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Apache Druid VS Materialize

Compare Apache Druid VS Materialize and see what are their differences

Apache Druid logo Apache Druid

Fast column-oriented distributed data store

Materialize logo Materialize

A Streaming Database for Real-Time Applications
  • Apache Druid Landing page
    Landing page //
    2023-10-07
  • Materialize Landing page
    Landing page //
    2023-08-27

Apache Druid videos

An introduction to Apache Druid

More videos:

  • Review - Building a Real-Time Analytics Stack with Apache Kafka and Apache Druid

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

Category Popularity

0-100% (relative to Apache Druid and Materialize)
Databases
46 46%
54% 54
Big Data
62 62%
38% 38
Database Tools
0 0%
100% 100
Data Dashboard
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 Apache Druid and Materialize

Apache Druid Reviews

Rockset, ClickHouse, Apache Druid, or Apache Pinot? Which is the best database for customer-facing analytics?
“When you're dealing with highly concurrent environments, you really need an architecture that’s designed for that CPU efficiency to get the most performance out of the smallest hardware footprint—which is another reason why folks like to use Apache Druid,” says David Wang, VP of Product and Corporate Marketing at Imply. (Imply offers Druid as a service.)
Source: embeddable.com
Apache Druid vs. Time-Series Databases
Druid is a real-time analytics database that not only incorporates architecture designs from TSDBs such as time-based partitioning and fast aggregation, but also includes ideas from search systems and data warehouses, making it a great fit for all types of event-driven data. Druid is fundamentally an OLAP engine at heart, albeit one designed for more modern, event-driven...
Source: imply.io

Materialize Reviews

We have no reviews of Materialize yet.
Be the first one to post

Social recommendations and mentions

Based on our record, Materialize should be more popular than Apache Druid. It has been mentiond 65 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.

Apache Druid mentions (9)

  • How to choose the right type of database
    Apache Druid: Focused on real-time analytics and interactive queries on large datasets. Druid is well-suited for high-performance applications in user-facing analytics, network monitoring, and business intelligence. - Source: dev.to / 3 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
  • Analysing Github Stars - Extracting and analyzing data from Github using Apache NiFi®, Apache Kafka® and Apache Druid®
    Spencer Kimball (now CEO at CockroachDB) wrote an interesting article on this topic in 2021 where they created spencerkimball/stargazers based on a Python script. So I started thinking: could I create a data pipeline using Nifi and Kafka (two OSS tools often used with Druid) to get the API data into Druid - and then use SQL to do the analytics? The answer was yes! And I have documented the outcome below. Here’s... - Source: dev.to / over 1 year ago
  • Apache Druid® - an enterprise architect's overview
    Apache Druid is part of the modern data architecture. It uses a special data format designed for analytical workloads, using extreme parallelisation to get data in and get data out. A shared-nothing, microservices architecture helps you to build highly-available, extreme scale analytics features into your applications. - Source: dev.to / over 1 year ago
  • Druids by Datadog
    Datadog's product is a bit too close to Apache Druid to have named their design system so similarly. From https://druid.apache.org/ : > Druid unlocks new types of queries and workflows for clickstream, APM, supply chain, network telemetry, digital marketing, risk/fraud, and many other types of data. Druid is purpose built for rapid, ad-hoc queries on both real-time and historical data. - Source: Hacker News / over 1 year ago
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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 / 7 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 / 12 months 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

What are some alternatives?

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

Apache Spark - Apache Spark is an engine for big data processing, with built-in modules for streaming, SQL, machine learning and graph processing.

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

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

Apache Kylin - OLAP Engine for Big Data

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

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