10 ms·

MVCC – the part of PostgreSQL we hate the most (2023)

• terminalbraid 2y ago
  https://news.ycombinator.com/item?id=41892830 https://news.ycombinator.com/item?id=41892830
  • metadat 2y ago
    Thanks for pointing this out, it's an existing discussion started half a day ago with 5 comments: The Part of PostgreSQL We Hate the Most (2023) https://news.ycombinator.com/item?id=41892830 https://news.ycombinator.com/item?id=41892830
  • deleted 2y ago
    [deleted]
  • infogulch 2y ago
    @dang maybe merge these threads?
    • wordofx 2y ago
      No
  • evanelias 2y ago
    The overall topic was also discussed extensively in this subthread from 6 days ago: https://news.ycombinator.com/item?id=41837317 https://news.ycombinator.com/item?id=41837317
• hlandau 2y ago
  With every new PostgreSQL release we see yet more features and sugar added to the frontend, yet seemingly no meaningful improvement to the backend/storage layer which suffers these fundamental problems. I wish the PostgreSQL community would stop chasing more frontend features and spend a concerted few years completely renovating their storage layer. The effort in each release seems massively and disproportionately skewed towards frontend improvements without the will to address these fundamental issues. It's absurd that in 2024, "the world's most advanced open source database" doesn't have a method of doing upgrades between major versions that doesn't involve taking the database down. Yes, logical replication exists, but it still doesn't do DDL, so it has big caveats attached.
  • factormeta 2y ago
    what about https://github.com/orioledb/orioledb https://github.com/orioledb/orioledb ?
  • paulryanrogers 2y ago
    > a method of doing upgrades between major versions that doesn't involve taking the database down. For large instances this is a big ask, especially of a project without single person in charge. MySQL does have better replication, yet still often requires manually setting that up and cutting it over to do major version upgrades.
  • jandrewrogers 2y ago
    The design of good storage layers in databases is deeply architectural. As a consequence, it is essentially a "forever" design decision. Fundamentally changing the storage architecture will alter the set of tradeoffs being made such that it will break the assumptions of existing user applications, which is generally considered a Very Bad Thing. The existing architecture, with all its quirks and behaviors, is part of the public API (see also: Hyrum's Law). In practice, the only way to change the fundamental architecture of a database is to write a new one, with everything that entails.
    • Negitivefrags 2y ago
      You could select which storage approach on a per table level. That way the new characteristics don’t surprise anyone.
      • emptiestplace 2y ago
        This is the MySQL approach, but it isn't without downsides - consistency, predictability, etc.
  • quotemstr 2y ago
    Better yet: decouple front and back ends. Let them talk over a stable interface and evolve independently. The SQLite ecosystem is evolving in this direction, in fits and starts.
• gacklecackle 2y ago
  [dead]
• hn_throwaway_99 2y ago
  Wow, as someone who feels like I'm decently familiar with the ins and outs of Postgres, I thought this was a great article and I learned a ton. It seems like one of the biggest fundamental flaws is that Postgres chose the O2N approach for tracking row versions instead of N2O. While switching to N2O wouldn't solve all problems (e.g. the article also talks about how Postgres stores full row copies and not just diffs), from an "80/20 rule" perspective, it seems like it would get rid of most of the downsides with the current implementation. For example, I'd assume that the vast majority of the time that transactions want the latest row version, so using the N2O ordering means you could probably do away with storing each row version in an index, as you'd only need to traverse the linked list of you needed an older version, which should be much less common.
  • topherjaynes 2y ago
    You should check out Andy's History of Databases (CMU Databases / Spring 2020) on youtube. He does the entire first class from the streets of Amsterdam because he can't get in his hotel... he's an interesting character and he's insanely good at explaining the ins and out
    • Tostino 2y ago
      The content that his group puts out on YouTube is great. Been a little while since I caught up, but I was extremely impressed.
