🚀 <!everyone> Apache Cloudberry (Incubating) 2.1 DEB/RPM packages are now available! You can now download convenience binaries directly from GitHub Releases: • Cloudberry 2.1 - https://github.com/apache/cloudberry/releases/tag/2.1.0-incubating • cloudberry-backup 2.1 - https://github.com/apache/cloudberry-backup/releases/tag/2.1.0-incubating • cloudberry-pxf 2.1 - https://github.com/apache/cloudberry-pxf/releases/tag/2.1.0-incubating This is the first release series providing official convenience binaries for the Cloudberry ecosystem. Thanks to everyone involved in packaging and release engineering work! 🙌 If any questions, please let us know!

Cloudberry Bi-Weekly meeting is coming in 20 minutes! 4:00 PM - 4:45 PM (UTC+8)/ 1100 1145 UTC+3 / 900 945 UTC+0 Meeting Notes: https://docs.google.com/document/d/14NLYVvApvijsQDt7uCKblVPKhayJSxb6na9dMAp5NAM/edit?usp=sharing Call link: meet.google.com/xug-bsvs-bci

🚀 Big milestone update from the Apache Cloudberry (Incubating) community! <!everyone> After nearly a year of work, the PostgreSQL kernel upgrade from PG 14.4 → PG 16.9 has finally been submitted as a large community PR 🎉 This upgrade brings many PostgreSQL 15/16 features and improvements into Cloudberry, including: • MERGE support • SQL/JSON enhancements • Logical replication improvements • Parallel VACUUM • pg_stat_io • Optimizer & Memoize improvements • WAL/storage enhancements • Security model upgrades • Many critical upstream fixes The community is now actively reviewing and stabilizing the merge. Since this is a very large PR, more reviewers, testers, and feedback are highly appreciated 🙌 • PR: https://github.com/apache/cloudberry/pull/1760 • Discussion thread: https://lists.apache.org/thread/r3m2ftz5mlpvovmmfm0727ph7y4cdgh3 Thanks to everyone who contributed to this huge effort ❤️

📺 Apache Cloudberry Bi-weekly Community Meeting (2026-05-22) recording is available now! Key updates from this meeting: • PostgreSQL 16 kernel upgrade milestone PR is entering review • Greenplum → Cloudberry in-place upgrade progress • Cloudberry Backup exporter & monitoring improvements • Java 21 support work for PXF • Deployment automation improvements with Ansible • AI development guidelines and AI-assisted workflows 🫱 Watch here: Thanks everyone for joining the discussions and contributing to the community! 🚀

#1771 :wave: Who is using Apache Cloudberry ? New discussion created by tuhaihe We want to express our sincere gratitude to all those who use and support the Apache Cloudberry. The Apache Cloudberry community is committed to improving Apache Cloudberry to enhance its community and ecosystem. We'd like to learn about the practical use cases of the Apache Cloudberry. Please feel free to submit your comment to let us know how you are using Apache Cloudberry. 🖋️ Submit your comment Just post a comment below in this GitHub discussion with some basic information: • Logo: your company/team/organization logo (Optional) • Name: your company/team/organization name • Website: your company/team/organization website • Usage Scenario: for what scenario do you use Apache Cloudberry • Contact info: eg, Email, LinkedIn, Twitter, etc (Optional) Note If this discussion notification bothers you, you can unsubscribe from it. apache/cloudberry

Hey <!here> 👋 The video recording for our latest Apache Cloudberry (Incubating) Bi-weekly Community Meeting (June 5th) is now live! 🎥 We had a fantastic, quick sync with the community. If you missed the live session, you can catch up on all the latest development updates and discussions right here: 👉 Feel free to drop any questions or thoughts in the channel. Huge thanks to everyone contributing to the project. See you at the next one! ☁️🫐

Hi All! Last months I spent to platformize Cloudberry — simplifying deployment and operation tasks and extending it with HashiCorp Vault. So I built a Kubernetes operator that turns all of that into a single declarative

