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# Apache Parquet vs ClickHouse Comparison - What are their main differences?

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Apache ParquetClickHouse[+ Add Product](#)

Reviews

**Apache Parquet** [

4.3/5(27)

](https://www.g2.com/products/apache-parquet/reviews#reviews)

**ClickHouse** [

4.5/5(24)

](https://www.g2.com/products/clickhouse/reviews#reviews)

Pricing

**Apache Parquet**
No pricing available

**ClickHouse**
 **Starting at $1.00** Per Month · ClickHouse Pricing

**Pricing Insights**
from reviews

Pros & Cons

**Apache Parquet**
Not enough data

**ClickHouse**
[
Easy Integrations (2)
](https://www.g2.com/products/clickhouse/reviews?filters%5Bsentiment_snippet%5D=1173116&qs=pros-and-cons#reviews)[
Integrations (2)
](https://www.g2.com/products/clickhouse/reviews?filters%5Bsentiment_snippet%5D=1173076&qs=pros-and-cons#reviews)[
Beginner Unfriendliness (1)
](https://www.g2.com/products/clickhouse/reviews?filters%5Bsentiment_snippet%5D=2359804&qs=pros-and-cons#reviews)[
Complex Usage (1)
](https://www.g2.com/products/clickhouse/reviews?filters%5Bsentiment_snippet%5D=2359921&qs=pros-and-cons#reviews)

Integrations

**Apache Parquet**
Not enough data

**ClickHouse**
[

 ![Product Avatar Image](https://images.g2crowd.com/uploads/product/image/large_detail/large_detail_b2d8d8b72a69d8fa5e1dd08504fd51fd/openlit.jpg "Product Avatar Image")

Openlit

](https://www.g2.com/products/openlit/reviews)[

 ![Product Avatar Image](https://images.g2crowd.com/uploads/product/image/large_detail/large_detail_3f2f6ba29e17c729d8403ba2d10d045e/vector-by-datadog.png "Product Avatar Image")

Vector By Datadog

](https://www.g2.com/products/vector-by-datadog/reviews)[
View all
](https://www.g2.com/products/clickhouse/integrations)

Screenshots

**Apache Parquet**
No screenshot available

**ClickHouse**
 ![ClickHouse screenshot](https://images.g2crowd.com/cdn-cgi/image/width=600,height=600,fit=scale-down,format=auto,onerror=redirect,/https://images.g2crowd.com/uploads/attachment/file/1384096/Screenshot-2024-06-21-at-7.45.48-AM.png)

Ratings

Meets Requirements

**Apache Parquet**

8.5

8.521

**ClickHouse**

9.2

9.215

Ease of Use

**Apache Parquet**

7.7

7.722

**ClickHouse**

8.9

8.915

Ease of Setup

**Apache Parquet**

7.2

7.29

**ClickHouse**

9.1

9.111

Ease of Admin

**Apache Parquet**

7.6

7.69

**ClickHouse**

7.5

7.56

Quality of Support

**Apache Parquet**

8.1

8.119

**ClickHouse**

8.5

8.513

Has the product been a good partner in doing business?

**Apache Parquet**

7.5

7.58

**ClickHouse**
Not enough data

Product Direction (% positive)

**Apache Parquet**

8.6

8.625

**ClickHouse**

10.0

10.014

Features

Columnar Databases[Hide 12 FeaturesShow 12 Features](javascript:void(0);)

8.4

16

8.5

9

Storage

Data Model

9.0

13

9.2(won by 0.2)

6

Data Types

8.8

12

9.0(won by 0.2)

7

Availability

Auto Recovery

8.2(won by 0.4)

12

7.8

6

Data Replication

8.8(won by 0.5)

12

 (There is a greater than 0.5 difference between this product's rating and its competitors)

8.3

6

Auto Sharding

7.4(won by default)

14

Feature Not Available

Performance

Integrated Cache

8.6(won by 0.5)

12

 (There is a greater than 0.5 difference between this product's rating and its competitors)

8.1

6

Security

Role-Based Authorization

9.0(tied score)

