.5
  • Seller Details
    Expand/Collapse Seller Details
  • Seller Details
    Seller
    CrateDB
    Company Website
    Year Founded
    2013
    HQ Location
    Redwood City, CA
    Twitter
    @cratedb
    4,210 Twitter followers
    LinkedIn® Page
    www.linkedin.com
    46 employees on LinkedIn®
Product Description
How are these determined?Information
This description is provided by the seller.

The real-time database for analytics, search, and AI. Store any type of data and combine the simplicity of SQL with the scalability of NoSQL. CrateDB is an open source, multi-model, distributed and co

Users
  • Software Engineer
  • Data Engineer
Industries
  • Computer Software
  • Information Technology and Services
Market Segment
  • 55% Small-Business
  • 31% Mid-Market
CrateDB 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
10
Easy Integrations
10
SQL Usage
10
Features
8
Scalability
8
Cons
Lack of Features
3
Poor Documentation
3
Software Limitations
3
Complex Configuration
2
Insufficient Training
2
CrateDB features and usability ratings that predict user satisfaction
9.0
Data Model
Average: 8.7
9.2
Data Types
Average: 8.5
9.3
Has the product been a good partner in doing business?
Average: 8.5
10.0
Integrated Cache
Average: 8.5
Seller Details
Seller
CrateDB
Company Website
Year Founded
2013
HQ Location
Redwood City, CA
Twitter
@cratedb
4,210 Twitter followers
LinkedIn® Page
www.linkedin.com
46 employees on LinkedIn®
Entry Level Price:Free
  • Overview
    Expand/Collapse Overview
  • Product Description
    How are these determined?Information
    This description is provided by the seller.

    StarTree Cloud is a fully-managed user-facing real-time analytics Database-as-a-Service (DBaaS) designed for OLAP at massive speed and scale. Based on Apache Pinot™, StarTree Cloud provides enterprise

    Users
    No information available
    Industries
    • Computer Software
    • Financial Services
    Market Segment
    • 38% Small-Business
    • 31% Mid-Market
  • Pros and Cons
    Expand/Collapse Pros and Cons
  • StarTree 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
    4
    Fast Querying
    4
    Large Datasets
    4
    Performance
    4
    Big Data Handling
    3
    Cons
    Learning Curve
    4
    Complex Setup
    3
    Difficult Setup
    3
    Insufficient Documentation
    3
    Poor Documentation
    3
  • User Satisfaction
    Expand/Collapse User Satisfaction
  • StarTree features and usability ratings that predict user satisfaction
    8.3
    Data Model
    Average: 8.7
    8.1
    Data Types
    Average: 8.5
    8.8
    Has the product been a good partner in doing business?
    Average: 8.5
    8.7
    Integrated Cache
    Average: 8.5
  • Seller Details
    Expand/Collapse Seller Details
  • Seller Details
    Seller
    StarTree
    Company Website
    Year Founded
    2019
    HQ Location
    Mountain View, California
    Twitter
    @startreedata
    2,251 Twitter followers
    LinkedIn® Page
    www.linkedin.com
    116 employees on LinkedIn®
Product Description
How are these determined?Information
This description is provided by the seller.

StarTree Cloud is a fully-managed user-facing real-time analytics Database-as-a-Service (DBaaS) designed for OLAP at massive speed and scale. Based on Apache Pinot™, StarTree Cloud provides enterprise

Users
No information available
Industries
  • Computer Software
  • Financial Services
Market Segment
  • 38% Small-Business
  • 31% Mid-Market
StarTree 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
4
Fast Querying
4
Large Datasets
4
Performance
4
Big Data Handling
3
Cons
Learning Curve
4
Complex Setup
3
Difficult Setup
3
Insufficient Documentation
3
Poor Documentation
3
StarTree features and usability ratings that predict user satisfaction
8.3
Data Model
Average: 8.7
8.1
Data Types
Average: 8.5
8.8
Has the product been a good partner in doing business?
Average: 8.5
8.7
Integrated Cache
Average: 8.5
Seller Details
Seller
StarTree
Company Website
Year Founded
2019
HQ Location
Mountain View, California
Twitter
@startreedata
2,251 Twitter followers
LinkedIn® Page
www.linkedin.com
116 employees on LinkedIn®
  • Overview
    Expand/Collapse Overview
  • Product Description
    How are these determined?Information
    This description is provided by the seller.

