Greenplum
Apache AGE
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Greenplum | Apache AGE | |
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9 | 31 | |
6,198 | 709 | |
1.0% | - | |
9.9 | 8.5 | |
5 days ago | over 1 year ago | |
C | C | |
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.
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!
Apache AGE
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Alternatives to Neo4j Enterprise
What about the AGE extension for Postgres? https://age.apache.org/
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Anyone Using Graph Databases in F#?
Waiting for Postgres to release theirs.
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In MongoDB you can have duplicate items even if you have unique index
I think they are talking about the AGE extension https://age.apache.org
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Age 1.0 – PostgreSQL extension for graph database
It's my understanding of the "incubation" period of Apache Software Foundation projects is to determine if they're able to actually execute the ASF process, and a bunch of other "project maturity metrics" (https://community.apache.org/apache-way/apache-project-matur...) of which AGE currently has some self-certification: https://age.apache.org/?l=maturity#
I recognize that's not exactly an answer to the question you asked, but I would be surprised if someone other than a project member knows a more forward-looking one
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Looking for opinions: 95% of my Data fits extremely well in a Relational Database and 5% fits extremely well into a graph database. Should I consider splitting it between the two, or is that a silly idea?
Postgres has a graph extension: https://age.apache.org. This means you can keep all your data in PG and use both models.
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Getting Started with Redis and RedisGraph
PostgreSQL with graph extension, developed by a team at Apache Software Foundation as Apache AGE. Apache AGE uses Gremlin.
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Ask HN: Why are relational DBs are the standard instead of graph-based DBs?
The big thing that graph dbs provide is transitive traversals of join relationships.
The problem with graph dbs is trying to return something that is not a graph. Like a count. Or derived information. And which graph model do you use? There’s more than one. Lots of information is very poorly modeled in graph dbs. Temporal organization, for example.
Ultimately, graphs are a way to use relations. But relations allow you much more flexibility to associate information (subject to the issue of transitive relationship traversal).
Mixed graph-relational is perfectly reasonable. Reasonable start here: [https://age.apache.org/]
their actual landing page is actually better than the Github one. It's a translation layer(s) to allow querying Postgres using openCypher
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Truth Behind Neo4j’s “Trillion” Relationship Graph
Depending on how one views "postgres", there are at least two extensions that allegedly do it: https://age.apache.org/ and the AgensGraph from which AGE derives
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One table vs two table design
There's an extension to postgresql (I haven't used it, but I am familiar with node/edge tables in MSSQL) that allows you to do this: https://age.apache.org/
What are some alternatives?
citus - Distributed PostgreSQL as an extension
Neo4j - Graphs for Everyone
TimescaleDB - An open-source time-series SQL database optimized for fast ingest and complex queries. Packaged as a PostgreSQL extension.
janusgraph - JanusGraph: an open-source, distributed graph database
ClickHouse - ClickHouse® is a free analytics DBMS for big data
RedisGraph - A graph database as a Redis module
cockroach - CockroachDB - the open source, cloud-native distributed SQL database.
yugabyte-db - YugabyteDB - the cloud native distributed SQL database for mission-critical applications.
Airflow - Apache Airflow - A platform to programmatically author, schedule, and monitor workflows
datalevin - A simple, fast and versatile Datalog database
dremio-oss - Dremio - the missing link in modern data
datahike - A durable Datalog implementation adaptable for distribution.