About
            Manage complex models using ArcadeDB without any compromise. Forget about Polyglot Persistence. no need for multiple databases. You can store graphs, documents, key values and time series all in one ArcadeDB Multi-Model database. Since each model is native to the database engine, you don't have to worry about translations slowing you down. ArcadeDB's engine was built with Alien Technology. It's able to crunch millions of records per second. With ArcadeDB, the traversing speed is not affected by the database size. It is always constant, whether your database has a few records or billions. ArcadeDB can work as an embedded database, on a single server and can scale up using multiple servers with Kubernetes. Flexible enough to run on any platform with a small footprint. Your data is secure. Our unbreakable fully transactional engine assures durability for mission-critical production databases. ArcadeDB uses a Raft Consensus Algorithm to maintain consistency across multiple servers.
             
            
        
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            About
            OrigoDB enables you to build high quality, mission critical systems with real-time performance at a fraction of the time and cost. This is not marketing gibberish! Please read on for a no nonsense description of our features. Get in touch if you have questions or download and try it out today! In-memory operations are orders of magnitude faster than disk operations. A single OrigoDB engine can execute millions of read transactions per second and thousands of write transactions per second with synchronous command journaling to a local SSD. This is the #1 reason we built OrigoDB. A single object oriented domain model is far simpler than the full stack including a relational model, object/relational mapping, data access code, views and stored procedures. That's a lot of waste that can be eliminated! The OrigoDB engine is 100% ACID out of the box. Commands execute one at a time, transitioning the in-memory model from one consistent state to the next.
             
            
        
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            About
            RecallGraph is a versioned-graph data store - it retains all changes that its data (vertices and edges) have gone through to reach their current state. It supports point-in-time graph traversals, letting the user query any past state of the graph just as easily as the present.
RecallGraph is a potential fit for scenarios where data is best represented as a network of vertices and edges (i.e., a graph) having the following characteristics:
1. Both vertices and edges can hold properties in the form of attribute/value pairs (equivalent to JSON objects).
2. Documents (vertices/edges) mutate within their lifespan (both in their individual attributes/values and in their relations with each other).
3. Past states of documents are as important as their present, necessitating retention and queryability of their change history.
Also see this blog post for an intro - https://blog.recallgraph.tech/never-lose-your-old-data-again.
             
            
        
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            About
            python-sql is a library to write SQL queries in a pythonic way. Simple selects, select with where condition. Select with join or select with multiple joins. Select with group_by and select with output name. Select with order_by, or select with sub-select. Select on other schema and insert query with default values. Insert query with values, and insert query with query. Update query with values. Update query with where condition. Update query with from the list. Delete query with where condition, and delete query with sub-query. Provides limit style, qmark style, and numeric style.
             
            
        
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        Company InformationArcadeDB 
    
    United Kingdom 
    arcadedb.com 
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        Company InformationOrigo 
    
    Founded: 2014 
    
    Sweden 
    origodb.com 
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        Company InformationRecallGraph 
    
    Founded: 2020 
    
    India 
    recallgraph.tech/ 
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        Company InformationPython Software Foundation 
    
    United States 
    pypi.org/project/python-sql/ 
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