[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"project-79409":3},{"id":4,"name":5,"fullName":6,"owner":7,"repo":5,"description":8,"homepage":9,"htmlUrl":10,"language":11,"languages":9,"totalLinesOfCode":9,"stars":12,"forks":13,"watchers":14,"openIssues":15,"contributorsCount":9,"subscribersCount":16,"size":16,"stars1d":17,"stars7d":18,"stars30d":19,"stars90d":16,"forks30d":16,"starsTrendScore":20,"compositeScore":21,"rankGlobal":9,"rankLanguage":9,"license":9,"archived":22,"fork":22,"defaultBranch":23,"hasWiki":22,"hasPages":22,"topics":24,"createdAt":9,"pushedAt":9,"updatedAt":30,"readmeContent":31,"aiSummary":32,"trendingCount":16,"starSnapshotCount":16,"syncStatus":33,"lastSyncTime":34,"discoverSource":35},79409,"fluss","apache\u002Ffluss","apache","Apache Fluss is a streaming storage built for real-time analytics.",null,"https:\u002F\u002Fgithub.com\u002Fapache\u002Ffluss","Java",1938,558,37,492,0,7,12,25,21,75.74,false,"main",[25,5,26,27,28,29],"streaming","lakehouse","real-time-analytics","big-data","hacktoberfest","2026-06-12 04:01:24","\u003C!--\n Licensed to the Apache Software Foundation (ASF) under one\n or more contributor license agreements.  See the NOTICE file\n distributed with this work for additional information\n regarding copyright ownership.  The ASF licenses this file\n to you under the Apache License, Version 2.0 (the\n \"License\"); you may not use this file except in compliance\n with the License.  You may obtain a copy of the License at\n\n      http:\u002F\u002Fwww.apache.org\u002Flicenses\u002FLICENSE-2.0\n\n Unless required by applicable law or agreed to in writing, software\n distributed under the License is distributed on an \"AS IS\" BASIS,\n WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n See the License for the specific language governing permissions and\n limitations under the License.\n-->\n\n\u003Cp align=\"center\">\n    \u003Cpicture>\n      \u003Csource media=\"(prefers-color-scheme: dark)\" srcset=\"website\u002Fstatic\u002Fimg\u002Flogo\u002Fsvg\u002Fwhite_color_logo.svg\">\n      \u003Csource media=\"(prefers-color-scheme: light)\" srcset=\"website\u002Fstatic\u002Fimg\u002Flogo\u002Fsvg\u002Fcolored_logo.svg\">\n      \u003C!-- Fall back to version that works for dark and light mode -->\n      \u003Cimg alt=\"Apache Fluss logo\" src=\"website\u002Fstatic\u002Fimg\u002Flogo\u002Fsvg\u002Fwhite_filled.svg\">\n    \u003C\u002Fpicture>\n\u003C\u002Fp>\n\n\u003Cp align=\"center\">\n  \u003Ca href=\"https:\u002F\u002Ffluss.apache.org\u002Fdocs\u002F\">Documentation\u003C\u002Fa> | \u003Ca href=\"https:\u002F\u002Ffluss.apache.org\u002Fdocs\u002Fquickstart\u002Fflink\u002F\">QuickStart\u003C\u002Fa> | \u003Ca href=\"https:\u002F\u002Ffluss.apache.org\u002Fcommunity\u002Fdev\u002Fide-setup\u002F\">Development\u003C\u002Fa>\n\u003C\u002Fp>\n\n\u003Cp align=\"center\">\n  \u003Ca href=\"https:\u002F\u002Fgithub.com\u002Fapache\u002Ffluss\u002Factions\u002Fworkflows\u002Fci.yaml\">\u003Cimg src=\"https:\u002F\u002Fgithub.com\u002Fapache\u002Ffluss\u002Factions\u002Fworkflows\u002Fci.yaml\u002Fbadge.svg?branch=main\" alt=\"CI\">\u003C\u002Fa>\n  \u003Ca href=\"https:\u002F\u002Fgithub.com\u002Fapache\u002Ffluss\u002Fblob\u002Fmain\u002FLICENSE\">\u003Cimg src=\"https:\u002F\u002Fimg.shields.io\u002Fbadge\u002Flicense-Apache%202-4EB1BA.svg\" alt=\"License\">\u003C\u002Fa>\n  \u003Ca href=\"https:\u002F\u002Fjoin.slack.com\u002Ft\u002Fapache-fluss\u002Fshared_invite\u002Fzt-33wlna581-QAooAiCmnYboJS8D_JUcYw\">\u003Cimg src=\"https:\u002F\u002Fimg.shields.io\u002Fbadge\u002Fslack-join_chat-brightgreen.svg?logo=slack\" alt=\"Slack\">\u003C\u002Fa>\n  \u003Ca href=\"https:\u002F\u002Fdeepwiki.com\u002Fapache\u002Ffluss\">\u003Cimg src=\"https:\u002F\u002Fdeepwiki.com\u002Fbadge.svg\" alt=\"Ask DeepWiki\">\u003C\u002Fa>\n\u003C\u002Fp>\n\n\u003Cp align=\"center\">\n  \u003Ca href=\"https:\u002F\u002Ftrendshift.io\u002Frepositories\u002F14168\" target=\"_blank\">\u003Cimg src=\"https:\u002F\u002Ftrendshift.io\u002Fapi\u002Fbadge\u002Frepositories\u002F14168\" alt=\"volcengine%2FOpenViking | Trendshift\" style=\"width: 250px; height: 55px;\" width=\"250\" height=\"55\"\u002F>\u003C\u002Fa>\n\u003C\u002Fp>\n\n## What is Apache Fluss (Incubating)?