4 repository-uri
Awesome GitHub RepositoriesIncremental Computation
Execution of differential computations like aggregations and joins to maintain up-to-date streaming views.
Distinct from Incremental Data Streaming: Focuses on the execution of differential logic (joins/aggs) rather than just memory-efficient streaming of data.
Explore 4 awesome GitHub repositories matching data & databases · Incremental Computation. Refine with filters or upvote what's useful.
Awesome Incremental Computation GitHub Repositories
Găsește cele mai bune repo-uri cu AI.Vom căuta cele mai potrivite repository-uri folosind AI.
- risingwavelabs/risingwave
risingwavelabs/risingwave
9,093Vezi pe GitHubRisingWave is a cloud-native streaming database and real-time analytics engine that uses standard SQL to process continuous data streams. It functions as a streaming data lakehouse, combining the capabilities of a streaming SQL database with a platform that integrates streaming ingestion with open table formats. The system is distinguished by its use of the PostgreSQL wire protocol, allowing it to integrate with existing SQL tools and drivers. It employs a decoupled compute and storage architecture, persisting streaming state and materialized views in cloud object storage to enable independen
Executes incremental aggregations and joins to maintain real-time views of streaming data.
Rustapache-icebergdata-engineeringdatabase - square/crossfilter
square/crossfilter
6,187Vezi pe GitHubFast n-dimensional filtering and grouping of records.
Computes histograms and top-K lists incrementally as filter conditions change, avoiding full recomputation.
JavaScript - cocoindex-io/cocoindex
cocoindex-io/cocoindex
6,117Vezi pe GitHubCocoindex is an incremental data processing engine that builds and maintains live indexes for AI agents, with a core focus on codebase indexing and knowledge graph extraction. The engine uses a function-graph execution model where user-defined Python functions are composed into a directed acyclic graph, and it processes data incrementally so only changed source records or code paths are re-computed, avoiding full recomputation at any scale. It supports automatic schema inference from transformation pipeline type annotations and provides full data lineage tracing, tagging every output record wi
Processes data changes incrementally so only modified content is re-computed, keeping large corpora fresh without full recomputation.
Rustagentic-data-frameworkaiai-agents - stumpy-dev/stumpy
stumpy-dev/stumpy
4,105Vezi pe GitHubStumpy este o bibliotecă Python pentru analiza scalabilă a seriilor temporale, centrată pe implementarea algoritmilor de profil matriceal. Acesta oferă un framework pentru calcularea profilurilor de distanță pentru a identifica tipare repetitive și anomalii în datele seriilor temporale. Proiectul se distinge prin capacitatea sa de a scala calculele grele pe hardware GPU și clustere distribuite folosind Dask. Suportă analiza multidimensională pentru descoperirea motivelor în fluxuri de date concurente și oferă calcul incremental pentru analiza fluxurilor în timp real. Biblioteca acoperă o gamă largă de tehnici de minare a seriilor temporale, inclusiv descoperirea motivelor, detectarea anomaliilor și potrivirea tiparelor de secvență. Oferă, de asemenea, instrumente pentru segmentarea semantică pentru a detecta schimbările de regim și extragerea lanțurilor ordonate temporal de tipare de sub-secvențe similare.
Calculates matrix profiles incrementally as new data arrives to monitor time series in real time.
Pythonanomaly-detectiondaskdata-science
