ClickHouse
redpanda
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ClickHouse | redpanda | |
---|---|---|
208 | 69 | |
33,909 | 8,734 | |
1.9% | 2.8% | |
10.0 | 10.0 | |
7 days ago | 3 days ago | |
C++ | C++ | |
Apache License 2.0 | - |
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
ClickHouse
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We Built a 19 PiB Logging Platform with ClickHouse and Saved Millions
Yes, we are working on it! :) Taking some of the learnings from current experimental JSON Object datatype, we are now working on what will become the production-ready implementation. Details here: https://github.com/ClickHouse/ClickHouse/issues/54864
Variant datatype is already available as experimental in 24.1, Dynamic datatype is WIP (PR almost ready), and JSON datatype is next up. Check out the latest comment on that issue with how the Dynamic datatype will work: https://github.com/ClickHouse/ClickHouse/issues/54864#issuec...
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Build time is a collective responsibility
In our repository, I've set up a few hard limits: each translation unit cannot spend more than a certain amount of memory for compilation and a certain amount of CPU time, and the compiled binary has to be not larger than a certain size.
When these limits are reached, the CI stops working, and we have to remove the bloat: https://github.com/ClickHouse/ClickHouse/issues/61121
Although these limits are too generous as of today: for example, the maximum CPU time to compile a translation unit is set to 1000 seconds, and the memory limit is 5 GB, which is ridiculously high.
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Fair Benchmarking Considered Difficult (2018) [pdf]
I have a project dedicated to this topic: https://github.com/ClickHouse/ClickBench
It is important to explain the limitations of a benchmark, provide a methodology, and make it reproducible. It also has to be simple enough, otherwise it will not be realistic to include a large number of participants.
I'm also collecting all database benchmarks I could find: https://github.com/ClickHouse/ClickHouse/issues/22398
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How to choose the right type of database
ClickHouse: A fast open-source column-oriented database management system. ClickHouse is designed for real-time analytics on large datasets and excels in high-speed data insertion and querying, making it ideal for real-time monitoring and reporting.
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Writing UDF for Clickhouse using Golang
Today we're going to create an UDF (User-defined Function) in Golang that can be run inside Clickhouse query, this function will parse uuid v1 and return timestamp of it since Clickhouse doesn't have this function for now. Inspired from the python version with TabSeparated delimiter (since it's easiest to parse), UDF in Clickhouse will read line by line (each row is each line, and each text separated with tab is each column/cell value):
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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.
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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 maintaining the freshness of results. The query in the streaming database focuses on recent data, making it suitable for continuous monitoring. Using streaming databases, you can run queries like finding the top 10 sold products where the “top 10 product list” might change in real-time.
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Proton, a fast and lightweight alternative to Apache Flink
Proton is a lightweight streaming processing "add-on" for ClickHouse, and we are making these delta parts as standalone as possible. Meanwhile contributing back to the ClickHouse community can also help a lot.
Please check this PR from the proton team: https://github.com/ClickHouse/ClickHouse/pull/54870
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1 billion rows challenge in PostgreSQL and ClickHouse
curl https://clickhouse.com/ | sh
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We Executed a Critical Supply Chain Attack on PyTorch
But I continue to find garbage in some of our CI scripts.
Here is an example: https://github.com/ClickHouse/ClickHouse/pull/58794/files
The right way is to:
- always pin versions of all packages;
redpanda
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Choosing Between a Streaming Database and a Stream Processing Framework in Python
Stream-processing platforms such as Apache Kafka, Apache Pulsar, or Redpanda are specifically engineered to foster event-driven communication in a distributed system and they can be a great choice for developing loosely coupled applications. Stream processing platforms analyze data in motion, offering near-zero latency advantages. For example, consider an alert system for monitoring factory equipment. If a machine's temperature exceeds a certain threshold, a streaming platform can instantly trigger an alert and engineers do timely maintenance.
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The best WebAssembly runtime may be no runtime at all
Yeah it’s just the stack switching itself that is a handful of cycles, but there is not much more overhead for the full VM switch if you structure your embedding the right way. Code the code is source available if you want to peek at it!
https://github.com/redpanda-data/redpanda/blob/dev/src/v/was...
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redpanda VS quix-streams - a user suggested alternative
2 projects | 7 Dec 2023
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Kafka Is Dead, Long Live Kafka
that's a littlebit of a stretch. when you say "no shortage" - outside of redpanda what product exists that actually compete in all deployment modes?
it's a misconception that redpanda is simply a better kafka. the way to think about it is that is a new storage engine, from scratch, that speaks the kafka protocol. similar to all of the pgsql companies in a different space, i.e.: big table pgsql support is not a better postgres, fundamentally different tech. you can read the src and design here: https://github.com/redpanda-data/redpanda. or an electric car is not the same as a combustion engine, but only similar in that they are cars that take you from point a to point b.
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Real-time Data Processing Pipeline With MongoDB, Kafka, Debezium And RisingWave
Redpanda with the MongoDB Debezium Connector installed. We use Redpanda as a Kafka broker.
- Redpanda
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Flink CDC / alternatives
And Kafka + Kafka Connect has https://www.confluent.io/ https://aiven.io/ https://upstash.com/ (and not quite Kafka, but protocol-compatible, https://redpanda.com/)
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The Redpanda Project
There exists a C++ project which was created after Rust the language was available. github.com/redpanda-data/redpanda/
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SOCKS Proxy Server Architecture for High Concurrency
I suggest you check out io_uring and thread per core architecture. Applications like scylladb and redpanda have thread per core architecture and use io_uring for async io.
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Kafka alternatives
Redpanda
What are some alternatives?
loki - Like Prometheus, but for logs.
Apache Kafka - Mirror of Apache Kafka
duckdb - DuckDB is an in-process SQL OLAP Database Management System
Apache Pulsar - Apache Pulsar - distributed pub-sub messaging system
Trino - Official repository of Trino, the distributed SQL query engine for big data, formerly known as PrestoSQL (https://trino.io)
NATS - High-Performance server for NATS.io, the cloud and edge native messaging system.
VictoriaMetrics - VictoriaMetrics: fast, cost-effective monitoring solution and time series database
jetstream - JetStream Utilities
TimescaleDB - An open-source time-series SQL database optimized for fast ingest and complex queries. Packaged as a PostgreSQL extension.
RabbitMQ - Open source RabbitMQ: core server and tier 1 (built-in) plugins
arrow-datafusion - Apache Arrow DataFusion SQL Query Engine
kafkacat - Generic command line non-JVM Apache Kafka producer and consumer [Moved to: https://github.com/edenhill/kcat]