• deleted 2y ago
  [deleted]
• globular-toast 2y ago
  The article says the benefit of O2N is there's no need to immediately update indexes, but then goes on to say postgres updates the indexes anyway! So is there actually any advantage to O2N at all?
  • apavlo 2y ago
    If all table pages exist in memory and you are using cooperative GC, then O2N can be preferable. As workers scan version chains, they can clean up dead tuples without taking additional locks. This is what Microsoft Hekaton does.
  • kikimora 2y ago
    Good question! Also they point out that famous Uber article erroneously mentions write amplification caused by what they thought was N2O. IDK if write amplification is real or not. But if it is really O2N then there is no apparent reason for write amplification and entire Uber article might had been based on the wrong premise.
    • jeltz 2y ago
      That article was just wondering pain bad, written by someone who was obviously a beginner to PostgreSQL and did not understsand the issue he was seeing. Yes, there are real issues but that article should be ignored.
• nightfly 2y ago
  > MySQL and Oracle store a compact delta between the new and current versions (think of it like a git diff). Doesn't git famously _not_ store diffs and instead follows the same storage pattern postgres uses here and stores the full new and old objects?
  • jmholla 2y ago
    That is correct. Each version of a file is a separate blob. There is some compression done by packing to make cloning faster, but the raw for git works with is these blobs.
    • thaumasiotes 2y ago
      [flagged]
      • simonw 2y ago
        Saying "that's incorrect" is a lot more productive than saying "that's a lie". Calling something a lie implies that the incorrect information was deliberate.
      • ori_b 2y ago
        Git does both. When you create a commit, it stores a full (zipped) copy of the object, without any deltas. Periodically (I believe it used to be every thousand commits, though I'm not sure what the heuristic is today), git will take the loose objects and compress them into a pack. The full blob format is how objects are manipulated by git internally: to do anything useful, the objects need to be extracted from the blob, with all deltas applied, before anything can be done with them. It's also worth nothing that accessing a deltified object is slow (O(n) in the number of deltas), so the length of the delta chain is limited. Because deltification is really just a compression format, it doesn't matter how or where the deltas are done -- the trivial "no deltas" option will work just fine if you want to implement that. You can trivially verify this by creating commits and looking in '.git/objects/*' for loose objects, running 'git repack', and then looking in '.git/objects/pack' for the deltified packs.
      • 2y ago
• vinnymac 2y ago
  The part I hate the most is that in 2024 I still need a connection pooler (such as pgbouncer) in front of it to make it usable.
  • bvrmn 2y ago
    Let me guess, PHP?
    • nobleach 2y ago
      I see this pattern all over the place, not just PHP. When leveraging containers, what's a better option? Certainly Java, Rust, even NodeJS all have decent enough connection pools for PG. But telling those apps that are running in those containers, "uhhh, you're just one among many so, your pooling strategy may not represent reality". I've seen folks try to solve this by literally doing replica math when an app boots up (are there 8 replicas running? ok, divide Postgres' default 100 connections by that). Moving the pool outside the app container seems like a better move.
• avg_dev 2y ago
  pretty informative. now i understand why people are often having issues with vacuum-related stuff. i like the diagrams too.
• fweimer 2y ago
  The big advantage is that you do not need any extra space if your workload mostly consists of INSERTs (followed by table drops). And it's generally unnecessary to split up insertion transactions because there is no size limit as such (neither on the generated data or the total count of rows changed). There is a limit on statements in a transaction, but you can sidestep that by using COPY FROM if you do not have to switch tables too frequently. From a DBA point of view, there is no need to manage a rollback/undo space separately from table storage. Every application is a bit different, but it's not that the PostgreSQL design is a loser in all regards. It's not like bubble sort.
  • indulona 2y ago
    > but it's not that the PostgreSQL design is a loser in all regards the article literally says that pg's mvcc design is from the 90s and no one does it like that any more. that is technology that is outdated by over 30 years. i'd say it does not make it a loser in all regards, but in the most important aspects.