CloudberryCluster

resource. Currently it is pre-release and i still working on data-loading, monitoring , helm tuning and bugs fixing. https://github.com/vyrodovalexey/cloudberry-k8s What you get: • Deploy — Helm install + one manifest, no manual

gpinitsystem

• Scale — change a field: scale-out w/ data redistribution, scale-in w/ PVC handling • Upgrade — rolling (mirrors → primaries → standby → coordinator) with auto-rollback • HA — segment mirroring, FTS auto-failover, WAL-streaming standby, segment recovery • Backup/restore — to S3 or PVC via native `gpbackup`/`gprestore`; on-demand, scheduled, retention • CLI —

cloudberry-ctl

instead of SSH-ing into pods Security — Vault-first 🔒 Cluster TLS issued by Vault PKI with auto-rotation, backup creds pulled from Vault (placeholder-only on disk, resolved at runtime), Vault Kubernetes auth — no bootstrap tokens. Auth — Keycloak Dual-mode Basic + OIDC: JWT validation w/ JWKS caching + role-claim extraction, mapped to a five-tier permission model. Observability — out of the box 📊 Prometheus metrics (reconciliation, FTS, scaling, mirroring, certs, backups); Cloudberry-tailored

postgres-exporter

+

cloudberry-query-exporter

sidecars; metrics → VictoriaMetrics (vmagent), logs → VictoriaLogs (Vector); Some raw Grafana dashboards. OpenTelemetry OTLP tracing (gRPC/HTTP) with span error recording via an OTel Collector. Batteries included — prepared images Ready-to-run images: the original Cloudberry DB built from the official Apache Cloudberry RPM on Rocky Linux (with

zstd

for backups), a backup-toolchain image (`gpbackup`/`gprestore`/`gpbackup_s3_plugin`/`gpbackman`), plus operator + CLI images. Happy to take questions or feedback 🙏

#1816 [Ideas] Description of backward-incompatible changes between Greenplum 6 and Cloudberry in the documentation. New discussion created by vovik0134 Description I propose adding a section to the Cloudberry documentation that describes backward-incompatible changes between Greenplum 6 and Cloudberry, regardless of their nature. Use case/motivation Our team is working on migrating from Greenplum 6 to Cloudberry, and during our research we have identified some backward-incompatible changes. Describing these backward-incompatible changes will help users prepare for migration and perform it in a more predictable way. I believe this scenario may also be relevant for other potential Cloudberry users and may help attract users who are planning to migrate from Greenplum 6. Related issues No response Are you willing to submit a PR? • Yes I am willing to submit a PR! apache/cloudberry

🚀 PostgreSQL 16 Upgrade Update Apache Cloudberry's main branch has successfully upgraded its PostgreSQL kernel from 14.4 to 16.9. To help users and contributors better understand the impact of this upgrade, we've published a detailed blog post summarizing major features, performance improvements, observability enhancements, security updates, and developer-facing changes introduced across PostgreSQL 15 and 16. Highlights include: • MERGE support • SQL/JSON enhancements • Parallel VACUUM • Memoize and optimizer improvements • pg_stat_io • Logical replication enhancements • Shared-memory statistics subsystem • Security and privilege model improvements The PostgreSQL 16 kernel is expected to be included in upcoming Cloudberry releases. 📖 Blog: https://cloudberry.apache.org/blog/postgresql16-for-apache-cloudberry-202606/ We'd love to hear your feedback and welcome testing from the community!

🎉 Exciting community news! Please join us in congratulating Anton Kurochkin (@woblerr) on becoming an Apache Cloudberry Committer! Anton has made fantastic contributions to cloudberry-backup and related Go tooling, including backup utilities, project modernization, roadmap discussions, and infrastructure improvements. Thank you for everything you've contributed, Anton! We're excited to continue building Apache Cloudberry together. 🚀 📖 Read the announcement: https://cloudberry.apache.org/blog/welcoming-anton-kurochkin-as-a-new-apache-cloudberry-committer/

Hi All, We are evaluating Apache Cloudberry (Incubating) for a production deployment and are looking for commercial support options. If you provide Cloudberry support services or can recommend a support partner, please DM me.