\n\nApache Fluss (Incubating) is a streaming storage built for real-time analytics & AI which can serve as the real-time data layer for Lakehouse architectures.\n\nIt bridges the gap between **data streaming** and **data Lakehouse** by enabling low-latency, high-throughput data ingestion and processing while seamlessly integrating with popular compute engines like **Apache Flink**, while \nApache Spark, and StarRocks are coming soon.\n\n**Fluss (German: river, pronounced `\u002Fflus\u002F`)** enables streaming data continuously converging, distributing and flowing into lakes, like a river 🌊\n\n## Features\n\n- **Sub-Second Data Freshness**: Continuous ingestion and immediate availability of data enable low-latency analytics and real-time decision-making at scale.\n- **Streaming & Lakehouse Unification**: Streaming-native storage with low-latency access on top of the lakehouse, using tables as a single abstraction to unify real-time and historical data across engines.\n- **Columnar Streaming**: Based on Apache Arrow it allows database primitives on data streams and techniques like column pruning and predicate pushdown. This ensures engines read only the data they need, minimizing I\u002FO and network costs.\n- **Compute–Storage Separation**: Stream processors focus on pure computation while Fluss manages state and storage, with features like deduplication, partial updates, delta joins, and aggregation merge engines.\n- **ML & AI–Ready Storage**: A unified storage layer supporting row-based, columnar, vector, and multi-modal data, enabling real-time feature stores and a centralized data repository for ML and AI systems.\n- **Changelogs & Decision Tracking**: Built-in changelog generation provides an append-only history of state and decision evolution, enabling auditing, reproducibility, and deep system observability.\n\n## Building\n\nPrerequisites for building Apache Fluss:\n\n- Unix-like environment (we use Linux, Mac OS X, Cygwin, WSL)\n- Git\n- Maven (we require version >= 3.8.6)\n- Java 11\n\n```bash\ngit clone https:\u002F\u002Fgithub.com\u002Fapache\u002Ffluss.git\ncd fluss\n.\u002Fmvnw clean package -DskipTests\n```\n\nApache Fluss is now installed in `build-target`. The build command uses Maven Wrapper (`mvnw`) which ensures the correct Maven version is used.\n\n## Contributing\n\nApache Fluss (Incubating) is open-source, and we’d love your help to keep it growing! Join the [discussions](https:\u002F\u002Fgithub.com\u002Fapache\u002Ffluss\u002Fdiscussions),\nopen [issues](https:\u002F\u002Fgithub.com\u002Fapache\u002Ffluss\u002Fissues) if you find a bug or request features, contribute code and documentation,\nor help us improve the project in any way. All contributions are welcome!\n\n## License\n\nApache Fluss (Incubating) project is licensed under the [Apache License 2.0](https:\u002F\u002Fgithub.com\u002Fapache\u002Ffluss\u002Fblob\u002Fmain\u002FLICENSE).\n","Apache Fluss 是一个专为实时分析设计的流式存储系统。该项目的核心功能包括低延迟、高吞吐量的数据摄入和处理，并能够无缝集成诸如 Apache Flink 等流行的计算引擎，未来还将支持 Apache Spark 和 StarRocks。它旨在填补数据流与数据湖仓之间的鸿沟，通过提供高效的数据流转能力来支持实时数据分析及人工智能应用。适用于需要快速响应变化数据的场景，如在线业务监控、即时推荐系统等。",2,"2026-06-11 03:57:48","trending"]