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ClickHouse VS Amazon Redshift

Compare ClickHouse VS Amazon Redshift and see what are their differences

ClickHouse logo ClickHouse

ClickHouse is an open-source column-oriented database management system that allows generating analytical data reports in real time.

Amazon Redshift logo Amazon Redshift

Learn about Amazon Redshift cloud data warehouse.
  • ClickHouse Landing page
    Landing page //
    2019-06-18
  • Amazon Redshift Landing page
    Landing page //
    2023-03-14

ClickHouse features and specs

  • High Performance
    ClickHouse is designed for fast processing of analytical queries, often performing significantly faster than traditional databases due to its columnar storage format and optimized query execution.
  • Scalability
    The system is built to handle extensive datasets by scaling horizontally through distributed cluster configurations, making it suitable for big data applications.
  • Real-time Data Ingestion
    ClickHouse supports real-time data ingestion and can immediately reflect changes in query results, which is valuable for use cases requiring instant data processing and analysis.
  • Cost Efficiency
    The open-source nature of ClickHouse makes it a cost-effective option, especially when compared to other commercial data warehouses.
  • SQL Compatibility
    ClickHouse features strong SQL support, which makes it easier for individuals with SQL expertise to transition and use the platform effectively.
  • Compression
    ClickHouse employs advanced compression algorithms that reduce storage requirements and improve query performance.

Possible disadvantages of ClickHouse

  • Complexity in Setup
    Setting up and managing ClickHouse, particularly in a distributed cluster environment, can be complex and require a higher level of expertise compared to some other database systems.
  • Limited Transaction Support
    ClickHouse is optimized for read-heavy operations and analytics but does not support full ACID transactions, which limits its use for certain transactional use cases.
  • Ecosystem and Tooling
    While the ecosystem is growing, ClickHouse still has fewer tools and third-party integrations compared to more mature databases, which can limit its utility in some environments.
  • Resource Intensive
    Running ClickHouse, especially for large datasets, can be resource-intensive, requiring significant memory and CPU resources.
  • Limited User Management
    The platform has relatively basic user management and security features, which may not meet the needs of enterprises with strict compliance and governance requirements.

Amazon Redshift features and specs

  • Scalability
    Amazon Redshift allows you to scale your data warehouse up or down easily based on your needs with just a few clicks or by using the API, providing flexibility to handle varying workloads.
  • Performance
    Redshift uses columnar storage, parallel processing, and efficient data compression techniques to deliver high performance for complex queries and large datasets.
  • Integration
    It seamlessly integrates with various AWS services like S3, DynamoDB, and QuickSight, making it easier to build a comprehensive data ecosystem.
  • Cost-effective
    Redshift offers a pay-as-you-go pricing model with no upfront costs, and you can save more with reserved instances, making it cost-effective for many businesses.
  • Security
    It includes features like encryption, Virtual Private Cloud (VPC), and compliance certifications (such as SOC 1, SOC 2, SOC 3, and more) to ensure data security and compliance.
  • Managed Service
    Amazon Redshift is a fully managed service, so it takes care of managing, monitoring, and scaling the infrastructure, allowing you to focus on your data and insights.

Possible disadvantages of Amazon Redshift

  • Complexity
    Although Redshift is powerful, it can be complex to set up, configure, and optimize for best performance, requiring knowledge and experience in data warehousing.
  • Cost for Unused Resources
    While Redshift is cost-effective for large-scale operations, costs can add up quickly if resources are not managed properly, especially with long-running clusters that are under-utilized.
  • Maintenance Windows
    Despite being a managed service, maintenance windows and updates can occasionally lead to downtime or performance degradation, impacting availability.
  • Data Transfer Costs
    Transferring data in and out of Redshift can incur additional costs, particularly if large volumes of data are involved, which can affect overall budget planning.
  • Vendor Lock-in
    Using Amazon Redshift ties you to the AWS ecosystem, which could be a disadvantage if you are considering a multi-cloud strategy or planning to switch providers in the future.

Analysis of ClickHouse

Overall verdict

  • ClickHouse is a powerful and capable columnar DBMS that offers excellent performance for analytical workloads. Its open-source nature allows for flexibility and community-driven improvements, making it a strong option for organizations needing a scalable analytics platform.

Why this product is good

  • ClickHouse is considered a good choice for many use cases due to its high performance in processing large volumes of data and its efficiency in executing complex analytical queries. It is designed to work well with large datasets and provides real-time query capabilities, making it ideal for applications like business intelligence, web analytics, and IoT.

