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PeerDB-io
peerdb
Go2023–2026
PeerDB-io / peerdb

peerdb

Fast, Simple and a cost effective tool to replicate data from Postgres to Data Warehouses, Queues and Storage

5Distinct people
20Mentions
0Explicit recommenders
3.3KGitHub stars
REPOSITORY AT A GLANCE

What to know before exploring

What it is

Fast, Simple and a cost effective tool to replicate data from Postgres to Data Warehouses, Queues and Storage

GitHub

Where it is used

No documented product use has been verified yet.

What people are saying

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Also in these discussions

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This week on Hacker News

Nov 7–Nov 14 UTC · Direct repository links and separately labeled related project stories. Indexed through 11/14/2026, 1:49:46 PM UTC.

No direct repository links were found in the indexed HN discussions over the past seven days. Older discussions are available below.

Mentions over time

HN mentions by year20 dated mentions

Observed mentions: 2023-07-27 15:39:08 UTC to 2026-06-28 13:25:05 UTC.

02468102023-01-01 00:00:00 UTC to 2024-01-01 00:00:00 UTC (exclusive): 2 mentions; 1 submissions, 1 comments20232024-01-01 00:00:00 UTC to 2025-01-01 00:00:00 UTC (exclusive): 10 mentions; 2 submissions, 8 comments20242025-01-01 00:00:00 UTC to 2026-01-01 00:00:00 UTC (exclusive): 7 mentions; 1 submissions, 6 comments2026-01-01 00:00:00 UTC to 2027-01-01 00:00:00 UTC (exclusive): 1 mentions; 0 submissions, 1 comments. Incomplete calendar period.2026*

* An incomplete calendar period is marked with an outlined bar. Its count is not directly comparable with a full period.

Counts come from the repository’s dated source evidence. Index cutoff: 2026-11-02 08:16:59 UTC.

View mention counts and date ranges
UTC ranges include their start and exclude their end. Select a period to filter the source evidence.
PeriodStart (UTC)End (exclusive, UTC)MentionsSubmissionsComments
20232023-01-01 00:00:00 UTC2024-01-01 00:00:00 UTC211
20242024-01-01 00:00:00 UTC2025-01-01 00:00:00 UTC1028
20252025-01-01 00:00:00 UTC2026-01-01 00:00:00 UTC716
2026 (partial)2026-01-01 00:00:00 UTC2027-01-01 00:00:00 UTC101

