Search Results for "throughput"

Garnet is a remote cache‑store developed by Microsoft Research. It delivers high throughput and low‑latency performance, supports scalability via clustering (sharding, replication, key migration, checkpointing, failover, transactions), and seamlessly integrates with existing Redis clients. Garnet offers much better throughput and scalability with many client connections and small batches, relative to comparable open-source cache-stores, leading to cost savings for large apps and services. ...

...Developed by Alibaba’s Tongyi Lab, it positions itself as the “SQLite of vector databases” by being easy to integrate, minimal in dependencies, and capable of handling high throughput with low latency on edge devices or small systems. Zvec excels at approximate nearest neighbor search and retrieval tasks that power features like semantic search, recommendation systems, and retrieval-augmented generation (RAG) setups. Its performance benchmarks show it achieving high queries-per-second and fast index build times compared to similar tools. ...

ZeusDB is a vector database built for fast, scalable similarity search with strong production ergonomics. It combines high-performance approximate nearest neighbor indexes with clean APIs and metadata filtering so applications can retrieve semantically relevant items at low latency. The storage layer is designed for durability and growth, supporting sharding, replication, and background compaction while keeping query tails predictable. Developers get multiple ingestion paths—batch,...

GT.M[tm] is a vetted industrial strength, transaction processing application platform consisting of a key-value database engine optimized for extreme transaction processing throughput & business continuity.

...The goal of the tool is reduce the overhead of creating new resources by reusing of the same resources among multiple processes. Achieving result is better performance and throughput. The resource pool was inspired by Java Apache's commons pool and adopts API and main principals from this project. Database connection is most popular example for pooling resource.

AMEN (Annotation, Mapping, Expression and Network) is a stand-alone, unified suite of tools to manage, explore and combine biological multifaceted high-throughput data such as annotation, chromosomal location, expression and interaction data.

PIP on GT.M is a mature and proven complete FOSS stack for developing transaction processing database applications with superb scalability, transaction throughput & unique functionality for extreme levels of business continuity.

Ray improves throughput when many concurrent queries access large scientific databases. Queries are synchronized to access sectors on disk simultaneously so that an arbitrary number of parallel queries can be executed without degradation in performance.

ArrayPipeLine is a web-based Laboratory Information Management system, using MySQL, Perl CGI and R. It enables high-throughput analysis of microarray data, providing automation of data handling, and rapid creation and implementation of analysis pipelines

Project MOVED to Codehaus New location is http://esper.codehaus.org The Esper project aims to provide a general-purpose event processing facility in Java for complex event processing of real-time, high throughput data streams.

Java software that store biological data in a database through a graphic interface