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The following commit(s) were added to refs/heads/main by this push:
new 518ae7f1a [website] Update Fluss messaging (#2428)
518ae7f1a is described below
commit 518ae7f1a2cf231d857b090ccfe6337ccaef1252
Author: Giannis Polyzos <[email protected]>
AuthorDate: Thu Jan 22 14:07:45 2026 +0200
[website] Update Fluss messaging (#2428)
---
README.md | 2 +-
.../how-to-release/creating-a-fluss-release.mdx | 2 +-
.../creating-a-fluss-shaded-release.md | 2 +-
website/docs/intro.md | 2 +-
website/docusaurus.config.ts | 2 +-
website/package.json | 3 +-
website/src/components/HomepageFeatures/index.tsx | 38 +++++++++-------------
website/src/pages/downloads.md | 2 +-
8 files changed, 24 insertions(+), 29 deletions(-)
diff --git a/README.md b/README.md
index 43b2ee050..447fceebc 100644
--- a/README.md
+++ b/README.md
@@ -38,7 +38,7 @@
## What is Apache Fluss (Incubating)?
-Apache Fluss (Incubating) is a streaming storage built for real-time analytics
which can serve as the real-time data layer for Lakehouse architectures.
+Apache Fluss (Incubating) is a streaming storage built for real-time analytics
& AI which can serve as the real-time data layer for Lakehouse architectures.
It 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
Apache Spark, and StarRocks are coming soon.
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 ac0acbb7e..e5ce9250a 100644
--- a/website/community/how-to-release/creating-a-fluss-release.mdx
+++ b/website/community/how-to-release/creating-a-fluss-release.mdx
@@ -836,7 +836,7 @@ Subject: [ANNOUNCE] Apache Fluss 0.8.0-incubating released
The Apache Fluss community is very happy to announce the release of Apache
Fluss 0.8.0-incubating.
-Apache Fluss is a streaming storage built for real-time analytics which can
serve as the real-time data layer for Lakehouse architectures.
+Apache Fluss is a streaming storage built for real-time analytics & AI which
can serve as the real-time data layer for Lakehouse architectures.
The release is available for download at:
https://downloads.apache.org/incubator/fluss/fluss-0.8.0-incubating/
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 c8f838d4b..c4a7f5f71 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
@@ -434,7 +434,7 @@ Subject: [ANNOUNCE] Apache Fluss Shaded 1.0-incubating
released
The Apache Fluss community is very happy to announce the release of Apache
Fluss Shaded 1.0-incubating.
-Apache Fluss is a streaming storage built for real-time analytics which can
serve as the real-time data layer for Lakehouse architectures.
+Apache Fluss is a streaming storage built for real-time analytics & AI which
can serve as the real-time data layer for Lakehouse architectures.
The release is available for download at:
https://downloads.apache.org/incubator/fluss/fluss-shaded-1.0-incubating/
diff --git a/website/docs/intro.md b/website/docs/intro.md
index acf3d79c5..c2d085863 100644
--- a/website/docs/intro.md
+++ b/website/docs/intro.md
@@ -6,7 +6,7 @@ slug: /
# What is Fluss?
-Fluss is a streaming storage built for real-time analytics which can serve as
the real-time data layer for Lakehouse architectures.
+Fluss is a streaming storage built for real-time analytics & AI which can
serve as the real-time data layer for Lakehouse architectures.