What Hacker News says

20 sources
++ We’re big Go fans, most of PeerDB is written in Go: https://github.com/PeerDB-io/peerdb The importance of optimizing (resource) margins and having predictable memory usage increases significantly in the DBaaS/Postgres world, where your process coexists and competes with other critical workloads. Also, WAL-RUS isn’t rocket science. Postgres already exposes a bunch native constructs for WAL archival, making development fairly straightforward even in Rust. TL;DR: when to choose Rust or Go really depends on the workload and what you are going after.
In WAL-RUS: a Rust Rewrite of WAL-G for PostgreSQL Backups
> "As part of the acquisition, we made an important decision: not only to keep PeerDB open source" > "Here goes the Open Source reference to our validation logic." > "PeerDB Open Source Repository" I hate to be that guy, but PeerDB seems to be governed by the Elastic License [1] which makes it NOT open source. The difference is not small, but significant for many. For one, it won't get integrated into other OSS projects. In my particular case, we have integrated Debezium Embedded into StackGres, as a high level object (CRD) named SGStream [2]. It allows Postgres logical replication from Postgres and exports to another Postgres and/or CloudEvents. No Kafka required. We'd love to consider other alternatives like PeerDB, but not being OSS is a red line we can't cross (having said that, we're really happy with Debezium in general, but having
Read the rest
In Lessons from a year of Postgres CDC in production
Great question! If you’re starting a greenfield application, pg_clickhouse makes a lot of sense since you’ll be using a unified query layer for your application. Now, coming to your question about replication: you can use PeerDB (acquired by ClickHouse https://github.com/PeerDB-io/peerdb), which is laser-focused and battle-tested at scale for Postgres-to-ClickHouse replication. Once the data is replicated into ClickHouse, you can start querying those tables from within Postgres using pg_clickhouse. In ClickHouse Cloud, we offer ClickPipes for Postgres CDC/replication, which is a managed service version of PeerDB and is tightly integrated with ClickHouse. Now there could be non-transcational tables that you can directly ingest to ClickHouse and still query using pg_clickhouse. So TL;DR: Postgres for OLTP; ClickHouse for OLAP; PeerDB/ClickP
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ipes for data replication; pg_clickhouse as the unified query layer. We are actively working on making this entire stack tightly integrated so that building real-time apps becomes seamless. More on that soon! :)
In Pg_ClickHouse: A Postgres extension for querying ClickHouse
Great question, exactly CDC from Postgres to ClickHouse and adapting the application to start using ClickHouse for analytics. Through the PeerDB acquisition, ClickHouse now has native CDC capabilities that work at any scale (few 10s of GB to 10s of TB Postgres databases). You can use ClickPipes if you’re on ClickHouse Cloud, or PeerDB if you’re using ClickHouse OSS. Sharing a few links for reference: https://clickhouse.com/docs/integrations/clickpipes/postgres https://github.com/PeerDB-io/peerdb https://clickhouse.com/cloud/clickpipes/postgres-cdc-connect... https://clickhouse.com/blog/clickhouse-acquires-peerdb-to-bo... Here is a short demo/talk that we did at our annual conferemce Open House that talks about this reference architecture https://clickhouse.com/videos/postgres-and-clickhouse-the-de...
In ClickHouse vs PostgreSQL UPDATE performance comparison
Sai from ClickHouse here. Have been living and breathing past year helping customers integrating Postgres and ClickHouse together. Totally agreed with this statement - there are numerous production grade workloads solving most of their data problems using these 2 purpose-built Open Source databases. My team at ClickHouse has been working hard to make the integration even seamless. We work on PeerDB, an open source tool enabling seamless Postgres replication to ClickHouse https://github.com/PeerDB-io/peerdb/ This integration is now also natively available in the Cloud through ClickPipes. The private preview was released just last week https://clickhouse.com/cloud/clickpipes/postgres-cdc-connect...
In 7 Databases in 7 Weeks for 2025
Great question! PeerDB can be just run on a single EC2 instance (using either Docker or Helm charts). A typical production-grade setup could use 4 vCores with 16GB RAM, You can scale up or down based on resource usage for your workload. To elaborate more on the architecture (https://docs.peerdb.io/architecture), the flow-worker does most of the heavy lifting (actual data movement during initial load and CDC), while the other components are fairly lightweight. Allocating around 70-80% of provisioned resources to the flow-worker is a good estimate. For Temporal, you could allocate 20-25% of resources and distribute the rest to other components. Our open-source offering (https://github.com/PeerDB-io/peerdb) supports multiple connectors (CH and non-CH). Currently, there aren’t any plans to make changes on that front!
In pg_flo – Stream, transform, and re-route PostgreSQL data in real-time
Sai from PeerDB here. Temporal has been very impactful for us and a major factor in our ability to build a production-grade product that supports large-scale workloads. At a high level, CDC is a complex state machine. Temporal helps building the state machine taking care of auto-retries/idempotency at different failure points and also aids in managing and observing it. This is very useful to identify root causes when issues arise. Managing Temporal shouldn’t be complex. They offer a well-maintained, mature Docker container. From a user standpoint, the software is intuitive and easy to understand. We package the temporal docker container in our own Docker setup and have it integrated into our Helm charts. We’ve quite a few users smoothly using Enterprise (that we open sourced recently) and standard OSS! https://github.com/PeerDB-io/peerdb/
Read the rest
In pg_flo – Stream, transform, and re-route PostgreSQL data in real-time