12

9.0(tied score)

5

Encryption

8.6(won by 0.3)

12

8.3

5

Authentication

7.9(won by default)

12

Not enough data

Audit Logs

7.9(won by default)

12

Not enough data

Support

Multi-Model

8.9(won by default)

12

Not enough data

Operating Systems

8.2(won by default)

12

Not enough data

Database Management Systems (DBMS)[Hide 48 FeaturesShow 48 Features](javascript:void(0);)

Not enough data

8.9

7

Management

Data dictionary

Not enough data

9.4(won by default)

6

Data Replication

Not enough data

7.9(won by default)

7

Query Language

Not enough data

9.3(won by default)

7

Data Modeling

Not enough data

9.4(won by default)

6

Performance Analysis

Not enough data

10.0(won by default)

5

Data Synchronization

Not enough data

Not enough data

Real-Time Data

Not enough data

Not enough data

Data Storage Management

Not enough data

Not enough data

Maintenance

Data Migration

Not enough data

8.8(won by default)

7

Backup and Recovery

Not enough data

7.8(won by default)

6

Multi-User Environment

Not enough data

Not enough data

Automatic Backup

Not enough data

Not enough data

Database Conversion

Not enough data

Not enough data

Security

Data Encryption

Not enough data

Not enough data

User Access Control

Not enough data

Not enough data

Mobile Access

Not enough data

Not enough data

Additional Functionality

Workflow Management

Not enough data

Not enough data

Third-Party Integrations

Not enough data

Not enough data

Data Extraction

Not enough data

Not enough data

Relational Database Management

Not enough data

Not enough data

SSL Security

Not enough data

Not enough data

API

Not enough data

Not enough data

Data Connectors

Not enough data

Not enough data

Search/Filter

Not enough data

Not enough data

Reporting & Statistics

Not enough data

Not enough data

Customizable Templates

Not enough data

Not enough data

AI Copilot

Not enough data

Not enough data

Full Text Search

Not enough data

Not enough data

Data Virtualization

Not enough data

Not enough data

Data Import/Export

Not enough data

Not enough data

Generative AI

Not enough data

Not enough data

Drag & Drop

Not enough data

Not enough data

Customizable Fields

Not enough data

Not enough data

Authentication

Not enough data

Not enough data

Data Visualization

Not enough data

Not enough data

Secure Data Storage

Not enough data

Not enough data

Activity Dashboard

Not enough data

Not enough data

Data Mapping

Not enough data

Not enough data

Multiple Programming Languages Supported

Not enough data

Not enough data

Data Capture and Transfer

Not enough data

Not enough data

User Management

Not enough data

Not enough data

NOSQL Database Management

Not enough data

Not enough data

Access Controls/Permissions

Not enough data

Not enough data

Calendar Management

Not enough data

Not enough data

Real-Time Monitoring

Not enough data

Not enough data

Document Storage

Not enough data

Not enough data

Audit Management

Not enough data

Not enough data

Charting

Not enough data

Not enough data

Relational Databases[Hide 24 FeaturesShow 24 Features](javascript:void(0);)

Not enough data

9.0

6

Management 

Query Language

Not enough data

9.3(won by default)

5

Data Schema

Not enough data

Not enough data

ACID - Complaint

Not enough data

Feature Not Available

Data Replication

Not enough data

Not enough data

Support 

Text Search

Not enough data

Not enough data

Data Types

Not enough data

Not enough data

Languages

Not enough data

Not enough data

Operating Systems

Not enough data

Not enough data

Security

Database Locking

Not enough data

Feature Not Available

Access Control

Not enough data

Not enough data

Encryption

Not enough data

Not enough data

Authentication

Not enough data

Not enough data

Performance 

Disaster Recovery

Not enough data

Not enough data

Data Concurrency

Not enough data

Not enough data

Workload Management

Not enough data

Not enough data

Advanced Indexing

Not enough data

Not enough data

Query Optimizer

Not enough data

Not enough data

Database Features

Storage

Not enough data

9.0(won by default)