Recommended for

  • Large-scale data analysis
  • Real-time analytics dashboards
  • Businesses needing high-speed query performance
  • Web analytics platforms
  • IoT data processing
  • Financial industry for quick data aggregation

Analysis of Amazon Redshift

Overall verdict

  • Amazon Redshift is generally considered a good solution for businesses seeking a robust, scalable, and cost-effective data warehousing service within the AWS cloud environment. However, its suitability may vary depending on specific organizational needs and workloads.

Why this product is good

  • Amazon Redshift is a popular data warehousing service within the AWS ecosystem, known for its scalability, ease of integration with other AWS services, and relatively low cost. It provides fast query performance for large datasets and offers features like columnar storage, parallel query execution, and advanced compression. These attributes make it an attractive choice for organizations looking to perform complex analytics and data processing tasks.

Recommended for

  • Organizations already utilizing AWS services and seeking seamless integration.
  • Businesses requiring scalable data warehousing at a competitive price.
  • Data-driven companies looking to perform fast, complex analytics on large datasets.
  • Teams needing flexible management options that can grow with their data storage needs.

ClickHouse videos

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Amazon Redshift videos

Getting Started with Amazon Redshift - AWS Online Tech Talks

More videos:

  • Review - Amazon Redshift Materialized Views
  • Tutorial - Amazon Redshift Tutorial | Amazon Redshift Architecture | AWS Tutorial For Beginners | Simplilearn

Category Popularity

0-100% (relative to ClickHouse and Amazon Redshift)
Databases
64 64%
36% 36
Relational Databases
100 100%
0% 0
Big Data
29 29%
71% 71
Data Warehousing
55 55%
45% 45

User comments

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Reviews

These are some of the external sources and on-site user reviews we've used to compare ClickHouse and Amazon Redshift

ClickHouse Reviews

Rockset, ClickHouse, Apache Druid, or Apache Pinot? Which is the best database for customer-facing analytics?
โ€ClickHouse is an open-source, column-oriented, distributed, and OLAP database thatโ€™s very easy to set up and maintain. โ€œBecause itโ€™s columnar, itโ€™s the best architectural approach for aggregations and for โ€˜sort byโ€™ on more than one column. It also means that group byโ€™s are very fast. Itโ€™s distributed, replication is asynchronous, and itโ€™s OLAPโ€”which means itโ€™s meant for...
Source: embeddable.com
ClickHouse vs TimescaleDB
Recently, TimescaleDB published a blog comparing ClickHouse & TimescaleDB using timescale/tsbs, a timeseries benchmarking framework. I have some experience with PostgreSQL and ClickHouse but never got the chance to play with TimescaleDB. Some of the claims about TimescaleDB made in their post are very bold, that made me even more curious. I thought itโ€™d be a great...
20+ MongoDB Alternatives You Should Know About
ClickHouse may be a great contender for moving analytical workloads from MongoDB. Much faster, and with JSON support and Nested Data Structures, it can be great choice for storing and analyzing document data.
Source: www.percona.com

Amazon Redshift Reviews

Data Warehouse Tools
No, SQL (Structured Query Language) is not a data warehouse itself. SQL is a programming language used for managing and querying data stored in relational database management systems (RDBMS) and data warehouses. Many data warehouse solutions, such as Peliqan, Amazon Redshift, and PostgreSQL, support SQL for querying and analyzing data within the data warehouse
Source: peliqan.io
Top 6 Cloud Data Warehouses in 2023
Coined in November 2021, Amazon Redshift was launched as a fully managed cloud data warehouse that can handle petabyte-scale data. While it was not the first cloud data warehouse, it became the first to proliferate in the market share after a large-scale adoption. Redshift uses SQL dialect based on PostgreSQL, which is well-known by many analysts globally, and its...
Source: geekflare.com
Top 5 Cloud Data Warehouses in 2023
Jan 11, 2023 The 5 best cloud data warehouse solutions in 2023Google BigQuerySource: https://cloud.google.com/bigqueryBest for:Top features:Pros:Cons:Pricing:SnowflakeBest for:Top features:Pros:Cons:Pricing:Amazon RedshiftSource: https://aws.amazon.com/redshift/Best for:Top features:Pros:Cons:Pricing:FireboltSource: https://www.firebolt.io/Best for:Top...
Top 5 BigQuery Alternatives: A Challenge of Complexity
As the most proven tool in this category, Amazon Redshift is a fully managed cloud-based data warehouse used to collect and store data. Like BigQuery, Redshift seamlessly integrates with multiple products and ETL services.
Source: blog.panoply.io

Social recommendations and mentions

Based on our record, ClickHouse should be more popular than Amazon Redshift. It has been mentiond 60 times since March 2021. We are tracking product recommendations and mentions on various public social media platforms and blogs. They can help you identify which product is more popular and what people think of it.

