Redis 8 Community Edition has successfully scaled its vector search capabilities to handle a billion vectors, maintaining high precision and low latency. The benchmarking results show that Redis can achieve 90% precision with a median latency of 200ms and 95% precision with a median latency of 1.3 seconds for the top 100 nearest neighbors when executing 50 search queries concurrently. The vector database's performance is demonstrated on a dataset consisting of one billion 768-dimensional vectors, using FLOAT16 precision and 10K queries with 100 ground truth (exact neighbors) per query. Redis can sustain high ingestion rates of up to 160K vector insertions per second for indexing configurations that result in lower precisions, while maintaining real-time latency. The performance is further improved by tuning the HNSW parameters, which allows balancing precision, latency, and throughput to fit specific use cases.