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Based on our record, Materialize should be more popular than Apache Doris. It has been mentiond 74 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.
Did I miss in the article where OP reveals the magic database that actually does this? 3rd party solutions like https://readyset.io/ and https://materialize.com/ exist specifically because databases donโt actually have what we all want materialized views to be. - Source: Hacker News / about 1 year ago
This triggered some associations for me. Strongest was Cells[0], a library for Common Lisp CLOS. The earliest reference I can find is 2002[1], making it over 20 years old. Second is incremental view maintenance systems like Feldera[2] or Materialize[3]. These use sophisticated theories (z-sets and differential dataflow) to apply efficient updates over sets of data, which generalizes the case of single variables.... - Source: Hacker News / about 1 year ago
It's hard to write something that is both accessible and well-motivated. The best uses of category theory is when the morphisms are far more exotic than "regular functions". E.g. It would be nice to describe a circuit of live queries (like https://materialize.com/ stuff) with proper caching, joins, etc. Figuring this out is a bit of an open problem. Haskell's standard library's Monad and stuff are watered down to... - Source: Hacker News / over 1 year ago
> [...] `https://materialize.com/` to solve their memory issues [...] Disclaimer: I work at Materialize Recently there have been major improvements in Materialize's memory usage as well as using disk to swap out some data. I find it pretty easy to hook up to Postgres/MySQL/Kafka instances: https://materialize.com/blog/materialize-emulator/. - Source: Hacker News / almost 2 years ago
I agree. So many disparate solutions. The streaming sql primitives are by themselves good enough (e.g. `tumble`, `hop` or `session` windows), but the infrastructural components are always rough in real life use cases. Crossing fingers for solutions like `https://github.com/feldera/feldera` to solve their memory issues, or `https://clickhouse.com/docs/en/materialized-view` to solve reliable streaming consumption.... - Source: Hacker News / almost 2 years ago
The latest version of Apache Doris is now available for download. Visit doris.apache.org for detailed release notes and upgrade guides, and join the Doris community to explore, test, and share your feedback. - Source: dev.to / 10 months ago
This article provides an in-depth introduction to deep integration between Apache Doris and Apache Gravitino, building a modern lakehouse architecture based on Iceberg REST Catalog. Through Gravitino's unified metadata management and dynamic credential vending capabilities, we achieve efficient and secure access to Iceberg data stored on S3. - Source: dev.to / 11 months ago
Tagging onto our Real-Time Analytics support, we are now also supporting Apache Doris in this release. Doris is a high-performance, real-time analytical data warehouse that is known for its speed and ease of use. By adding a Doris catalog, engineers implementing Gravitino will now have more flexibility in their cataloging options for their analytical workloads. (Issue #1339, visit jdbc-doris-catalog for... - Source: dev.to / about 1 year ago
Like in many databases, Apache Doris shards data into partitions, and then a partition is further divided into buckets. Partitions are typically defined by time or other continuous values. This allows query engines to quickly locate the target data during queries by pruning irrelevant data ranges. - Source: dev.to / about 2 years ago
What makes a modern database system? The three key modules are query optimizer, execution engine, and storage engine. Among them, the role of execution engine to the DBMS is like the chef to a restaurant. This article focuses on the execution engine of the Apache Doris data warehouse, explaining the secret to its high performance. - Source: dev.to / about 2 years ago
Apache Flink - Flink is a streaming dataflow engine that provides data distribution, communication, and fault tolerance for distributed computations.
ClickHouse - ClickHouse is an open-source column-oriented database management system that allows generating analytical data reports in real time.
Apache Kafka - Apache Kafka is an open-source message broker project developed by the Apache Software Foundation written in Scala.
StarRocks - StarRocks offers the next generation of real-time SQL engines for enterprise-scale analytics. Learn how we make it easy to deliver real-time analytics.
RisingWave - RisingWave is a stream processing platform that utilizes SQL to enhance data analysis, offering improved insights on real-time data.
Apache Hive - Apache Hive data warehouse software facilitates querying and managing large datasets residing in distributed storage.