Received: from malur.postgresql.org ([217.196.149.56]) by arkaria.postgresql.org with esmtps (TLS1.3) tls TLS_ECDHE_RSA_WITH_AES_256_GCM_SHA384 (Exim 4.94.2) (envelope-from ) id 1v98pZ-00AaBh-Bz for pgsql-admin@arkaria.postgresql.org; Wed, 15 Oct 2025 21:14:44 +0000 Received: from localhost ([127.0.0.1] helo=malur.postgresql.org) by malur.postgresql.org with esmtp (Exim 4.94.2) (envelope-from ) id 1v98pY-008L0g-Aj for pgsql-admin@arkaria.postgresql.org; Wed, 15 Oct 2025 21:14:43 +0000 Received: from makus.postgresql.org ([2001:4800:3e1:1::229]) by malur.postgresql.org with esmtps (TLS1.3) tls TLS_ECDHE_RSA_WITH_AES_256_GCM_SHA384 (Exim 4.94.2) (envelope-from ) id 1v98pX-008L0W-S4 for pgsql-admin@lists.postgresql.org; Wed, 15 Oct 2025 21:14:43 +0000 Received: from mail-pl1-x629.google.com ([2607:f8b0:4864:20::629]) by makus.postgresql.org with esmtps (TLS1.3) tls TLS_ECDHE_RSA_WITH_AES_128_GCM_SHA256 (Exim 4.96) (envelope-from ) id 1v98pV-001y3s-0j for pgsql-admin@lists.postgresql.org; Wed, 15 Oct 2025 21:14:42 +0000 Received: by mail-pl1-x629.google.com with SMTP id d9443c01a7336-27eec33b737so646455ad.1 for ; Wed, 15 Oct 2025 14:14:41 -0700 (PDT) DKIM-Signature: v=1; a=rsa-sha256; c=relaxed/relaxed; d=gmail.com; s=20230601; t=1760562880; x=1761167680; darn=lists.postgresql.org; h=to:subject:message-id:date:from:mime-version:from:to:cc:subject :date:message-id:reply-to; bh=PlI9gT9QRY/BLS2PD3kcXYWvEyaX50qyeU0ZYM2EVOY=; b=b/vBY/D6/qyGHjpZ3QulHdJ4SsvzVWJgaSpvXk+HNXZz/IqBO7ZwVRpXP/CmqKjVWC Z5RSuRk220zqeHewtOL8rHVLvbvNNsL1TsflDfxZ3L8MGt6bpdaDiXSVyCsl9whg4fBz g0ORMsLZiqyRRg0xLVLJANPCGVwa1SW29L/+nbXkkdgJNjaKHbwNO10/T7OMKM8Dlswv yPfK3hfRktWvRPd2tMPawbs5Noe2E+pJHGQUx1+zwzF5ZwgFdeTJTScEKc5tO/eXwqNQ dV567uuqUxYb4eRzajd91aJelKwJ4cRhT3jhlIrtnz/2exVzJ9XBt9MHrJN2C5bgoRa8 mjLw== X-Google-DKIM-Signature: v=1; a=rsa-sha256; c=relaxed/relaxed; d=1e100.net; s=20230601; t=1760562880; x=1761167680; h=to:subject:message-id:date:from:mime-version:x-gm-message-state :from:to:cc:subject:date:message-id:reply-to; bh=PlI9gT9QRY/BLS2PD3kcXYWvEyaX50qyeU0ZYM2EVOY=; b=RZ+4TqDmCvAQQFOr+ceHDoc8usKyT5rTbc2FFCp2LzAmLJ5xaft08hIeWwfPlRsjQm Nw07WN+wPguKTk0i+SCFxwhYWT76n3pAXOaXxy8L+fSlP57uFACK4APNTtbLxzgTFpgP 5y2X1sBraL84i+7lpUEYlkf7CUrvfqrZEGfllgvEiHSfwklYCNc8kXFtBHLmXbUj/P1M SpEpXWvpnRrhK2R8neHjwieJawKG5cqYi7Smd9u14Vyg/TJnhz8kFlrYD2BgtFq+Uo1I PBSRZdsNr7AyQcpf5I8iI8EyKWGfzZr09yUzv2jj5T1vztiLRNqcbk01KOIyDh9UmUow Ej+A== X-Gm-Message-State: AOJu0YyAUT0wLP4ULTPXyovIA3StXRr+IMALnOlf0BcR3JSUBUAT2fA5 VPyhgN/YffoaLMXGhPUMNn+W8Fq8x4jsl0zGETDEpgEj+heocWiCIgW6RP9ol5tg+crfeaiWkzS dX/2YyZkWnrxhzPA1k3ZyefM8DtTHborso4h3 X-Gm-Gg: ASbGncti96CxncQ1rkGd+eTCDyRiopOe/PH199RoBz7d2K368t7THV2h3YcjwYTc53c pkIephH1UMlGQHK3AQxI+S5rDz7HLwdVNbiSVV3Lm150REih7qTKj4sZ/j3Z0axE9R+h/2gz7Qj rwwaq933rmufO+eFI08Lm9enUynk8V1jf5ymXcMABkNRYZ3JgYCjXw3Z4mTzMg7Qj470GOVOozw PtflVh/6l4y4ahrrONs2KWS9ODOqOXJbqgFUC2eRP7reaPoHQEy/OZtcKSlSa07FqwyFHRQtwnG hNZsEC0= X-Google-Smtp-Source: AGHT+IGhk7Oj1Lh/VFMwtJfBSxtHLF39hYm7KfG23DLHgsXCCoWv0DrPd7+/DGvUvvMgi17UpfFitdCaS9oDQKKog8Y= X-Received: by 2002:a17:903:1585:b0:267:af07:6526 with SMTP id d9443c01a7336-29027303346mr383866605ad.55.1760562879905; Wed, 15 Oct 2025 14:14:39 -0700 (PDT) MIME-Version: 1.0 From: mahamood hussain Date: Thu, 16 Oct 2025 02:44:26 +0530 X-Gm-Features: AS18NWAY4Bh10F9svIwdsHi4NZch3Nf8AZDUfw30ArYag4SGkE10JUg3HKu0Sx4 Message-ID: Subject: Guidance Requested: Migrating Large-Scale DB2 Databases to PostgreSQL To: Pgsql-admin Content-Type: multipart/alternative; boundary="0000000000000fc495064138fd59" List-Id: List-Help: List-Subscribe: List-Post: List-Owner: List-Archive: Archived-At: Precedence: bulk --0000000000000fc495064138fd59 Content-Type: text/plain; charset="UTF-8" Content-Transfer-Encoding: quoted-printable Hi Team, We are in the process of migrating several DB2 databases to PostgreSQL, primarily to reduce the high licensing costs associated with DB2. These databases support retail applications (e.g., supermarkets and stores), and during peak hours, we anticipate over 100 concurrent connections. ------------------------------ Current Database Profile: - Approximately 3,000 tables in total - Around 100 tables contain active data - Most tables have low data volume - A few large tables range from 10 GB to 2 TB - The largest table contains approximately 80 billion rows ------------------------------ Migration Approach: - We are using Ispirer for code conversion (DB2 to PostgreSQL). - For data migration, we are evaluating Fivetran, but noted that it relies on the COPY method for data loading. ------------------------------ Questions & Areas Where We Need Guidance: 1. Is Fivetran a suitable option for migrating very large datasets (e.g., tables with 80+ billion rows)? 2. Are there any reliable open-source tools for DB2 to PostgreSQL data migration that we can use internally, without needing to invest in a too= l like Fivetran? 3. Are there more scalable or efficient alternatives for both the initial load and ongoing/incremental sync to PostgreSQL? ------------------------------ Additional Input Requested: - What are the key best practices (Do=E2=80=99s and Don=E2=80=99ts) to kee= p in mind during a large-scale DB2 =E2=86=92 PostgreSQL migration? - Are there specific PostgreSQL settings or configurations we should pay attention to for optimizing performance, especially for large datasets a= nd DB2-style workloads? ------------------------------ We are keen to ensure performance, data integrity, and scalability throughout this migration. Any insights=E2=80=94particularly from those wit= h experience in similar large-scale PostgreSQL implementations=E2=80=94would = be highly appreciated. If this is not the right forum for these questions, please do let me know if there is a better place to seek this guidance. Thanks in advance for your support! --0000000000000fc495064138fd59 Content-Type: text/html; charset="UTF-8" Content-Transfer-Encoding: quoted-printable

