python-fake-data-producer-for-apache-kafka
Metabase
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python-fake-data-producer-for-apache-kafka | Metabase | |
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32 | 67 | |
74 | 36,417 | |
- | 1.4% | |
4.5 | 10.0 | |
8 months ago | 1 day ago | |
Python | Clojure | |
Apache License 2.0 | GNU General Public License v3.0 or later |
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python-fake-data-producer-for-apache-kafka
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ElephantSQL Is Shutting Down
I had good experience with Aiven in the past, we needed something located in the EU: https://aiven.io/
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Crossplane: Streamline your infrastructure provisioning & management
Access to Aiven
- Google Cloud Spanner is now half the cost of Amazon DynamoDB
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Scale up: a MySQL bug story, or why Aiven works
One of the hardest questions we answer for our large enterprise customers is why they should choose Aiven instead of managing their own database and streaming services. It can seem counterintuitive that paying extra for a managed service can save you money. However, when we factor in economies of scale - particularly in regards to access to specialized knowledge and tooling - the case for managed services becomes clear. This was certainly the case for some of our MySQL clients earlier this year, where their investments in Aiven paid off in the form of a quietly managed bug fix.
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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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What are your favorite tools or components in the Kafka ecosystem?
Fake data utility - https://github.com/aiven/python-fake-data-producer-for-apache-kafka
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Do we have such a thing as Postgres Atlas?
For PostgreSQL, similar offerings are: * Google Cloud SQL * AWS RDS * Digital Ocean Postgres * Azure Database for Postgres * Aiven, Instaclustr etc
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Good database solution
Aiven - https://aiven.io/
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Why are we paying these folks - a tale of DevRel
Majority of companies layer DevRel on top of marketing as a sort of afterthought, and that’s usually a recipe for failure. All four co-founders at Aiven (the company where I work at) have been long-time open-source maintainers/contributors and highly value the work of DevRel. Similar examples can be seen at HashiCorp, where co-founder Armon Dadgar has been doing DevRel on the whiteboard since the early days of the company. Technical founders know the value of DevRel and know when to form a DevRel team. This is very different from bringing your first DevRel hire onboard and making them convince the leadership why the company needs DevRel in the first place. If your developer advocate needs to explain to the technical leadership the need for DevRel, that's a red flag for that individual and the company.
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Hetzner continues its growth in the US with a new location
I wonder when Aiven https://aiven.io/ (or something similar) will start supporting hetzner.
Metabase
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HackTheBox - Writeup Analytics
Remote Code Execution via H2
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Blazer: Business Intelligence Made Simple
We've used it for about a year - Blazer is okay if you need a quick SQL query console, but we found it lacking as an actual business intelligence tool. The support for graphs and dashboards is limited, for graphs it requires you to structure the query in an exact way as you can see in the Blazer readme.
After some research on available alternatives that don't break the bank, we decided to deploy a self-hosted instance of Metabase[0]. This took only a few minutes to set up using their Docker image[1] and it has much better graphing capabilities and you can easily put a custom layout together for dashboards. Upgrading is similarly easy (just redeploy). Also easy to configure: data sources, hiding or changing the data type of a column, G Suite sign-in for our domain. Highly recommend it if you need anything more than Blazer's table output.
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Is Tableau Dead?
I've never used Tableau, but heard a lot of hate about it. However, in my previous role, we were big fans of Metabase (https://metabase.com). You can also self-host it, which was a huge win for us.
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My mental model of Clojure transducers
It seems folks want a working example. Here's one in prod:
Metabase is a BI tool, backend written mostly in Clojure. Like basically all BI tools they have this intermediate representation language thing so you write the same thing in "MBQL (metabase query language)" and it theoretically becomes same query in like, Postgres and Mongo and whatever. End user does not usually write MBQL, it's a service for the frontend querybuilding UI thing and lots of other frontend UI stuff mainly in usage.
Whole processing from MBQL -> your SQL or whatever is done via a buncha big-ass transducers. Metabase is not materially faster than other BI tools (because all the other BI tools do something vaguely similar in their langs) but it's pretty comparable speed and the whole thing was materially written by like 5 peeps
https://github.com/metabase/metabase/blob/master/src/metabas...
