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ipolyzos pushed a commit to branch main
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The following commit(s) were added to refs/heads/main by this push:
new de648d210 [hotfix] update messaging on github page (#2478)
de648d210 is described below
commit de648d2107c236e5ec614b46a0e3781421ed6a94
Author: Giannis Polyzos <[email protected]>
AuthorDate: Mon Jan 26 11:01:33 2026 +0200
[hotfix] update messaging on github page (#2478)
---
README.md | 12 ++++++------
.../community/how-to-release/creating-a-fluss-release.mdx | 2 +-
.../how-to-release/creating-a-fluss-shaded-release.md | 2 +-
website/src/components/HomepageIntroduce/index.tsx | 2 +-
4 files changed, 9 insertions(+), 9 deletions(-)
diff --git a/README.md b/README.md
index 447fceebc..c59df6125 100644
--- a/README.md
+++ b/README.md
@@ -47,12 +47,12 @@ Apache Spark, and StarRocks are coming soon.
## Features
-- **Sub-Second Latency**: Low-latency streaming reads/writes optimized for
real-time applications with Apache Flink.
-- **Columnar Stream**: 10x improvement in streaming read performance with
efficient pushdown projections.
-- **Streaming & Lakehouse Unification**: Unified data streaming and Lakehouse
with low latencies for powerful analytics.
-- **Real-Time Updates**: Cost-efficient partial updates for large-scale data
without expensive join operations.
-- **Changelog Generation**: Complete changelogs for streaming processors,
streamlining analytics workflows.
-- **Lookup Queries**: Ultra-high QPS for primary key lookups, enabling
efficient dimension table serving.
+- **Sub-Second Data Freshness**: Continuous ingestion and immediate
availability of data enable low-latency analytics and real-time decision-making
at scale.
+- **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.
+- **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/O and network costs.
+- **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.
+- **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.
+- **Changelogs & Decision Tracking**: Built-in changelog generation provides
an append-only history of state and decision evolution, enabling auditing,
reproducibility, and deep system observability.
## Building
diff --git a/website/community/how-to-release/creating-a-fluss-release.mdx
b/website/community/how-to-release/creating-a-fluss-release.mdx
index e5ce9250a..bedcd8288 100644
--- a/website/community/how-to-release/creating-a-fluss-release.mdx
+++ b/website/community/how-to-release/creating-a-fluss-release.mdx
@@ -614,7 +614,7 @@ The Apache Fluss community has voted and approved the
release of
Apache Fluss 0.8.0-incubating (RC1). We now kindly request the IPMC
members to review and vote for this release.
-Apache Fluss (Incubating) - A streaming storage built for real-time analytics
which can serve as the real-time data layer for Lakehouse architectures.
+Apache Fluss (Incubating) - A streaming storage built for real-time analytics
& AI which can serve as the real-time data layer for Lakehouse architectures.
Fluss community vote thread:
* https://lists.apache.org/thread/<VOTE THREAD>
diff --git
a/website/community/how-to-release/creating-a-fluss-shaded-release.md
b/website/community/how-to-release/creating-a-fluss-shaded-release.md
index c4a7f5f71..9d56ba062 100644
--- a/website/community/how-to-release/creating-a-fluss-shaded-release.md
+++ b/website/community/how-to-release/creating-a-fluss-shaded-release.md
@@ -288,7 +288,7 @@ The Apache Fluss community has voted and approved the
release of
Apache Fluss Shaded 1.0-incubating (rc3). We now kindly request the IPMC
members to review and vote for this release.
-Apache Fluss (Incubating) - A streaming storage built for real-time analytics
which can serve as the real-time data layer for Lakehouse architectures.
+Apache Fluss (Incubating) - A streaming storage built for real-time analytics
& AI which can serve as the real-time data layer for Lakehouse architectures.
Fluss community vote thread:
* https://lists.apache.org/thread/<VOTE THREAD>
diff --git a/website/src/components/HomepageIntroduce/index.tsx
b/website/src/components/HomepageIntroduce/index.tsx
index 51dd0964c..6d747f23d 100644
--- a/website/src/components/HomepageIntroduce/index.tsx
+++ b/website/src/components/HomepageIntroduce/index.tsx
@@ -30,7 +30,7 @@ const IntroduceList: IntroduceItem[] = [
{
description: (
<>
- <b>Apache Fluss (Incubating)</b> is a streaming storage built for
real-time analytics which can serve as the real-time data layer for Lakehouse
architectures. With its columnar stream and real-time update capabilities,
Fluss integrates seamlessly with Apache Flink to enable high-throughput,
low-latency, cost-effective streaming data warehouses tailored for real-time
applications.
+ <b>Apache Fluss (Incubating)</b> is a streaming storage built for
real-time analytics & AI which can serve as the real-time data layer for
Lakehouse architectures. With its columnar stream and real-time update
capabilities, Fluss integrates seamlessly with Apache Flink to enable
high-throughput, low-latency, cost-effective streaming data warehouses tailored
for real-time applications.
</>
),
image: require('@site/static/img/fluss.png').default,