    • naranha 2y ago
      At least couchdb is also append only with vacuum. So it's maybe not completely outdated.
      • jbellis 2y ago
        High performance has never been a reason to use couchdb.
    • mikeocool 2y ago
      When it comes to your data store, some people might consider using technology that’s been reliably used in production by many organizations for 30 years a feature not a bug. I’d prefer not to be the first person running up against a limit or discovering a bug in my DB software.
      • mannyv 2y ago
• indulona 2y ago
  [flagged]
  • vrosas 2y ago
    I’ve been trashed for suggesting as much. People here seem to think any team or startup not choosing Postgres is committing some type of negligence.
    • rnewme 2y ago
      To be fair that's sort of a possotive self fulfilling propercy. The more it's used the better it's going to get.
• derefr 2y ago
  Question: is storing full new row-tuple versions something fundamental to Postgres as a whole, or is it just a property of the default storage engine / “table access method”?
  • paulddraper 2y ago
    You could store partial tuples without disrupting the interface. Though full tuples is pretty fundamental to the underlying implementation....MVCC, VACUUM, etc. It'd be a massive change to say the least.
  • dfox 2y ago
    From the PQ protocol PoV the way how this works is pretty much irrelevant, but the actual implementation of PostgreSQL contains ridiculous amount of places that depend on the “backward” MVCC implementation of the tuple heaps.
• msie 2y ago
  Nicely written article. Easy to read and understand!
• fforflo 2y ago
  OrioleDB was supposed to tackle this problem with a new storage engine . https://github.com/orioledb/orioledb https://github.com/orioledb/orioledb
  • kiwicopple 2y ago
    (I’m on the Supabase team) Oriole has joined us at supabase now and it’s being worked on full time by Alexander and his team. Here is the patch set: https://www.orioledb.com/docs#patch-set https://www.orioledb.com/docs#patch-set It will be available to try on the supabase platform later this year too
    • fforflo 2y ago
      Yeah, I've been keeping an eye on the pgsql-hackers discussions. Alexander+team are doing great work.
    • justinclift 2y ago
      As a data point, there are easily noticeable typos on that docs page. Might be a good idea to have someone run a spell checker over it at some point?
    • philippemnoel 2y ago
      The whole ParadeDB team is really excited for OrioleDB and Supabase to ship this :) It's long overdue in the Postgres ecosystem!
• thr0w 2y ago
  Don't agree with their characterization of `pg_repack`. `VACUUM FULL` is definitely crushing, but that's why repack exists as a faster/lighter alternative. Anyone have a different experience?
  • dfox 2y ago
    pg_repack is an hack-ish solution to do what VACUUM FULL does without completely locking the relation in question. But well, when you care about either of these things, your workload has significant issues, with the typical case being using pgsql as a backend for something that was originally a thick client designed for some kind of RDBMS based on shared files (InterBase mentioned in TFA, MS Jet whatever…)
  • fovc 2y ago
    The requirement for having two copies of the table simultaneously on systems that make it easy to add but not subtract storage. Otherwise pg_repack has worked really well. We solved the 2x storage with partitions, but it feels like the tail wagging the dog
• dfox 2y ago
  > Oracle and MySQL do not have this problem in their MVCC implementation because their secondary indexes do not store the physical addresses of new versions. Instead, they store a logical identifier (e.g., tuple id, primary key) that the DBMS then uses to look up the current version’s physical address. Now this may make secondary index reads slower since the DBMS has to resolve a logical identifier, but these DBMS have other advantages in their MVCC implementation to reduce overhead. Interesting behavior of MySQL that I have observed (~500GB database, with a schema that is more of an document oriented than relational) is that when you update single row doing SELECT id WHERE something; UPDATE what WHERE id=id is orders of magnitudes faster than UPDATE what WHERE something. I somehow suspect that this is the reason for this behavior. But well, the normal workload will not do that and this only slows down ad-hoc DML when you fix some inconsistency.