    Apache Parquet is a columnar storage format available to any project in the Hadoop ecosystem, regardless of the choice of data processing framework, data model or programming language.

    Users
    No information available
    Industries
    • Computer Software
    • Information Technology and Services
    Market Segment
    • 48% Mid-Market
    • 30% Small-Business
  • User Satisfaction
    Expand/Collapse User Satisfaction
  • Apache Parquet features and usability ratings that predict user satisfaction
    9.0
    Data Model
    Average: 8.7
    8.8
    Data Types
    Average: 8.5
    7.5
    Has the product been a good partner in doing business?
    Average: 8.5
    8.6
    Integrated Cache
    Average: 8.5
  • Seller Details
    Expand/Collapse Seller Details
  • Seller Details
    Year Founded
    1999
    HQ Location
    Wakefield, MA
    Twitter
    @TheASF
    65,765 Twitter followers
    LinkedIn® Page
    www.linkedin.com
    2,345 employees on LinkedIn®
Product Description
How are these determined?Information
This description is provided by the seller.

Apache Parquet is a columnar storage format available to any project in the Hadoop ecosystem, regardless of the choice of data processing framework, data model or programming language.

Users
No information available
Industries
  • Computer Software
  • Information Technology and Services
Market Segment
  • 48% Mid-Market
  • 30% Small-Business
Apache Parquet features and usability ratings that predict user satisfaction
9.0
Data Model
Average: 8.7
8.8
Data Types
Average: 8.5
7.5
Has the product been a good partner in doing business?
Average: 8.5
8.6
Integrated Cache
Average: 8.5
Seller Details
Year Founded
1999
HQ Location
Wakefield, MA
Twitter
@TheASF
65,765 Twitter followers
LinkedIn® Page
www.linkedin.com
2,345 employees on LinkedIn®
(51)4.6 out of 5
Save to My Lists
Entry Level Price:Free
  • Overview
    Expand/Collapse Overview
  • Product Description
    How are these determined?Information
    This description is provided by the seller.

    We power the time-aware data-driven decisions that enable fast-moving organizations to realize the full potential of their AI investments and outpace competitors. Our technology delivers transforma

    Users
    No information available
    Industries
    • Financial Services
    • Banking
    Market Segment
    • 57% Enterprise
    • 25% Small-Business
  • Pros and Cons
    Expand/Collapse Pros and Cons
  • KX 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
    Speed
    11
    Performance
    9
    Tool Power
    7
    Efficiency
    6
    Fast Processing
    6
    Cons
    Learning Curve
    12
    Difficult Learning
    7
    Steep Learning Curve
    7
    Complexity
    2
    Expensive
    2
  • User Satisfaction
    Expand/Collapse User Satisfaction
  • KX features and usability ratings that predict user satisfaction
    8.8
    Data Model
    Average: 8.7
    9.5
    Data Types
    Average: 8.5
    9.0
    Has the product been a good partner in doing business?
    Average: 8.5
    9.1
    Integrated Cache
    Average: 8.5
  • Seller Details
    Expand/Collapse Seller Details
  • Seller Details
    Seller
    KX
    Year Founded
    1996
    HQ Location
    NY, USA
    Twitter
    @kxsystems
    4,210 Twitter followers
    LinkedIn® Page
    www.linkedin.com
    571 employees on LinkedIn®
Product Description
How are these determined?Information
This description is provided by the seller.