📢 New Migration Resource Available If you're planning a migration from Greenplum 6.x to Apache Cloudberry, check out this new guide contributed by community member vovik0134: 📖 cloudberry.apache.org/docs/sys-admin/migration-and-upgrade/backward-incompatible-changes-from-greenplum-6 The document summarizes compatibility changes across: • PostgreSQL kernel upgrades • SQL syntax and function behavior • Partitioning mechanisms • System catalogs and metadata • Configuration and resource management Every section includes: 🔍 Detection queries 🛠️ Recommended remediation steps This guide reflects many years of PostgreSQL evolution between Greenplum 6 (PostgreSQL 9.4-based) and modern Apache Cloudberry releases, making it especially useful for organizations planning a large-version upgrade. Huge thanks to vovik0134 for contributing this valuable resource to the Apache Cloudberry community! 🎉

📺 Apache Cloudberry Bi-weekly Community Meeting Recording is Available! The Apache Cloudberry ecosystem continues to grow. Recent highlights include: • 🚀 PostgreSQL 16 stabilization • 🔍 New extensions for interconnect observability and relation size monitoring • 🛡️ A new extension to prevent costly partition full scans • 🔐 Continuous CVE security updates • 📖 New Greenplum → Cloudberry migration guide • ⚙️ Progress on PXF, Cloudberry Backup, Release 2.2, and more Watch the recording to learn what's happening across the community! 🎥 📓 docs.google.com/document/d/14NLYVvApvij…/edit?tab=t.wvg9yii82vhl

Hello everyone, As I mentioned in my introduction post, I've created an kubernetes operator for Apache Cloudberry. The first public version was released today. Main features in this release: • Automatic coordinator / standby takeover • Automatic segment / mirroring takeover • Segment scale-up • Short-lived SSH certificates • And more I'd love to get your feedback and help make the operator more robust, so please test it out, and don't hesitate to reach out if you run into any issues. github.com/keldonio/keldon-operator

#1838 Keldon — Kubernetes Operator for Apache Cloudberry (looking for feedback) New discussion created by elhimad Hi everyone, I've been building Keldon, an open-source Kubernetes operator for Apache Cloudberry, and just shipped the first public release (v0.11.1). What it does: • Fully automated cluster bootstrap via

gpinitsystem

— coordinator, standby, segments, and mirrors, all provisioned declaratively from a single YAML • Horizontal scale-up: patch

spec.segments.count

, the operator provisions new pods and redistributes data automatically • Two SSH trust models: static keypair for dev/CI, certificate mode for production (per-cluster CA, short-lived certs, annotation-driven rotation without pod restarts) • Declarative

postgresql.conf

and

pg_hba.conf

management via

DatabaseConfig

• High availability out of the box: standby coordinator (WAL streaming, auto-promoted on failure) and mirror segments (one mirror per primary, auto-recovered via

gprecoverseg

) • On-demand backups to S3-compatible storage via

gpbackup

, with cross-cluster restore support • Phase-driven lifecycle:

PodsStarting

→

SSHReady

→

Initializing

→

Running

, with the operator reconciling continuously from there • Admission webhook that catches errors at the API boundary — cluster name length, HA node availability, invalid CRD references — before anything reaches a pod • Helm install, cert-manager for webhook TLS, Kubernetes 1.29+ Why I built it: Standing up a Cloudberry cluster is operationally heavy — SSH trust, gpinitsystem, segment registration, mirror setup, replication wiring. Keldon automates all of it so you can go from zero to a running MPP cluster without touching any of it manually. What I'm looking for: 1. Are there use cases or deployment patterns in the community I haven't accounted for? 2. Anything in the way Keldon models clusters that conflicts with how you think about Cloudberry architecture? 3. If you get a chance to try it, I'd love to hear what breaks — missing features / bug to fix Repo: github.com/keldonio/keldon-operator Docs: keldon.io/docs Happy to answer questions or take direction on anything missing. — Imad apache/cloudberry

🎉Congratulations to Liu Shengsong on becoming an Apache Cloudberry Committer! Welcome aboard! cloudberry.apache.org/blog/welcoming-liushengsong-as-a-new-apache-cloudberry-committer

🎥 The recording of our latest Apache Cloudberry Bi-weekly Community Meeting (July 10, 2026) is now available! Highlights from this meeting: • 🎉 Welcomed our new Committer Liu Shengsong • 🚀 Discussed Cloudberry 2.2 release preparation and PostgreSQL 16 stabilization • 🌐 Shared updates on cloudberry-pxf, cloudberry-backup, and Kubernetes Operator projects • 🛠️ Talked about improving release workflows, CI/CD, and documentation Thanks to everyone who joined the discussion and contributed! Watch the recording here: Feel free to share your feedback and join the ongoing discussions on our mailing lists and community channels. 🙌

