Greenplum
go
Greenplum | go | |
---|---|---|
9 | 2,074 | |
6,199 | 119,718 | |
0.2% | 0.6% | |
9.9 | 10.0 | |
5 days ago | about 20 hours ago | |
C | Go | |
Apache License 2.0 | BSD 3-clause "New" or "Revised" License |
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.
Greenplum
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Ask HN: It's 2023, how do you choose between MySQL and Postgres?
Friends don't let their friends choose Mysql :)
A super long time ago (decades) when I was using Oracle regularly I had to make a decision on which way to go. Although Mysql then had the mindshare I thought that Postgres was more similar to Oracle, more standards compliant, and more of a real enterprise type of DB. The rumor was also that Postgres was heavier than MySQL. Too many horror stories of lost data (MyIsam), bad transactions (MyIsam lacks transaction integrity), and the number of Mysql gotchas being a really long list influenced me.
In time I actually found out that I had underestimated one of the most important attributes of Postgres that was a huge strength over Mysql: the power of community. Because Postgres has a really superb community that can be found on Libera Chat and elsewhere, and they are very willing to help out, I think Postgres has a huge advantage over Mysql. RhodiumToad [Andrew Gierth] https://github.com/RhodiumToad & davidfetter [David Fetter] https://www.linkedin.com/in/davidfetter are incredibly helpful folks.
I don't know that Postgres' licensing made a huge difference or not but my perception is that there are a ton of 3rd party products based on Postgres but customized to specific DB needs because of the more liberalness of the PG license which is MIT/BSD derived https://www.postgresql.org/about/licence/
Some of the PG based 3rd party DBs:
Enterprise DB https://www.enterprisedb.com/ - general purpose PG with some variants
Greenplum https://greenplum.org/ - Data warehousing
Crunchydata https://www.crunchydata.com/products/hardened-postgres - high security Postgres for regulated environments
Citus https://www.citusdata.com - Distributed DB & Columnar
Timescale https://www.timescale.com/
Why Choose PG today?
If you want better ACID: Postgres
If you want more compliant SQL: Postgres
If you want more customizability to a variety of use-cases: Postgres using a variant
If you want the flexibility of using NOSQL at times: Postgres
If you want more product knowledge reusability for other backend products: Postgres
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Show HN: Postgres WASM
I was wondering if anyone had thought about using this to experiment with the planner.
The engineering and support teams at Greenplum, a fork of Postgres, have a tool (minirepro[0]) which, given a sql query, can grab a minimal set of DDLs and the associated statistics for the tables involved in the query that can then be loaded into a "local" GPDB instance. Having the DDL and the statistics meant the team was able to debug issues in the optimizer (example [1]), without having access to a full set of data. This approach, if my understanding is correct, could be enabled in the browser with this Postgres WASM capability.
[0] https://github.com/greenplum-db/gpdb/blob/6X_STABLE/gpMgmt/b...
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Amazon Aurora's Read/Write Capability Enhancement with Apache ShardingSphere-Proxy
A database solution architect at AWS, with over 10 years of experience in the database industry. Lili has been involved in the R&D of the Hadoop/Hive NoSQL database, enterprise-level database DB2, distributed data warehouse Greenplum/Apache HAWQ and Amazon’s cloud native database.
- Greenplum Database – Massively Parallel PostgreSQL for Analytics
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What’s the Database Plus concept and what challenges can it solve?
Today, it is normal for enterprises to leverage diversified databases. In my market of expertise, China, in the Internet industry, MySQL together with data sharding middleware is the go to architecture, with GreenPlum, HBase, Elasticsearch, Clickhouse and other big data ecosystems being auxiliary computing engine for analytical data. At the same time, some legacy systems (such as SQLServer legacy from .NET transformation, or Oracle legacy from outsourcing) can still be found in use. In the financial industry, Oracle or DB2 is still heavily used as the core transaction system. New business is migrating to MySQL or PostgreSQL. In addition to transactional databases, analytical databases are increasingly diversified as well.
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Data Science Competition
Green Plum
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Inspecting joins in PostgreSQL
PostgreSQL is a free and advanced database system with the capacity to handle a lot of data. It’s available for very large data in several forms like Greenplum and Redshift on Amazon. It is open source and is managed by an organized and very principled community.
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What’s so special about distributed SQL? Ask us anything!
