Throughput, batching, and efficiency of indexing pipelines.
CocoIndex's first post-v1 releases: stable memoization keys, scheduled live refresh, scoped stats, safer SQL connectors, and more graph and streaming integrations.
Featuring five new target connectors, filesystem-level change detection, Python 3.14 free-threading, and smarter pipeline lifecycle management.
Featuring batching support for CocoIndex functions, execution robustness, schema & type system improvements, custom source support, and more.
CocoIndex now batches GPU and ML workloads automatically: 5x throughput on text embeddings and AI ops, with zero configuration required.
CocoIndex updates: production readiness, scalability, and reliability, plus more customization, native integrations, and multi-modal pipeline features.
How CocoIndex's layered concurrency controls optimize data-processing performance, prevent system overload, and keep pipelines stable and efficient at scale.
CocoIndex helps to keep the index up to date with source changes, super efficient and low latency - with the support of incremental processing.
Handle large files in data indexing: processing granularity, fan-in/fan-out, and memory pressure, walked through a patent XML example in CocoIndex.