🚀 Apache Cloudberry ecosystem keeps growing! We’re happy to share that Odyssey 1.5.1 has added support for Apache Cloudberry. This release improves PostgreSQL-compatible connection pooling with: • Extended protocol enhancements • Better pipelining performance • Pool balancing improvements • New metrics and observability features Welcome Odyssey to the Cloudberry ecosystem! 🎉 See more: postgresql.org/about/news/odyssey-151-released-3348

📢 Apache Cloudberry @ Community Over Code Asia 2026 If you'll be attending Community Over Code Asia in Beijing, come say hello! We'll be presenting multiple technical sessions, joining BoF discussions, hosting a community meetup, and welcoming everyone at the Apache Cloudberry booth. Whether you're already using Cloudberry or just curious about the project, we'd love to meet you and hear your ideas. 👉 Full schedule: cloudberry.apache.org/blog/apache-cloudberry-at-community-over-code-asia-2026 See you there! 👋

cloudberry 2.1 require libxerces-c-3.3.so but on readhat linux 9 libxerces-c-3.2 is available how can resolve this issue during installation of rpm

📺 Apache Cloudberry Bi-weekly Community Meeting Recording is Available Missed our latest community meeting? The recording is now available! In this meeting, we covered: • 🚀 Release and development updates • 🐘 Ongoing engineering work • 🌱 Ecosystem and community updates Watch the recording: Thanks to everyone who joined the discussion! We'd love to see more community members at future meetings.

#1875 Slow Data Insertion in Cloud Berry New discussion created by TanmayK2000 Hi, I am using Apache CLoudberry Datawarehouse for data insertion with the help of Apache Nifi i noticed that data insertion in Datawarehouse is very slow for eg i am transfering 17 million data from one table to other table which in Datawarehouse the insertion process is taking place from last 3 days and till now only 8 million data is transfer why insertion is slow any idea ?? apache/cloudberry

Hi All, What is the best approach to migrate data from greenplum 6.21 to Cloudberry 2.1? Can we get gpbackup and gprestore utilities rpm files? Thanks

#1877 why incubating the greenplum database again? New discussion created by sunnn Im intrigued to know why the incubation is happening for the same databse again as i remember there was hawq which was retired from apache long ago and also nowadays people dont even know about greenplum as many databases sucha as doris are available apache/cloudberry

Comment on #1877 why incubating the greenplum database again? Discussion answered by jianlirong Thanks for the question. The motivation behind Apache Cloudberry comes from several observations about the evolution of the PostgreSQL ecosystem over the past few years. First, Greenplum has accumulated many years of production experience and has been widely adopted across different industries. It also established itself as one of the most mature open-source MPP databases built on PostgreSQL. As the project evolved away from its previous open development model, we felt there was still a strong need in the community for a vendor-neutral, Apache-governed open-source successor that could continue serving users who value openness, long-term sustainability, and community-driven innovation. Second, Apache HAWQ and Apache Cloudberry were created to solve very different problems. HAWQ was designed as a SQL-on-Hadoop engine, with its architecture tightly integrated with the Hadoop ecosystem and based on an older PostgreSQL codebase. Cloudberry, on the other hand, is a distributed MPP database designed for modern analytics workloads, while continuously evolving together with newer PostgreSQL releases. Although the projects share some historical roots, their technical goals and target use cases are fundamentally different. Finally, the analytical database ecosystem has become much richer over the last decade. Excellent systems such as ClickHouse, Doris, and StarRocks have each established their own strengths and communities. At the same time, we continue to see strong demand for an open-source distributed database that combines: 1. close compatibility with modern PostgreSQL, 2. a proven shared-nothing MPP architecture, 3. rich SQL capabilities, 4. enterprise-grade stability and scalability, and 5. an open, community-governed development model. Apache Cloudberry is our effort to meet that demand. Rather than replacing existing systems, we hope to provide another strong option for users and organizations whose requirements align with these goals. Our goal is not to compete with any particular project, but to contribute another healthy and sustainable choice to the open-source ecosystem. We believe that diversity, open governance, and collaboration ultimately benefit both users and the PostgreSQL community as a whole. Lirong apache/cloudberry

