https://www.solosoft.dev/tags/real-time/Recent content in Real-Time on SoloSoftHugoen-usFri, 01 May 2026 00:00:00 +0000https://www.solosoft.dev/post/memgraph-database-2026/Fri, 01 May 2026 00:00:00 +0000https://www.solosoft.dev/post/memgraph-database-2026/<p>The world of databases has long been divided between those optimized for transactions (OLTP) and those optimized for analytics (OLAP). Graph databases occupy a unique space in this landscape: they excel at querying relationships &ndash; the connections between entities that are increasingly central to modern applications. Fraud detection, recommendation engines, knowledge graphs, network monitoring, and identity resolution all depend on understanding how things relate to each other. Memgraph takes this capability and adds a critical dimension: real-time performance.</p> <p><strong>Memgraph</strong> is an in-memory, ACID-compliant graph database purpose-built for real-time data processing. Unlike traditional graph databases that prioritize durability over speed, Memgraph is architected from the ground up for low-latency, high-throughput graph operations. It supports the Cypher query language (the same query language used by Neo4j), stream ingestion from Apache Kafka and other message brokers, and enterprise-grade transactional guarantees.</p>https://www.solosoft.dev/post/rvc-voice-conversion-2026/Fri, 01 May 2026 00:00:00 +0000https://www.solosoft.dev/post/rvc-voice-conversion-2026/<p>RVC (Retrieval-based Voice Conversion) WebUI is an open-source voice conversion framework developed by the <a href="https://github.com/RVC-Project/Retrieval-based-Voice-Conversion-WebUI">RVC-Project</a> team that has become the standard tool for AI voice conversion in both spoken and singing contexts. Built on the VITS (Variational Inference Text-to-Speech) architecture, RVC achieves high-quality voice conversion with remarkably little training data &ndash; just 10 minutes of audio is sufficient for a convincing voice model.</p> <p>The project distinguishes itself from traditional voice conversion approaches through its retrieval-based mechanism. Instead of requiring paired data (same content spoken in different voices), RVC uses a feature retrieval approach that extracts and transfers speaker characteristics while preserving the linguistic content of the source audio. This makes it particularly powerful for singing voice conversion, where preserving pitch, rhythm, and emotional expression is critical.</p>