Show HN: Peerdb Streams – Simple, native Postgres change data capture

Hello HN, I am Sai Srirampur, one of the Co-founders of PeerDB. (https://github.com/PeerDB-io/peerdb). We spent the past 7 months building a solid experience to replicate data from Postgres to data warehouses. Now we're expanding to queues. PeerDB Streams provides a simple and native way to replicate changes as they happen in Postgres to Queues (Kafka, Redpanda, Google PubSub, etc). We use Postgres logical decoding to enable Change Data Capture (CDC). Blog post here: https://blog.peerdb.io/peerdb-streams-simple-native-postgres.... 10-min quickstart here: https://docs.peerdb.io/quickstart/streams-quickstart. We chose queues as many users found that existing tools are complex. Debezium is the most used tool for this use-case. It has large production usage. However, a common pain point among our users is that it has a significant learning cu
Read the rest
rve taking months to productionize. A few issues are: a) Interacting through a command line interface, understanding the various settings, and learning best practices for running it in production is not trivial. Debezium UI, released to address usability concerns [1], is still in an incubating state [2]. Additionally, reading Debezium resources to get started can be overwhelming [3]. b) Supporting data formats and transformations isn’t easy. It needs a Java project, building JAR packages and setting up a runtime path on the kafka connect plugin. c)Debezium is not as native as Kafka for other queues and doesn’t offer the same level of configurability. For example, with Event Hubs, it is difficult to stream to topics spread across namespaces and subscriptions. TL;DR Debezium aims to provide a comprehensive experience for engineers to implement CDC rather than making it dead simple for them. So you can do a lot with Debezium but need to know a lot about it. At PeerDB, we are building a simple yet comprehensive experience for Postgres CDC. The goal is to enable engineers to build prod-grade Postgres CDC with a minimal learning curve, within a few days. PeerDB’s feature-set isn't at Debezium's level yet, and as we evolve, we might face similar challenges. However, we're putting usability at the forefront and we believe that we can achieve the above goal. First, PeerDB offers a simple UI to set up Postgres and Kafka by creating PEERs and initiating CDC by creating a MIRROR. Through the UI, users can monitor the progress of CDC, including throughput and latency; set up alerts to Slack/Email based on replication slot growth; investigate Postgres-native metrics, including slot size, etc. Here is a demo showing of PeerDB UI in action: https://www.loom.com/share/ebcfb7646a1e48738835853b760e5d04 Second, for users who prefer a CLI, we provide a Postgres-compatible SQL layer to manage CDC. This offers the same level of features as the UI and is more intuitive compared to bash scripts. Third, users can perform row-level transformations using Lua scripts executed at runtime. This enables features such as encrypting/masking PII data, supporting various data formats (JSON, MsgPack, Protobuf, etc.), and more. We offer a script editor along with a bunch of useful templates [5]. Fourth, we provide native connectors to non-Kafka targets. We also provide native configurability options tailored to these platforms. For example, with Event Hubs, users can perform CDC to topics distributed across different namespaces and subscriptions [4]. Finally, We are laser focused on Postgres, enabling specific optimizations like native metrics for replication, wait-events, and # of connections. Features like faster initial loads through parallel snapshotting and decoding transactions in-flight are in private beta. Our hope is to provide the best data-movement experience for Postgres. PeerDB Streams is another step in that direction. We would love to get your feedback on product experience, our thesis and anything else that comes to your mind. It would be super useful for us. Thank you! References: [1] https://debezium.io/blog/2020/10/22/towards-debezium-ui/ [2] https://debezium.io/documentation/reference/stable/operation... [3] https://medium.com/@cooper.wolfe/i-hated-debezium-so-much-i-... [4] https://blog.peerdb.io/enterprise-grade-replication-from-pos... [5] https://github.com/PeerDB-io/examples [5] https://app.peerdb.cloud [6] https://github.com/PeerDB-io/PeerDB
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