2003 - https://greenplum.org/
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Using Postgres as a Data Warehouse
There's Greenplum!
go
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Microsoft Maintains Go Fork for FIPS 140-2 Support
There used to be the GO FIPS branch :
https://github.com/golang/go/tree/dev.boringcrypto/misc/bori...
But it looks dead.
And it looks like https://github.com/golang-fips/go as well.
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Borgo is a statically typed language that compiles to Go
I'm not sure what exactly you mean by acknowledgement, but here are some counterexamples:
- A proposal for sum types by a Go team member: https://github.com/golang/go/issues/57644
- The community proposal with some comments from the Go team: https://github.com/golang/go/issues/19412
Here are some excerpts from the latest Go survey [1]:
- "The top responses in the closed-form were learning how to write Go effectively (15%) and the verbosity of error handling (13%)."
- "The most common response mentioned Go’s type system, and often asked specifically for enums, option types, or sum types in Go."
I think the problem is not the lack of will on the part of the Go team, but rather that these issues are not easy to fix in a way that fits the language and doesn't cause too many issues with backwards compatibility.
[1]: https://go.dev/blog/survey2024-h1-results
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AWS Serverless Diversity: Multi-Language Strategies for Optimal Solutions
Now, I’m not going to use C++ again; I left that chapter years ago, and it’s not going to happen. C++ isn’t memory safe and easy to use and would require extended time for developers to adapt. Rust is the new kid on the block, but I’ve heard mixed opinions about its developer experience, and there aren’t many libraries around it yet. LLRD is too new for my taste, but **Go** caught my attention.
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How to use Retrieval Augmented Generation (RAG) for Go applications
Generative AI development has been democratised, thanks to powerful Machine Learning models (specifically Large Language Models such as Claude, Meta's LLama 2, etc.) being exposed by managed platforms/services as API calls. This frees developers from the infrastructure concerns and lets them focus on the core business problems. This also means that developers are free to use the programming language best suited for their solution. Python has typically been the go-to language when it comes to AI/ML solutions, but there is more flexibility in this area. In this post you will see how to leverage the Go programming language to use Vector Databases and techniques such as Retrieval Augmented Generation (RAG) with langchaingo. If you are a Go developer who wants to how to build learn generative AI applications, you are in the right place!
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From Homemade HTTP Router to New ServeMux
net/http: add methods and path variables to ServeMux patterns Discussion about ServeMux enhancements
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Building a Playful File Locker with GoFr
Make sure you have Go installed https://go.dev/.
- Fastest way to get IPv4 address from string
- We now have crypto/rand back ends that ~never fail
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Why Go is great choice for Software engineering.
The Go Programming Language
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OpenBSD 7.5 Released
When Go first shipped, it was already well-documented that the only stable ABI on some platforms was via dynamic libraries (such as libc) provided by said platforms. Go knowingly and deliberately ignored this on the assumption that they can get away with it. And then this happened:
https://github.com/golang/go/issues/16606
If that's not "getting burned", I don't know what is. "Trying to provide a nice feature" is an excuse, and it can be argued that it is a valid one, but nevertheless they knew that they were using an unstable ABI that could be pulled out from under them at any moment, and decided that it's worth the risk. I don't see what that has to do with "not being as broadly compatible as they had hoped", since it was all known well in advance.
What are some alternatives?
citus - Distributed PostgreSQL as an extension
v - Simple, fast, safe, compiled language for developing maintainable software. Compiles itself in <1s with zero library dependencies. Supports automatic C => V translation. https://vlang.io
TimescaleDB - An open-source time-series SQL database optimized for fast ingest and complex queries. Packaged as a PostgreSQL extension.
TinyGo - Go compiler for small places. Microcontrollers, WebAssembly (WASM/WASI), and command-line tools. Based on LLVM.
ClickHouse - ClickHouse® is a free analytics DBMS for big data
zig - General-purpose programming language and toolchain for maintaining robust, optimal, and reusable software.
cockroach - CockroachDB - the open source, cloud-native distributed SQL database.
Nim - Nim is a statically typed compiled systems programming language. It combines successful concepts from mature languages like Python, Ada and Modula. Its design focuses on efficiency, expressiveness, and elegance (in that order of priority).
Airflow - Apache Airflow - A platform to programmatically author, schedule, and monitor workflows
Angular - Deliver web apps with confidence 🚀
dremio-oss - Dremio - the missing link in modern data
golang-developer-roadmap - Roadmap to becoming a Go developer in 2020