Hi Team,

We are= in the process of migrating several DB2 databases to PostgreSQL, primarily= to reduce the high licensing costs associated with DB2. These databases su= pport retail applications (e.g., supermarkets and stores), and during peak = hours, we anticipate over 100 concurrent connections.


Current Database Profile:

  • Approximately 3,000 tables in total

  • Around 100 tables contain active data

  • Most tables have low data volume

  • A few large tables range from 10 GB to 2 TB

  • The largest table contains approximately 80 billion rows


Migration Approach:<= /h3>
  • We are using Ispirer for code conversion (DB2 to PostgreSQL).

  • For data migration, we are evaluating Fivetran, but noted that it relies= on the COPY method for data loading.


Questions & Areas Where= We Need Guidance:

  1. Is Fivetran a suitable option for migrating very large datasets (e.g., t= ables with 80+ billion rows)?

  2. Are there any reliable open-source tools for DB2 to PostgreSQL data migr= ation that we can use internally, without needing to invest in a tool like = Fivetran?

  3. Are there more scalable or efficient alternatives for both the initial l= oad and ongoing/incremental sync to PostgreSQL?


Additional Input Requested:=

  • What are the key best practices (Do=E2=80=99s and Don=E2=80=99ts) to kee= p in mind during a large-scale DB2 =E2=86=92 PostgreSQL migration?

  • Are there specific PostgreSQL settings or configurations we should pay a= ttention to for optimizing performance, especially for large datasets and D= B2-style workloads?


We are keen to ensure performance, data integrity, and scalabil= ity throughout this migration. Any insights=E2=80=94particularly from those= with experience in similar large-scale PostgreSQL implementations=E2=80=94= would be highly appreciated.

If this is not the right forum for these= questions, please do let me know if there is a better place to seek this g= uidance.

Thanks in advance for your support!

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