We power the time-aware data-driven decisions that enable fast-moving organizations to realize the full potential of their AI investments and outpace competitors. Our technology delivers transforma

Users
No information available
Industries
  • Financial Services
  • Banking
Market Segment
  • 57% Enterprise
  • 25% Small-Business
KX 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
Speed
11
Performance
9
Tool Power
7
Efficiency
6
Fast Processing
6
Cons
Learning Curve
12
Difficult Learning
7
Steep Learning Curve
7
Complexity
2
Expensive
2
KX features and usability ratings that predict user satisfaction
8.8
Data Model
Average: 8.7
9.5
Data Types
Average: 8.5
9.0
Has the product been a good partner in doing business?
Average: 8.5
9.1
Integrated Cache
Average: 8.5
Seller Details
Seller
KX
Year Founded
1996
HQ Location
NY, USA
Twitter
@kxsystems
4,210 Twitter followers
LinkedIn® Page
www.linkedin.com
571 employees on LinkedIn®
(114)4.2 out of 5
5th Easiest To Use in Columnar Databases software
Save to My Lists
  • Overview
    Expand/Collapse Overview
  • Product Description
    How are these determined?Information
    This description is provided by the seller.

    A scalable, distributed database that supports structured data storage for large tables. Use HBase when you need random, realtime read/write access to Big Data.

    Users
    • Software Engineer
    • Big Data Engineer
    Industries
    • Computer Software
    • Information Technology and Services
    Market Segment
    • 52% Enterprise
    • 27% Mid-Market
  • User Satisfaction
    Expand/Collapse User Satisfaction
  • Hbase features and usability ratings that predict user satisfaction
    8.1
    Data Model
    Average: 8.7
    7.2
    Data Types
    Average: 8.5
    8.0
    Has the product been a good partner in doing business?
    Average: 8.5
    7.0
    Integrated Cache
    Average: 8.5
  • Seller Details
    Expand/Collapse Seller Details
  • Seller Details
    Year Founded
    1999
    HQ Location
    Wakefield, MA
    Twitter
    @TheASF
    65,765 Twitter followers
    LinkedIn® Page
    www.linkedin.com
    2,345 employees on LinkedIn®
Product Description
How are these determined?Information
This description is provided by the seller.

A scalable, distributed database that supports structured data storage for large tables. Use HBase when you need random, realtime read/write access to Big Data.

Users
  • Software Engineer
  • Big Data Engineer
Industries
  • Computer Software
  • Information Technology and Services
Market Segment
  • 52% Enterprise
  • 27% Mid-Market
Hbase features and usability ratings that predict user satisfaction
8.1
Data Model
Average: 8.7
7.2
Data Types
Average: 8.5
8.0
Has the product been a good partner in doing business?
Average: 8.5
7.0
Integrated Cache
Average: 8.5
Seller Details
Year Founded
1999
HQ Location
Wakefield, MA
Twitter
@TheASF
65,765 Twitter followers
LinkedIn® Page
www.linkedin.com
2,345 employees on LinkedIn®
  • Overview
    Expand/Collapse Overview
  • Product Description
    How are these determined?Information
    This description is provided by the seller.

    Apache Kudu is a free and open source column-oriented data store of the Apache Hadoop ecosystem.

    Users
    No information available
    Industries
    No information available
    Market Segment
    • 54% Enterprise
    • 46% Mid-Market
  • User Satisfaction
    Expand/Collapse User Satisfaction
  • Apache Kudu features and usability ratings that predict user satisfaction
    8.7
    Data Model
    Average: 8.7
    6.3
    Data Types
    Average: 8.5
    8.3
    Has the product been a good partner in doing business?
    Average: 8.5
    7.3
    Integrated Cache
    Average: 8.5
  • Seller Details
    Expand/Collapse Seller Details
  • Seller Details
    Year Founded
    1999
    HQ Location
    Wakefield, MA
    Twitter
    @TheASF
    65,765 Twitter followers
    LinkedIn® Page
    www.linkedin.com
    2,345 employees on LinkedIn®
Product Description
How are these determined?Information
This description is provided by the seller.

Apache Kudu is a free and open source column-oriented data store of the Apache Hadoop ecosystem.