5

Availability

Not enough data

9.3(won by default)

5

Stability

Not enough data

9.0(won by default)

5

Scalability

Not enough data

9.0(won by default)

5

Query Language

Not enough data

8.7(won by default)

5

Security

Not enough data

Not enough data

Data Manipulation

Not enough data

Not enough data

Real-time Analytic Database[Hide 10 FeaturesShow 10 Features](javascript:void(0);)

Not enough data

10.0

6

Query latency

Lower query latency

Not enough data

10.0(won by default)

5

Continuous queries

Not enough data

Not enough data

Data latency

Lower data latency

Not enough data

Not enough data

Data pipeline performance

Not enough data

Not enough data

Connectors

Faster ingestion

Not enough data

Not enough data

Built-in connectors

Not enough data

Not enough data

Scale

Linearly scalable database

Not enough data

Not enough data

Storage management

Not enough data

Not enough data

Architecture

Data security

Not enough data

Not enough data

Lockless architecture

Not enough data

Not enough data

User Insights

Reviewers' Company Size

[![Apache Parquet](https://images.g2crowd.com/uploads/product/image/thumb_square/thumb_square_b350900e1c1cde239f398145fc13d8f3/apache-parquet.jpg "Apache Parquet")](https://www.g2.com/products/apache-parquet/reviews)

Apache Parquet

Small-Business(50 or fewer emp.)

30.8%

Mid-Market(51-1000 emp.)

50.0%

Enterprise(\> 1000 emp.)

19.2%

[![ClickHouse](https://images.g2crowd.com/uploads/product/hd_favicon/1085fc1aec988cc21861ba894db51044/clickhouse.svg "ClickHouse")](https://www.g2.com/products/clickhouse/reviews)

ClickHouse

Small-Business(50 or fewer emp.)

56.5%

Mid-Market(51-1000 emp.)

34.8%

Enterprise(\> 1000 emp.)

8.7%

Small-Business

(50 or fewer emp.)

30.8%

56.5%

Mid-Market

(51-1000 emp.)

50.0%

34.8%

Enterprise

(\> 1000 emp.)

19.2%

8.7%

Reviewers' Industry

[![Apache Parquet](https://images.g2crowd.com/uploads/product/image/thumb_square/thumb_square_b350900e1c1cde239f398145fc13d8f3/apache-parquet.jpg "Apache Parquet")](https://www.g2.com/products/apache-parquet/reviews)
Apache Parquet

Computer Software

38.5%

Information Technology and Services

19.2%

Financial Services

7.7%

Education Management

7.7%

Hospital & Health Care

3.8%

Other

23.1%

[![ClickHouse](https://images.g2crowd.com/uploads/product/hd_favicon/1085fc1aec988cc21861ba894db51044/clickhouse.svg "ClickHouse")](https://www.g2.com/products/clickhouse/reviews)
ClickHouse

Information Technology and Services

30.4%

Computer Software

26.1%

Wholesale

4.3%

Telecommunications

4.3%

Marketing and Advertising

4.3%

Other

30.4%

FAQs

## Apache Parquet vs ClickHouse FAQs

Generated using AI

Last updated: August 15, 2026

### What is the difference between Apache Parquet vs ClickHouse?

ClickHouse stands out for its higher G2 rating, superior Ease of Setup, and real-time analytics strengths, while Apache Parquet is favored for efficient storage and compatibility with big data frameworks.

| [Apache Parquet](https://www.g2.com/products/apache-parquet/reviews) | [ClickHouse](https://www.g2.com/products/clickhouse/reviews) |
| --- | --- |
| 4.3/5 (27 reviews) | 4.5/5 (23 reviews) |
| — | — |
| 7.2 | 9.0 |
| 8.1 | 8.3 |
| Efficient storage and compatibility with big data frameworks | Real-time analytics and fast query performance |

### How do the pricing models of Apache Parquet and ClickHouse compare?

ClickHouse is rated higher for value, with reviewers expressing greater satisfaction with its price-to-performance ratio compared to Apache Parquet.

