debezium
pinot
debezium | pinot | |
---|---|---|
80 | 15 | |
9,907 | 5,146 | |
1.3% | 1.0% | |
9.9 | 9.9 | |
3 days ago | 5 days ago | |
Java | Java | |
Apache License 2.0 | 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.
debezium
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Choosing Between a Streaming Database and a Stream Processing Framework in Python
They manage data in the application layer and your original data stays where it is. This way data consistency is no longer an issue as it was with streaming databases. You can use Change Data Capture (CDC) services like Debezium by directly connecting to your primary database, doing computational work, and saving the result back or sending real-time data to output streams.
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Generating Avro Schemas from Go types
Both of these articles mention a key player, Debezium. In fact, Debezium has had a place in the modern infrastructure. Let's use a diagram to understand why.
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debezium VS quix-streams - a user suggested alternative
2 projects | 7 Dec 2023
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How the heck do I validate records with this kind of data??
This might be overkill, but you could use an extra tool like https://debezium.io to capture logs about all creates, updates, and deletes in your table
- All the ways to capture changes in Postgres
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Managed Relational Databases with AWS RDS and Aurora
If you're considering a relational database for an event-driven architecture, check out Debezium. It lets you stream changes to relational databases, and subscribe to change events.
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Real-time Data Processing Pipeline With MongoDB, Kafka, Debezium And RisingWave
Debezium
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Postgresql to hadoop in real time
https://debezium.io/ comes to mind as an open source product, but there are a gazillion of these tools out there.
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ClickHouse Advanced Tutorial: Apply CDC from MySQL to ClickHouse
Contrary to what it sounds, it’s quite straightforward. The database changes are captured via Debezium and published as events on Apache Kafka. ClickHouse consumes those changes in partial order by Kafka Engine. Real-time and eventually consistent.
- Debezium: Stream Changes from Your Database
pinot
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How to choose the right type of database
Apache Pinot: Tailored for providing ultra-low latency analytics at scale. Apache Pinot is widely used for real-time analytical solutions where rapid data insights and decision-making are critical.
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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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🦿🛴Smarcity garbage reporting automation w/ ollama
Consume data into third party software (then let Open Search or Apache Spark or Apache Pinot) for analysis/datascience, GIS systems (so you can put reports on a map) or any ticket management system
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Apache Pinot 1.0
There is indeed Spark support for writing new data into Pinot (https://docs.pinot.apache.org/basics/data-import/batch-inges...) as well as to query it (https://github.com/apache/pinot/blob/master/pinot-connectors...).
This does not run inside the Pinot cluster - you can use standard Spark execution engine to run this ingestion. In addition, Pinot also supports an out of the box ingestion capability from batch sources using the Minion framework (https://docs.pinot.apache.org/basics/components/cluster/mini...) that does not need any external component (like Spark)
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Ask HN: Who is hiring? (June 2023)
StarTree | Onsite | Mountain View CA, Bangalore India | Site Lead, SRE, Software Engineers (Backend, Data Infrastructure, Platform), Staff Security Engineer Compliance and Governance
You can find all the job postings here: https://startree.ai/careers
My name is Peter Corless and I am the Director of Product Marketing at StarTree (https://startree.ai/). We are a Mountain View, California based company and aer now opening an engineering operation in Bangalore, India.
We make StarTree Cloud, an Online Analytical Processing (OLAP) database-as-a-service (DBaaS) for real-time, user-facing analytics, powered by Apache Pinot.
Apache Pinot (https://pinot.apache.org/) is a top-level Apache Software Foundation (ASF) project that came out of LinkedIn. A lot of the PMCs for the Apache Pinot project work at StarTree. It is also used at Uber, Stripe, DoorDash, Just Eat Takeaway (GrubHub), and a lot of other organizations.
Apache Pinot is known for its ability to provide high concurrency — hundreds of thousands of QPS — against petabytes of data. It uses the star-tree index to provide really fast responses measured in milliseconds.
We're past 100 employees and looking for people who want to help grow us to the next orders of magnitude.
Let me know if you have questions or interest.
- Seeking Feedback on Siddhi
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When you should use columnar databases and not Postgres, MySQL, or MongoDB
But then you realize there are other databases out there focused specifically on analytical use cases with lots of data and complex queries. Newcomers like ClickHouse, Pinot, and Druid (all open source) respond to a new class of problem: The need to develop applications using endpoints published on analytical queries that were previously confined only to the data warehouse and BI tools.
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Building Apache Pinot and Presto
Recently, we have been surveying some streaming database solutions and the primary target is Apache Pinot, which fits our needs from the description and is therefore the primary target.
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Reducing Database Loading
There are many mainstream streaming databases, and Apache Pinot is the most popular one recently.
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How-to-Guide: Contributing to Open Source
Apache Pinot
What are some alternatives?
maxwell - Maxwell's daemon, a mysql-to-json kafka producer
hudi - Upserts, Deletes And Incremental Processing on Big Data.
kafka-connect-bigquery - A Kafka Connect BigQuery sink connector
Trino - Official repository of Trino, the distributed SQL query engine for big data, formerly known as PrestoSQL (https://trino.io)
realtime - Broadcast, Presence, and Postgres Changes via WebSockets
Airflow - Apache Airflow - A platform to programmatically author, schedule, and monitor workflows
Apache Arrow - Apache Arrow is a multi-language toolbox for accelerated data interchange and in-memory processing
kafka-observability - An exploration of observability for Kafka client applications
RocksDB - A library that provides an embeddable, persistent key-value store for fast storage.
Apache Pulsar - Apache Pulsar - distributed pub-sub messaging system