ClickHouse mentions (60)

  • Setting up ClickHouse on macOS and Testing with Node.js
    ClickHouse is an open-source columnar database built for high-performance analytical queries. This guide shows how I installed ClickHouse on macOS, ran it in the background using a lightweight nohup setup that stores logs and PID in hidden user folders, and tested it with a minimal Node.js + TypeScript example using @clickhouse/client. - Source: dev.to / 15 days ago
  • From Go to Rust: Supercharging Our ClickHouse UDFs with Alloy
    At Agnostic, we build open-source infrastructure for collaborative blockchain data platforms. One of our flagship tools is clickhouse-evm, a suite of high-performance User Defined Functions (UDFs) that brings native Ethereum decoding and querying capabilities directly into ClickHouse. - Source: dev.to / 3 months ago
  • ๐Ÿง  From Hive and Elastic to ClickHouse: What Surprised Me
    Over the past few weeks, Iโ€™ve been diving into ClickHouse โ€” and itโ€™s been full of surprises. - Source: dev.to / 3 months ago
  • Cross-Compiling Haskell under NixOS with Docker
    I attended the AWS Summit 2025 in Singapore. I enjoyed the event. There were booths from various companies which I found interesting, such as GitLab and ClickHouse. More importantly, I got to meet very interesting people. - Source: dev.to / 4 months ago
  • How to Build a Streaming Deduplication Pipeline with Kafka, GlassFlow, and ClickHouse
    ClickHouse: A fast columnar database. It will be our final destination for clean data. And, for simplicity in this tutorial, we'll cleverly use it as our "memory" or state store to remember which events we've already seen recently. - Source: dev.to / 5 months ago
View more

Amazon Redshift mentions (29)

  • How to Pitch Your Boss to Adopt Apache Iceberg?
    If your team is managing large volumes of historical data using platforms like Snowflake, Amazon Redshift, or Google BigQuery, youโ€™ve probably noticed a shift happening in the data engineering world. A new generation of data infrastructure is forming โ€” one that prioritizes openness, interoperability, and cost-efficiency. At the center of that shift is Apache Iceberg. - Source: dev.to / 6 months ago
  • Everyone Uses Postgresโ€ฆ But Why?
    Postgres can be easily adapted to build highly tailored solutions. For instance, Amazon Redshift can be considered a highly scalable fork of Postgres. Itโ€™s a distributed database focusing on OLAP workloads that you can deploy in AWS. - Source: dev.to / 11 months ago
  • From ETL and ELT to Reverse ETL
    With the transition from ETL to ELT, data warehouses have ascended to the role of data custodians, centralizing customer data collected from fragmented systems. This pivotal shift has been enabled by a suite of powerful tools: Fivetran and Airbyte streamline the extraction and loading, DBT handles the transformation, and robust warehousing solutions like Snowflake and Redshift store the data. While traditionally... - Source: dev.to / about 1 year ago
  • Choosing Between a Streaming Database and a Stream Processing Framework in Python
    They differ from conventional analytic databases like Snowflake, Redshift, BigQuery, and Oracle in several ways. Conventional databases are batch-oriented, loading data in defined windows like hourly, daily, weekly, and so on. While loading data, conventional databases lock the tables, making the newly loaded data unavailable until the batch load is fully completed. Streaming databases continuously receive new... - Source: dev.to / over 1 year ago
  • Choosing the Right AWS Database: A Guide for Modern Applications
    Data warehousing is the process of storing and analyzing large volumes of data for business intelligence and analytics purposes. AWS offers a fully managed data warehousing service called Amazon Redshift that can handle petabyte-scale data warehouses with ease. - Source: dev.to / almost 2 years ago
View more

What are some alternatives?

When comparing ClickHouse and Amazon Redshift, you can also consider the following products

MySQL - The world's most popular open source database

Google BigQuery - A fully managed data warehouse for large-scale data analytics.

Apache Doris - Apache Doris is an open-source real-time data warehouse for big data analytics.

Microsoft SQL Server - Microsoft Azure is an open, flexible, enterprise-grade cloud computing platform. Move faster, do more, and save money with IaaS + PaaS. Try for FREE.

PostgreSQL - PostgreSQL is a powerful, open source object-relational database system.

Snowflake - Snowflake is the only data platform built for the cloud for all your data & all your users. Learn more about our purpose-built SQL cloud data warehouse.