- **Apache Parquet:** Reviewers highlight its open-source nature and efficient storage, but note a steeper learning curve and complexity for smaller-scale use cases.
- **ClickHouse:** Reviewers consistently praise its performance and cost-effectiveness, mentioning the ability to handle large datasets on modest hardware and rapid query speeds as key value drivers.

### What are the best alternatives to Apache Parquet and ClickHouse?

The top three alternatives to Apache Parquet and ClickHouse are BigQuery, Azure Cosmos DB, and MySQL.

| Product | G2 Rating (reviews) | Largest Segment | Pricing Insight | Top Reviewer-Cited Strength |
| --- | --- | --- | --- | --- |
| [Apache Parquet](https://www.g2.com/products/apache-parquet/reviews) | 4.3/5 (27 reviews) | — | Open-source, efficient storage | Efficient storage and compatibility with big data frameworks |
| [ClickHouse](https://www.g2.com/products/clickhouse/reviews) | 4.5/5 (23 reviews) | — | Cost-effective for large-scale analytics | Real-time analytics and fast query performance |
| [BigQuery](https://www.g2.com/products/google-cloud-bigquery/reviews) | 4.5/5 (1224 reviews) | Enterprise | — | Scalability and integration with Google Cloud ecosystem |
| [Azure Cosmos DB](https://www.g2.com/products/azure-cosmos-db/reviews) | 4.2/5 (68 reviews) | Enterprise | — | Global distribution and multi-model support |
| [MySQL](https://www.g2.com/products/mysql/reviews) | 4.4/5 (1682 reviews) | Small-Business | — | Reliability and widespread adoption |

### Which Columnar Databases features should I prioritize when comparing Apache Parquet and ClickHouse?

Buyers should prioritize Storage, Ease of Setup, Query Performance, Integration Capabilities, and Real-Time Analytics when comparing Apache Parquet and ClickHouse.

- **Storage:** Apache Parquet is frequently praised for efficient storage and compression; ClickHouse is noted for optimized storage and fast data retrieval.
- **Ease of Setup:** ClickHouse scores 9.0, while Apache Parquet scores 7.2, indicating a smoother setup experience for ClickHouse.
- **Query Performance:** ClickHouse is highlighted for real-time analytics and fast query speeds; Apache Parquet is recognized for efficient analytical queries but is more batch-oriented.
- **Integration Capabilities:** Apache Parquet is compatible with a wide range of big data frameworks; ClickHouse is noted for integrations with analytics tools like Grafana and dbt.
- **Real-Time Analytics:** ClickHouse is favored for real-time data processing, while Apache Parquet is primarily used for batch processing.

### What are the pros and cons of Apache Parquet vs ClickHouse?

ClickHouse's headline strength is real-time analytics and fast query performance, while Apache Parquet excels in efficient storage and compatibility with big data frameworks.

- **Apache Parquet strengths:** Efficient columnar storage, high compression, compatibility with Apache Spark, Hive, and Impala, and schema evolution support.
- **Apache Parquet trade-offs:** Steep learning curve, complexity for small-scale data, slower write performance, and limited real-time data support.
- **ClickHouse strengths:** Real-time analytics, fast query execution, high performance on large datasets, easy integration with analytics tools, and cost-effective scaling.
- **ClickHouse trade-offs:** Initial learning curve, advanced query optimization requires expertise, and some stability concerns for production systems.

### Is Apache Parquet or ClickHouse better for small businesses?

MySQL is the top-ranked alternative for small businesses, but between Apache Parquet and ClickHouse, ClickHouse is better suited for small-business needs due to its higher Ease of Use and Setup scores.

- **Apache Parquet:** No dominant small-business segment; reviewers note complexity and a steeper learning curve for smaller-scale deployments.
- **ClickHouse:** No dominant small-business segment; reviewers highlight ease of use, rapid setup, and strong performance even on modest hardware, making it attractive for small-business analytics.

### Which Columnar Databases platform has better integrations?

ClickHouse is favored for integrations, with reviewers citing smooth connections to analytics tools and dashboards.