#1886 Add LZO compression support to gpfdist New discussion created by ZTE-EBASE Description This PR adds LZO compressed file format read/write support to the

gpfdist

utility in Apache Cloudberry. Key Insight: LZO is specifically designed for speed over compression ratio. It's ideal for scenarios where decompression throughput matters more than storage savings - such as large-scale data loading into MPP databases like Cloudberry. Core Features Read Support (.lzo → Cloudberry): • ✅ Block-level decompression: Processes LZO data block by block, extracting uncompressed length and compressed length from each block header • ✅ Checksum verification: Validates data integrity using Adler32 and CRC32 checksums embedded in LZO blocks • ✅ Enhanced error reporting: Provides detailed, actionable error messages for various failure scenarios (truncated files, corrupt data, invalid format, checksum mismatches) Write Support (Cloudberry → .lzo): • ✅ Table data unloading: Exports table data to LZO-compressed external files • ✅ Standard LZOP format output: Generates files compatible with standard lzop tool and Hadoop LZO readers • ✅ Configurable compression level: Supports LZO compression levels (default: level 1, fastest; configurable up to level 9) Future Potential - Hadoop Ecosystem Integration: • 🔮 Direct query of Hive tables stored in LZO-compressed format on HDFS • 🔮 Seamless integration with Spark LZO Parquet output • 🔮 Accelerated data loading from Sqoop LZO imports Use case/motivation Scenario 1: High-Volume Data Loading LZO is a lightweight compression algorithm optimized for decompression speed (~500MB/s), making it ideal for scenarios requiring rapid data ingestion. Compared to BZip2 (~10MB/s) and GZIP (~100MB/s), LZO provides the fastest decompression while maintaining a reasonable compression ratio. Scenario 2: Hadoop Ecosystem Integration Many Hadoop ecosystem tools natively support LZO compression: 1. Hive: Supports LZO-compressed text and sequence files 2. Spark: Can write LZO-compressed output (via hadoop-lzo library) 3. Sqoop: Commonly uses LZO for bulk imports from RDBMS to HDFS References Technical Documentation • LZO Official Website • LZOP File Format Specification • Hadoop LZO Compression Guide Cloudberry Documentation • GPFDIST Official Docs • External Tables Guide Related Projects • Apache Cloudberry GitHub • Greenplum Database (upstream) Related issues No response Are you willing to submit a PR? • Yes I am willing to submit a PR! apache/cloudberry

📣 Apache Cloudberry August 2026 Incubation Report is out! <!everyone> Our latest incubation report covers the major progress from May through July 2026. Some highlights: • 🚀 PostgreSQL 16 kernel upgrade has been merged into

main

• 📦 Apache Cloudberry 2.2.0 has entered the release process • 🧊 Iceberg support has started in

datalake_fdw

• 🔧 Continued improvements to ORCA, planner, extensions, CI, security, and packaging • ☁️ Ecosystem projects including PXF, cloudberry-backup, cloudberry-go-libs, WAL-G, and Kubernetes operators continued to move forward • 👥 Anton Kurochkin and Liu Shengsong joined as new Committers • 🌏 Community engagement continued through Community Over Code Asia 2026 and other events Thanks to everyone who continues to contribute to Cloudberry — whether through code, reviews, documentation, testing, releases, or community discussions! 🙌 🫱🏻 Read the full incubation report: cloudberry.apache.org/blog/apache-cloudberry-incubation-report-202608

The recording of our latest Apache Cloudberry (Incubating) bi-weekly community meeting is available: Highlights include: • Recent PRs and feature discussions • Release-branch management and cherry-picking • Behave test automation and CI • Rocky Linux 10 support and release progress • Cloudberry ecosystem and website updates • Community events and Kubernetes operator collaboration Please watch the recording and share your thoughts with the community!

We’ve launched a new Size Calculator for Apache Cloudberry to help with hardware planning before starting a POC. Enter your uncompressed data size, choose a physical, VM, or cloud deployment, and get an estimated configuration covering nodes, CPU, memory, storage, networking, and primary/mirror layout. Advanced options also allow you to adjust compression ratio and query concurrency. It’s designed to provide a practical starting point for POC planning—not a replacement for workload validation. Try it here: cloudberry.apache.org/sizing Many thanks to @Ryan Wei for providing the prototype and the original idea!

