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Materialize VS ClickHouse

Compare Materialize VS ClickHouse and see what are their differences

Materialize logo Materialize

A Streaming Database for Real-Time Applications

ClickHouse logo ClickHouse

ClickHouse is an open-source column-oriented database management system that allows generating analytical data reports in real time.
  • Materialize Landing page
    Landing page //
    2023-08-27
  • ClickHouse Landing page
    Landing page //
    2019-06-18

Materialize videos

Bootstrap Vs. Materialize - Which One Should You Choose?

More videos:

  • Review - Materialize Review | Does it compete with Substance Painter?
  • Review - Why We Don't Need Bootstrap, Tailwind or Materialize

ClickHouse videos

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Category Popularity

0-100% (relative to Materialize and ClickHouse)
Databases
23 23%
77% 77
Database Tools
100 100%
0% 0
Relational Databases
12 12%
88% 88
Big Data
100 100%
0% 0

User comments

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Reviews

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

Materialize Reviews

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ClickHouse Reviews

Rockset, ClickHouse, Apache Druid, or Apache Pinot? Which is the best database for customer-facing analytics?
ClickHouse is an open-source, column-oriented, distributed, and OLAP database that’s very easy to set up and maintain. “Because it’s columnar, it’s the best architectural approach for aggregations and for ‘sort by’ on more than one column. It also means that group by’s are very fast. It’s distributed, replication is asynchronous, and it’s OLAP—which means it’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 it’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

Social recommendations and mentions

Materialize might be a bit more popular than ClickHouse. We know about 65 links to it since March 2021 and only 44 links to ClickHouse. 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.

Materialize mentions (65)

  • Choosing Between a Streaming Database and a Stream Processing Framework in Python
    To fully leverage the data is the new oil concept, companies require a special database designed to manage vast amounts of data instantly. This need has led to different database forms, including NoSQL databases, vector databases, time-series databases, graph databases, in-memory databases, and in-memory data grids. Recent years have seen the rise of cloud-based streaming databases such as RisingWave, Materialize,... - Source: dev.to / 4 months ago
  • We Built a Streaming SQL Engine
    Some recent solutions to this problem include Differential Dataflow and Materialize. It would be neat if postgres adopted something similar for live-updating materialized views. https://github.com/timelydataflow/differential-dataflow. - Source: Hacker News / 8 months ago
  • Ask HN: Who is hiring? (October 2023)
    Materialize | Full-Time | NYC Office or Remote | https://materialize.com Materialize is an Operational Data Warehouse: A cloud data warehouse with streaming internals, built for work that needs action on what’s happening right now. Keep the familiar SQL, keep the proven architecture of cloud warehouses but swap the decades-old batch computation model for an efficient incremental engine to get complex queries that... - Source: Hacker News / 8 months ago
  • Ask HN: Who is hiring? (June 2023)
    Materialize | EM (Compute), Senior PM | New York, New York | https://materialize.com/ You shouldn't have to throw away the database to build with fast-changing data. Keep the familiar SQL, keep the proven architecture of cloud warehouses, but swap the decades-old batch computation model for an efficient incremental engine to get complex queries that are always up-to-date. That is Materialize, the only true SQL... - Source: Hacker News / about 1 year ago
  • Ask HN: Who is hiring? (April 2023)
    Materialize | NY, NY | https://materialize.com/ The Cloud Database for Fast-Changing Data. We put a streaming engine in a database, so your team can build real-time data products without the cost, complexity, and development time of stream processing. Cloud team openings: https://grnh.se/0ad6ab6b4us Senior PM openings: https://grnh.se/415c267f4us. - Source: Hacker News / about 1 year ago
View more

ClickHouse mentions (44)

  • Simplified API Creation and Management: ClickHouse to APISIX Integration Without Code
    In the world of data management and web services, creating and managing APIs can often be a complex and time-consuming task. However, with the right tools, this process can be significantly simplified. In this article, we will explore how to create APIs for fetching data from ClickHouse tables without writing any code and manage these APIs using APISIX. ClickHouse, a fast and open-source columnar database... - Source: dev.to / 12 days ago
  • The 2024 Web Hosting Report
    For the third, examples here might be analytics plugins in specialized databases like Clickhouse, data-transformations in places like your ETL pipeline using Airflow or Fivetran, or special integrations in your authentication workflow with Auth0 hooks and rules. - Source: dev.to / 4 months ago
  • Choosing Between a Streaming Database and a Stream Processing Framework in Python
    Online analytical processing (OLAP) databases like Apache Druid, Apache Pinot, and ClickHouse shine in addressing user-initiated analytical queries. You might write a query to analyze historical data to find the most-clicked products over the past month efficiently using OLAP databases. When contrasting with streaming databases, they may not be optimized for incremental computation, leading to challenges in... - Source: dev.to / 4 months ago
  • Real-Time Data Enrichment and Analytics With RisingWave and ClickHouse
    To achieve seamless real-time data ingestion, transformation, and analytics, a powerful combination to explore is RisingWave and ClickHouse. RisingWave is a PostgreSQL-compatible database specifically designed for stream processing. It excels at ingesting real-time data streams, performing diverse transformations, and enabling instant querying of results. ClickHouse® is a high-performance, column-oriented SQL... - Source: dev.to / 5 months ago
  • Ask HN: Is there a Hacker News takeout to export my comments / upvotes, etc.?
    You can export the whole dataset as described here: https://github.com/ClickHouse/ClickHouse/issues/29693
        curl https://clickhouse.com/ | sh.
    - Source: Hacker News / 6 months ago
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What are some alternatives?

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

Apache Flink - Flink is a streaming dataflow engine that provides data distribution, communication, and fault tolerance for distributed computations.

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

Apache Kafka - Apache Kafka is an open-source message broker project developed by the Apache Software Foundation written in Scala.

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

OctoSQL - OctoSQL is a query tool that allows you to join, analyse and transform data from multiple databases and file formats using SQL. - cube2222/octosql

MySQL - The world's most popular open source database