- **Apache Parquet:** Reviewers mention compatibility with Apache Spark, Hive, and Impala for data processing pipelines.
- **ClickHouse:** Reviewers highlight integrations with Grafana and dbt, as well as easy connections to analytics dashboards.

### How do Apache Parquet and ClickHouse compare on customer support?

ClickHouse and Apache Parquet are rated in near-parity on Quality of Support, with ClickHouse at 8.3 and Apache Parquet at 8.1.

- **Apache Parquet:** Reviewers describe support as responsive, with documentation and community resources aiding troubleshooting.
- **ClickHouse:** Reviewers note strong community and documentation, with support experiences described as reliable and helpful for resolving issues.

### Which is easier to implement, Apache Parquet or ClickHouse?

ClickHouse is easier to implement, with a 1.8-point higher Ease of Setup score (9.0 vs 7.2) compared to Apache Parquet.

- **Apache Parquet:** Reviewers mention a steeper learning curve and more complex setup, especially for those new to columnar formats or big data frameworks.
- **ClickHouse:** Reviewers consistently highlight straightforward setup, rapid deployment, and ease of use, even for complex analytics workloads.

### Which product has better Storage?

ClickHouse is favored for Storage, with reviewers citing both efficient storage and rapid data retrieval for large datasets.

- **Apache Parquet:** Reviewers praise its efficient columnar storage, high compression, and ability to reduce storage requirements by up to one third for big data analytics.
- **ClickHouse:** Reviewers highlight optimized storage, fast query performance, and the ability to handle billions of records efficiently, with strong mention of storage savings and compression algorithms.

Alternatives

**Apache Parquet Alternatives**

 ![Azure Cosmos DB](https://images.g2crowd.com/uploads/product/image/thumb_square/thumb_square_f176b4154a751d10150daa67a57b7dc5/azure-cosmos-db.jpg "Azure Cosmos DB")

[
Azure Cosmos DB
](/products/azure-cosmos-db/reviews)

 ![Snowflake](https://images.g2crowd.com/uploads/product/hd_favicon/1544409170/snowflake.svg "Snowflake")

[
Snowflake
](/products/snowflake/reviews)

 ![Google Cloud BigQuery](https://images.g2crowd.com/uploads/product/hd_favicon/875b8a68eca98ce3458f26e9dd34cdf9/google-cloud-bigquery.svg "Google Cloud BigQuery")

[
BigQuery
](/products/google-cloud-bigquery/reviews)

 ![MariaDB](https://images.g2crowd.com/uploads/product/hd_favicon/1546027546/mariadb.svg "MariaDB")

[
MariaDB
](/products/mariadb/reviews)

**ClickHouse Alternatives**

 ![Google Cloud BigQuery](https://images.g2crowd.com/uploads/product/hd_favicon/875b8a68eca98ce3458f26e9dd34cdf9/google-cloud-bigquery.svg "Google Cloud BigQuery")

[
BigQuery
](/products/google-cloud-bigquery/reviews)

 ![MySQL](https://images.g2crowd.com/uploads/product/image/thumb_square/thumb_square_240340edca859994ec71e4490aa20022/mysql.png "MySQL")

[
MySQL
](/products/mysql/reviews)

 ![Snowflake](https://images.g2crowd.com/uploads/product/hd_favicon/1544409170/snowflake.svg "Snowflake")

[
Snowflake
](/products/snowflake/reviews)

 ![Microsoft SQL Server](https://images.g2crowd.com/uploads/product/hd_favicon/a8a99a96fda235658139f710592f8a53/microsoft-sql-server.svg "Microsoft SQL Server")

[
MS SQL
](/products/microsoft-sql-server/reviews)

## Apache Parquet vs ClickHouse

- Reviewers felt that ClickHouse meets the needs of their business better than Apache Parquet.
- When comparing quality of ongoing product support, reviewers felt that ClickHouse is the preferred option.
- For feature updates and roadmaps, our reviewers preferred the direction of ClickHouse over Apache Parquet.