diff --git a/website/docusaurus.config.ts b/website/docusaurus.config.ts
index 7e8a99430..959c9e5c8 100644
--- a/website/docusaurus.config.ts
+++ b/website/docusaurus.config.ts
@@ -24,7 +24,7 @@ const { versionsMap, latestVersion } = loadVersionData();
const config: Config = {
title: 'Apache Fluss™ (Incubating)',
- tagline: 'Streaming Storage for Real-Time Analytics',
+ tagline: 'Streaming Storage for Real-Time Analytics & AI',
favicon: 'img/logo/fluss_favicon.svg',
// Set the production url of your site here
diff --git a/website/package.json b/website/package.json
index c17363c78..91c57d3c4 100644
--- a/website/package.json
+++ b/website/package.json
@@ -15,9 +15,10 @@
"typecheck": "tsc"
},
"dependencies": {
+ "@docsearch/core": "^4.5.0",
"@docusaurus/core": "^3.9.2",
- "@docusaurus/plugin-pwa": "^3.9.2",
"@docusaurus/plugin-client-redirects": "^3.9.2",
+ "@docusaurus/plugin-pwa": "^3.9.2",
"@docusaurus/preset-classic": "^3.9.2",
"@mdx-js/react": "^3.0.0",
"algoliasearch": "^5.10.2",
diff --git a/website/src/components/HomepageFeatures/index.tsx
b/website/src/components/HomepageFeatures/index.tsx
index 9adda4c44..09671c2ce 100644
--- a/website/src/components/HomepageFeatures/index.tsx
+++ b/website/src/components/HomepageFeatures/index.tsx
@@ -29,47 +29,41 @@ type FeatureItem = {
const FeatureList: FeatureItem[] = [
{
- title: 'Sub-Second Latency',
+ title: 'Sub-Second Data Freshness',
content:
- 'Fluss supports low-latency streaming reads and writes, similar to
Apache Kafka. Combined with Apache Flink, Fluss enables the creation of
high-throughput, low-latency streaming data warehouses, optimized for real-time
applications.',
+ 'Continuous ingestion and immediate availability of data enable
low-latency analytics and real-time decision-making at scale.',
Svg: require('@site/static/img/feature_real_time.svg').default
},
{
- title: 'Columnar Stream',
+ title: 'Streaming & Lakehouse Unification',
content:
- 'Fluss stores streaming data in a columnar format, delivering up
to 10x improvement in streaming read performance. Networking costs are
significantly reduced through efficient pushdown projections.',
- Svg: require('@site/static/img/feature_column.svg').default
+ '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.',
+ Svg: require('@site/static/img/feature_lake.svg').default
},
{
- title: 'Streaming & Lakehouse Unification',
+ title: 'Columnar Streaming',
content:
- 'Fluss unifies data streaming and the data Lakehouse by serving
streaming data on top of the Lakehouse. This allows for low latencies on the
Lakehouse and powerful analytics to data streams.',
- Svg: require('@site/static/img/feature_lake.svg').default
+ '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.',
+ Svg: require('@site/static/img/feature_column.svg').default
},
{
- title: 'Real-Time Updates',
+ title: 'Compute–Storage Separation',
content:
- 'The PrimaryKey Table supports real-time streaming updates for
large-scale data. It also enables cost-efficient partial updates, making it
ideal for enriching wide tables without expensive join operations.',
+ 'Stream processors focus on pure computation while Fluss manages
state and storage, with features like deduplication, partial updates, delta
joins, and aggregation merge engines.',
Svg: require('@site/static/img/feature_update.svg').default
},
{
- title: 'Changelog Generation & Tracking',
+ title: 'ML & AI–Ready Storage',
content:
- 'Updates generate complete changelogs that can be directly
consumed by streaming processors in real time. This allows to streamline
streaming analytics workflows and reduce operational costs.',
- Svg: require('@site/static/img/feature_changelog.svg').default
+ '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.',
+ Svg: require('@site/static/img/feature_query.svg').default
},
{
- title: 'Lookup Queries',
+ title: 'Changelogs & Decision Tracking',
content:
- 'Fluss supports ultra-high QPS for primary key point lookups,
making it an ideal solution for serving dimension tables. When combined with
Apache Flink, it enables high-throughput lookup joins with exceptional
efficiency.',
- Svg: require('@site/static/img/feature_lookup.svg').default
+ 'Built-in changelog generation provides an append-only history of
state and decision evolution, enabling auditing, reproducibility, and deep
system observability.',
+ Svg: require('@site/static/img/feature_changelog.svg').default
},
- // {
- // title: 'Interactive Queries',
- // content:
- // 'Fluss is queryable with query engines like Flink, enabling
direct data analytics. This reduces development complexity and simplifies
debugging.',
- // Svg: require('@site/static/img/feature_query.svg').default
- // },
];
function Feature({ title, content, Svg }: FeatureItem) {
diff --git a/website/src/pages/downloads.md b/website/src/pages/downloads.md
index 69624e1d4..dc1efc6ab 100644
--- a/website/src/pages/downloads.md
+++ b/website/src/pages/downloads.md
@@ -1,6 +1,6 @@
# Apache Fluss (Incubating) Downloads
-> Apache Fluss (Incubating) is a streaming storage built for real-time
analytics which can serve as the real-time data layer for Lakehouse
architectures.
+> Apache Fluss (Incubating) is a streaming storage built for real-time
analytics & AI which can serve as the real-time data layer for Lakehouse
architectures.
Apache Fluss 0.8.0 is the latest stable release.