(nb: I used to work for Metabase but currently do not. but open core is open core)
- Upgrade Your Metabase Installation
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Upgrade your Metabase installation immediately
They haven't released the source, and the compiled versions are non-trivial to diff (e.g. there are nondeterministic numbers from the clojure compiler that seem to have changed from one to the other, and .clj files have been removed from the jar).
The old version has `hash=1bb88f5`, which is a public commit: https://github.com/metabase/metabase/commit/1bb88f5
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Launch HN: Twenty.com (YC S23) – open-source CRM
We are unsure about the right license to use, so this is a great feedback. We had a MIT license one week ago that we know that we cannot hold on long term and we felt we were lying to the community by keeping an MIT license and changing it in one year.
By using AGPL, we feel it's the right level of restriction. It's the license used by Metabase for example (https://github.com/metabase/metabase) that many companies use internally.
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Ask HN: Open-Source Self-Hosted No-Code Platforms?
The solution really depends on what sort of problems you are trying to solve and who your customers are.
There are a fair few low-code solutions out there for reporting and data visualisation that are great for finance and marketing teams for example. e.g. https://metabase.com/ , https://evidence.dev/
For multipurpose SMB workflows and organisational processes, I have used n8n in the recent past and found it was quite good and incredibly easy to maintain. https://n8n.io/engineering-resources/
For enterprise processes I'd go with Camunda (solely based on recommendations and not first hand experience). Although only parts of their platform are OSS https://github.com/camunda
Bear in mind that some of these are not suitable if you want to build something that competes with them while taking their OSS code. But are perfectly fine otherwise.
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916 days of Emacs
Anyway, I have a collection of scripts that merge ActivityWatch data from all my machines and WakaTime exports to a PostgreSQL database which I then query with a project called Metabase. If you're curious, the scripts are in a repository called sqrt-data. I've been playing with this for ~4-5 years already I think.
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Ask HN: Who is hiring? (April 2023)
Metabase | https://metabase.com | REMOTE | Full-time | Backend, Frontend, Full Stack, and DevOps engineers
Metabase is open source analytics software that lets anyone in your company rummage around in the databases you have. It connects to a number of databases / data warehouses (BigQuery, Redshift, Snowflake, Postgres, MySQL, etc).
What are some alternatives?
kafka-connect-opensky - Kafka Source Connector reading in from the OpenSky API
Apache Superset - Apache Superset is a Data Visualization and Data Exploration Platform [Moved to: https://github.com/apache/superset]
OpenKP - Automatically extracting keyphrases that are salient to the document meanings is an essential step to semantic document understanding. An effective keyphrase extraction (KPE) system can benefit a wide range of natural language processing and information retrieval tasks. Recent neural methods formulate the task as a document-to-keyphrase sequence-to-sequence task. These seq2seq learning models have shown promising results compared to previous KPE systems The recent progress in neural KPE is mostly observed in documents originating from the scientific domain. In real-world scenarios, most potential applications of KPE deal with diverse documents originating from sparse sources. These documents are unlikely to include the structure, prose and be as well written as scientific papers. They often include a much diverse document structure and reside in various domains whose contents target much wider audiences than scientists. To encourage the research community to develop a powerful neural m
lightdash - Open source BI for teams that move fast ⚡️
fake-data-producer-for-apache-kafka-docker - Fake Data Producer for Aiven for Apache Kafka® in a Docker Image
appsmith - Platform to build admin panels, internal tools, and dashboards. Integrates with 25+ databases and any API.
Grafana - The open and composable observability and data visualization platform. Visualize metrics, logs, and traces from multiple sources like Prometheus, Loki, Elasticsearch, InfluxDB, Postgres and many more.
Elasticsearch - Free and Open, Distributed, RESTful Search Engine
demo-scene - 👾Scripts and samples to support Confluent Demos and Talks. ⚠️Might be rough around the edges ;-) 👉For automated tutorials and QA'd code, see https://github.com/confluentinc/examples/
superset - Apache Superset is a Data Visualization and Data Exploration Platform
example-koa-prisma - Example to deploy a Koa application using Prisma on Koyeb
Redash - Make Your Company Data Driven. Connect to any data source, easily visualize, dashboard and share your data.