Dev tools · alternatives · 2026
24 alternatives to AKM
Rate-limit aware smart API key scheduling
Below are 24 products that do a similar job, ranked by how close each is in meaning and then by launch-day votes.
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Bucket4J▲77Rate-limiting based on token bucket algorithm for Java
2021 · github.com · its alternatives →
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Golimit is Uber ringpop based distributed and decentralized rate limiter - myntra/golimit
2018 · github.com · its alternatives →
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A lightweight engine for durable execution / deterministic workflows I built with Rust, wasmtime and the WASM Component Model. Its main use is running reliable, long-running workflows that can automatically resume after failures. Looking for feedback on the approach and potential use cases!
2025 · obeli.sk · its alternatives →
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High performance secure & portable Rust functions in Node.js
2020 · secondstate.io · its alternatives →
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🚀 Fast and simple Node.js version manager, built in Rust - Schniz/fnm
2019 · github.com · its alternatives →
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DeltaMemory▲104Most AI agents forget everything between sessions. We built DeltaMemory to fix that. It's a cognitive memory layer that gives agents persistent recall, automatic fact extraction, and temporal reasoning — via a single SDK call. Key numbers: - 89% accuracy on LoCoMo long-term conversation benchmark - 50ms p50 retrieval latency - 97% cost reduction vs raw token re-processing Open source SDKs, works with any LLM stack. Currently in early access. Happy to answer questions about the architecture, benchmark methodology, or how we handle knowledge graphs.
Feb 2026 · deltamemory.com · its alternatives →
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Hey HN! I’m the founder of Unify, and we’ve just released our Model Hub, which provides a collection of LLM endpoints with live runtime benchmarks all plotted across time: https://unify.ai/hub A key finding is that static tabular runtime benchmarks for LLMs simply do not work. It’s necessary to take a time-series perspective, and plot the variations through time. We currently have 21 models provided by: Anyscale, Perplexity AI, Replicate, Together AI, OctoAI, Mistral AI and OpenAI, with more on the roadmap. We test across different regions (Asia, US, Europe), with varied…
2024 · its alternatives →
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Hi HN! I built a distributed rate limiter using the token bucket algorithm with Redis backing. Key highlights: • 50,000+ requests/second throughput with <2ms P95 latency • Redis-backed distributed state for multi-instance deployments • 18 REST API endpoints for rate limiting, config, and monitoring • 265+ tests including load tests and integration tests • Docker/Kubernetes ready with comprehensive documentation Built with Java 21 + Spring Boot. Perfect for protecting APIs, microservices, or SaaS platforms from abuse. The pain point I solved: existing solutions were either too…
2025 · github.com · its alternatives →
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I recently built a small open-source tool to benchmark different LLM API endpoints — including OpenAI, Claude, and self-hosted models (like llama.cpp). It runs a configurable number of test requests and reports two key metrics: • First-token latency (ms): How long it takes for the first token to appear • Output speed (tokens/sec): Overall output fluency Demo: https://llmapitest.com/ Code: https://github.com/qjr87/llm-api-test The goal is to provide a simple, visual, and reproducible way to evaluate performance across different LLM providers, including…
2025 · llmapitest.com · its alternatives →
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I've been working on Fast LiteLLM - a Rust acceleration layer for the popular LiteLLM library - and I had some interesting learnings that might resonate with other developers trying to squeeze performance out of existing systems. My assumption was that LiteLLM, being a Python library, would have plenty of low-hanging fruit for optimization. I set out to create a Rust layer using PyO3 to accelerate the performance-critical parts: token counting, routing, rate limiting, and connection pooling. The Approach - Built Rust implementations for token counting using tiktoken-rs - Added lock-free data…
Nov 2025 · github.com · its alternatives →
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I built this after seeing multiple teams accidentally ship API keys in their frontend code. The problem: Modern web development moves fast. You're vibe-coding, shipping features, and suddenly your AWS keys are sitting in a tag visible to anyone who opens DevTools. I've personally witnessed this happen to at least 3-4 production apps in the past year alone. KeyLeak Detector runs through your site (headless browser + network interception) and checks for 50+ types of leaked secrets: AWS/Google keys, Stripe tokens, database connection strings, LLM API keys (OpenAI, Claude, etc.), JWT…
Nov 2025 · github.com · its alternatives →
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simple daemon for rate limit. Contribute to limitd/limitd development by creating an account on GitHub.
2015 · github.com · its alternatives →
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A Redis module that provides rate limiting in Redis as a single command. - brandur/redis-cell
2016 · github.com · its alternatives →
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I think in-process key management is the right abstraction for multi-key LLM setups. Not LiteLLM, not a Redis queue, not a custom load balancer. The failure modes are well-understood: a key gets rate-limited, you wait, you try the next one. Billing errors need a longer cooldown than rate limits. This is not a distributed systems problem — it's a state machine that fits in a library. The problem is everyone keeps solving it with infrastructure instead. Spin up LiteLLM, now you have a Python service to maintain. Reach for Redis, now you have a database for a problem that doesn't need one.…
Mar 2026 · github.com · its alternatives →
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Multi-tier exact-match cache for AI agents backed by Valkey or Redis. LLM responses, tool results, and session state behind one connection. Framework adapters for LangChain, LangGraph, and Vercel AI SDK. OpenTelemetry and Prometheus built in. No modules required - works on vanilla Valkey 7+ and Redis 6.2+. Shipped v0.1.0 yesterday, v0.2.0 today with cluster mode. Streaming support coming next. Existing options locked you into one tier (LangChain = LLM only, LangGraph = state only) or one framework. This solves both. npm:…
Apr 2026 · its alternatives →
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Over the past few months, as we scaled our internal AI Agents, we hit a dead end: Running LLM-generated arbitrary code in Docker is basically running naked on security due to container escape risks. But using full traditional VMs takes minutes to boot and eats too much memory to support high-density concurrency. We loved the developer experience of SaaS sandboxes on the market, but they are closed-source, expensive, and have too high a barrier to entry for self-hosting. So, our team decided to build our own. After months of grinding, using RustVMM and KVM, we built a blazing-fast,…
Apr 2026 · github.com · its alternatives →
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Promptly▲13An AI Cost Optimization Infrastructure for LLM Applications
Mar 2026 · getpromptly.in · its alternatives →
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Ranked by how close each launch is in meaning, then by votes. Prices were read from each product’s own site when checked and can change. Refine with your own description →