#1939 Apache Cloudberry through ODBC into Apache Arrow (adbcBridge 0.1.0) — is multi-argument unnest a safe bulk-ingest path on Cloudberry? New discussion created by singhpratech adbcBridge is a small Apache-2.0 ADBC driver written in C11 that loads an ODBC driver and exposes it through the Arrow ADBC C ABI: block-cursor reads straight into Arrow record batches, bulk ingest, metadata, partitioned parallel reads. I ran Apache Cloudberry through it as one of 46 databases in a single compatibility workload, and it is one of the few entries that needed no driver quirks and no tolerance flags at all — so I wanted to share the entry here and ask one question at the end. What was verified (Apache Cloudberry 2.1.0-incubating,

woblerr/cloudberry

image; driver psqlodbc 16, PostgreSQL wire): • Linux: PASS • macOS arm64: PASS (amd64 emulated) • Windows x64: PASS (compose service unchanged, 3 GB / shm 1 GB) What the compatibility entry records: an MPP cluster of PostgreSQL 14 segments behind one coordinator, driven by the

postgres

entry's types unchanged (

INTEGER

,

DOUBLE PRECISION

,

VARCHAR

,

BYTEA

,

DATE

,

TIMESTAMP

,

NUMERIC(10,3)

,

BOOLEAN

all behave as on stock PostgreSQL) and, unlike CockroachDB, needing no

PRIMARY KEY

. Since it reports

SQL_DBMS_NAME

"PostgreSQL" behind the same

psqlodbcw.so

, no driver-name quirk could be correct here without also firing on real PostgreSQL; the only place Cloudberry is named in the bridge is a fork test on the

version()

banner. Extra steps cover what the standard workload cannot tell apart from PostgreSQL: a

DISTRIBUTED BY

table whose bulk-ingested rows occupy both segments plus an aggregate merged on the coordinator (

Gather Motion 2:1

, GPORCA), and append-optimized column-oriented storage read from

pg_am

as

ao_column

. Full entry: https://github.com/singhpratech/adbcbridge/blob/main/docs/COMPATIBILITY.md The question. For real PostgreSQL the bridge ingests through a multi-argument

unnest

form —

INSERT INTO t SELECT * FROM unnest($1::bigint[], $2::text[], …)

with one array parameter per column — and it only turns that on when

version()

is a PostgreSQL banner carrying no fork marker, so Cloudberry (banner

PostgreSQL 14.4 (Apache Cloudberry 2.1.0-incubating …)

) keeps the plain multi-row

INSERT

path. Probing Cloudberry directly, the

unnest

form works exactly as on PostgreSQL — from array literals and from bound `bigint[]`/`text[]` parameters, into heap, append-optimized row and append-optimized column tables, across the segments — and server-side it lands 5,000 rows roughly an order of magnitude faster than the multi-row

INSERT

it keeps (~530k vs ~33k rows/s, bare SQL on a shared host). Is relying on multi-argument

unnest

expansion something Cloudberry considers stable across releases, the same way PostgreSQL does — i.e. is it reasonable to let Cloudberry through that gate? If there is a caveat (GPORCA vs the planner, distribution of the unnested rows, anything on the 2.x roadmap), I would rather know before flipping it. Trying it (Python; Rust, Go, Java and C# are on the docs site):

pip install adbcbridge

import adbcbridge with adbcbridge.connect(uri="Driver=psqlodbcw.so;Servername=127.0.0.1;Port=5432;Database=mydb;Username=gpadmin;Password=…;") as conn: with conn.cursor() as cur: cur.execute("SELECT ...") table = cur.fetch_arrow_table() # a pyarrow.Table Links: repository https://github.com/singhpratech/adbcbridge · docs https://adbcbridge.org/docs/ · upstream notes https://github.com/singhpratech/adbcbridge/blob/main/docs/UPSTREAM.md · PyPI https://pypi.org/project/adbcbridge/ It is a 0.1.0. If the entry says something wrong about Cloudberry, or you run a version I didn't, an issue on the repository with the details is the most useful thing you could send. apache/cloudberry