asami
datalevin
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asami | datalevin | |
---|---|---|
6 | 15 | |
626 | 1,030 | |
0.6% | 3.0% | |
0.0 | 9.6 | |
about 2 years ago | 4 days ago | |
Clojure | Clojure | |
Eclipse Public License 1.0 | Eclipse Public License 1.0 |
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.
asami
- Ask HN: What are some 'cool' but obscure data structures you know about?
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Ask HN: Why are relational DBs are the standard instead of graph-based DBs?
Unlike some other commenters, I agree that graph models are usually a better fit for most data than relational models. There's been some interesting work in recent years developing this idea: in the Clojure world there's Datomic, XTDB, and a host of competitors, all of which build on work from Semantic Web/SPARQL/triplestores and logic programming. Some are even intended to be used as primary datastores: they support some amount of schema and constraints, have well-defined consistency and ACID guarantees, etc. This makes them unlike graph databases like Neo4J and others, which fill an architectural role more like Elasticsearch as a read-optimization tool. Here's an interesting talk making a case for triple-based databases.
- Introduction to the Asami Graph Database
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How to query Datomic, Datascript, Asami, or other graph databases
Despite the documentation that exists, I've heard many people who have been confused about how to query Datomic, Datascript, Asami, or other graph databases. So I've made an attempt at explaining it https://github.com/threatgrid/asami/wiki/Introduction
- Introduction (To Graph Databases)
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Asami
The first Graph implementation for Asami was a simple in-memory data structure, described in my ClojureD talk. The code for this appears in asami.index. This file started much smaller (as referenced above), but has since expanded with the needs extended functionality, such as transactions, and transitive closure operations.
datalevin
- Datalevin: A simple, fast and versatile Datalog database
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Is Datomic right for my use case?
You can also consider other durable Datalog options like datahike or datalevin which can work either as lib (SQLite style) or in a client-server setup; if you want to play with bi-temporality XTDB is a rock solid option with very good support and documentation.
- Datomic is free
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benefits of clojure for web development over Haskell
There are some Clojure-ecosystems things that are pretty cool, too, that you'd probably miss going into Haskell. lacinia is an extremely cool GraphQL library, and there are a variety of interesting datalog-based datastores which are spiritual descendents of Datomic, notably xtdb (formerly crux) and datalevin. Also as noted, you can write the front-end in ClojureScript if you want to, and there are a lot of cool libraries for that as well.
- SQLite Internals: Pages and B-trees
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Call for Help - Open Source Datom/EAV/Fact database in Rust.
There are plenty of open source Datomic Inspired databases. Check out https://github.com/juji-io/datalevin and scroll down all the way down to “Alternatives”. There was even the beginning of a rust one by Mozilla: https://github.com/mozilla/mentat
- Datalevin ships performant fulltext search for its KV and Datalog stores
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T-Wand: Beat Lucene in Less Than 600 Lines of Code
The benchmarks in question have several implementation issues, I reported them on GitHub.
https://github.com/juji-io/datalevin/issues/created_by/caval...
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Choice of NoSQL database: XTDB vs MongoDB
Highly recommend you give https://github.com/juji-io/datalevin a chance. You can use it both as a key-value and/or relational datalog store (like datomic) but it’s very simple to set up and blazing fast!
-
Ask HN: Why are relational DBs are the standard instead of graph-based DBs?
Unlike some other commenters, I agree that graph models are usually a better fit for most data than relational models. There's been some interesting work in recent years developing this idea: in the Clojure world there's Datomic, XTDB, and a host of competitors, all of which build on work from Semantic Web/SPARQL/triplestores and logic programming. Some are even intended to be used as primary datastores: they support some amount of schema and constraints, have well-defined consistency and ACID guarantees, etc. This makes them unlike graph databases like Neo4J and others, which fill an architectural role more like Elasticsearch as a read-optimization tool. Here's an interesting talk making a case for triple-based databases.
What are some alternatives?
datascript - Immutable database and Datalog query engine for Clojure, ClojureScript and JS
xtdb - An immutable database for application development and time-travel data compliance, with SQL and XTQL. Developed by @juxt
crux - General purpose bitemporal database for SQL, Datalog & graph queries. Backed by @juxt [Moved to: https://github.com/xtdb/xtdb]
datahike - A durable Datalog implementation adaptable for distribution.
Apache AGE - Graph database optimized for fast analysis and real-time data processing. It is provided as an extension to PostgreSQL. [Moved to: https://github.com/apache/age]
naga - Datalog based rules engine
grakn - TypeDB: the polymorphic database powered by types
indradb - A graph database written in rust