Users
No information available
Industries
No information available
Market Segment
  • 54% Enterprise
  • 46% Mid-Market
Apache Kudu features and usability ratings that predict user satisfaction
8.7
Data Model
Average: 8.7
6.3
Data Types
Average: 8.5
8.3
Has the product been a good partner in doing business?
Average: 8.5
7.3
Integrated Cache
Average: 8.5
Seller Details
Year Founded
1999
HQ Location
Wakefield, MA
Twitter
@TheASF
65,765 Twitter followers
LinkedIn® Page
www.linkedin.com
2,345 employees on LinkedIn®
  • Overview
    Expand/Collapse Overview
  • Product Description
    How are these determined?Information
    This description is provided by the seller.

    Apache Druid is an open source real-time analytics database. Druid combines ideas from OLAP/analytic databases, timeseries databases, and search systems to create a complete real-time analytics soluti

    Users
    No information available
    Industries
    • Computer Software
    Market Segment
    • 52% Enterprise
    • 29% Mid-Market
  • User Satisfaction
    Expand/Collapse User Satisfaction
  • Druid features and usability ratings that predict user satisfaction
    8.8
    Data Model
    Average: 8.7
    7.8
    Data Types
    Average: 8.5
    7.7
    Has the product been a good partner in doing business?
    Average: 8.5
    8.9
    Integrated Cache
    Average: 8.5
  • Seller Details
    Expand/Collapse Seller Details
  • Seller Details
    Seller
    Druid
    Year Founded
    1998
    HQ Location
    Rio de Janeiro, Rio de Janeiro
    Twitter
    @druid
    4 Twitter followers
    LinkedIn® Page
    www.linkedin.com
    79 employees on LinkedIn®
Product Description
How are these determined?Information
This description is provided by the seller.

Apache Druid is an open source real-time analytics database. Druid combines ideas from OLAP/analytic databases, timeseries databases, and search systems to create a complete real-time analytics soluti

Users
No information available
Industries
  • Computer Software
Market Segment
  • 52% Enterprise
  • 29% Mid-Market
Druid features and usability ratings that predict user satisfaction
8.8
Data Model
Average: 8.7
7.8
Data Types
Average: 8.5
7.7
Has the product been a good partner in doing business?
Average: 8.5
8.9
Integrated Cache
Average: 8.5
Seller Details
Seller
Druid
Year Founded
1998
HQ Location
Rio de Janeiro, Rio de Janeiro
Twitter
@druid
4 Twitter followers
LinkedIn® Page
www.linkedin.com
79 employees on LinkedIn®
  • Overview
    Expand/Collapse Overview
  • Product Description
    How are these determined?Information
    This description is provided by the seller.

    Apache ORC is a self-describing type-aware columnar file format for Hadoop workloads.

    Users
    No information available
    Industries
    No information available
    Market Segment
    • 45% Enterprise
    • 36% Mid-Market
  • User Satisfaction
    Expand/Collapse User Satisfaction
  • Apache ORC features and usability ratings that predict user satisfaction
    0.0
    No information available
    0.0
    No information available
    8.0
    Has the product been a good partner in doing business?
    Average: 8.5
    0.0
    No information available
  • Seller Details
    Expand/Collapse Seller Details
  • Seller Details
    Year Founded
    1999
    HQ Location
    Wakefield, MA
    Twitter
    @TheASF
    65,765 Twitter followers
    LinkedIn® Page
    www.linkedin.com
    2,345 employees on LinkedIn®
Product Description
How are these determined?Information
This description is provided by the seller.

Apache ORC is a self-describing type-aware columnar file format for Hadoop workloads.

Users
No information available
Industries
No information available
Market Segment
  • 45% Enterprise
  • 36% Mid-Market
Apache ORC features and usability ratings that predict user satisfaction
0.0
No information available
0.0
No information available
8.0
Has the product been a good partner in doing business?
Average: 8.5
0.0
No information available
Seller Details
Year Founded
1999
HQ Location
Wakefield, MA
Twitter
@TheASF
65,765 Twitter followers
LinkedIn® Page
www.linkedin.com
2,345 employees on LinkedIn®