  • whazor 2y ago
    A SELECT is a readonly operation and can be performed in parallel. However, an UPDATE actually writes and might lock the table. Whereas UPDATE id=id allows for row level locking. There is also the risk of missing newly inserted records between the SELECT and the UPDATE.
    • nine_k 2y ago
      SELECT FOR UPDATE was invented to address this,
      • fipar 2y ago
        Or just select + update in a transaction, which with IIRC, with the default isolation level will use optimistic locking for the select part, unlike select for update.
        • nuttingd 2y ago
          You would need to use serializable isolation for this to hold true. Any isolation level less than serializable will use the snapshot that was active at the time of the select. In Postgres, even with the serializable isolation level, all transactions that touch the same rows must also be using the serializable isolation level or it's not really enforced. This is one aspect of serializable isolation in Postgres that seemed like a major gotcha for real world application development. There's no future proof solution: new code can be added that doesn't use the serializable isolation, and then the assumptions of isolation from the earlier code are no longer valid. FOR UPDATE is the only real solution in my eyes
• jongjong 2y ago
  For most cases, MVCC sounds like over-engineering. From the problem description: > The goal of MVCC in a DBMS is to allow multiple queries to read and write to the database simultaneously without interfering with each other when possible. How is that a problem for most use cases? If there is a read query which is taking a long time, with many rows, and some of these later rows happen to be updated mid-read but the earlier rows are not... It's not really a problem for the vast majority of application. Why is it better for all rows to be delivered out of date versus just the first half fetched being out of date? It's not ideal in either case but it's unavoidable that some requests can sometimes return out of date data. It seems like a tiny advantage. I suspect the real need to implement MVCC arose out of the desire for databases like Postgres to implement atomic transactions as a magical black box. IMO, two-phase commit is a simpler solution to this problem. It's not possible to fully hide concurrency complexity from the user; it ends up with tradeoffs.
  • kccqzy 2y ago
    One person's over engineering is another person's essential feature. I personally like the fact that Postgres supports the serializable isolation level that simplifies application programming. > It's not really a problem for the vast majority of application. This is true, but I don't even want to think about when it is indeed not really a problem and in the few cases when it is a problem.
    • magicalhippo 2y ago
      > I personally like the fact that Postgres supports the serializable isolation level that simplifies application programming. Not sure how PG implements it, but I tried it in a case where I did need it in SQLAnywhere, and only found out a bit too late that while the docs stated it was very detrimental to performance, the docs didn't explicitly say why, and it was much worse than I had assumed. I assumed it meant the transaction would lock the table, do it's thing and release on commit/rollback. And of course, that would hurt performance a lot if there was high contention. But no, that's not what it did. It was much, much worse. Instead of taking a lock on the whole table, it locked all the rows. Which went as swimmingly as you could expect on a table with thousands upon thousands of rows. Not sure why they did it this way, but yeah had to ditch that and went with the good old retry loop.
• thih9 2y ago
  > Then in the 2010s, it was MongoDB because non-durable writes made it “webscale“. Off topic, it was marketing all along: https://news.ycombinator.com/item?id=15124306 https://news.ycombinator.com/item?id=15124306
  • Hilift 2y ago
    It was designed by former DoubleClick engineers as an afterthought DIY db for another service because no other db met their requirements. Supposedly version 4.2.8 (2020) is fairly solid, i.e. no dirty writes. https://en.wikipedia.org/wiki/MongoDB#Technical_criticisms https://en.wikipedia.org/wiki/MongoDB#Technical_criticisms
• OrvalWintermute 2y ago
  This article is incorrect IMO - the following section in particular. “ In the 2000s, the conventional wisdom selected MySQL because rising tech stars like Google and Facebook were using it. Then in the 2010s, it was MongoDB because non-durable writes made it “webscale“. In the last five years, PostgreSQL has become the Internet’s darling DBMS. And for good reasons! It’s dependable, feature-rich, extensible, and well-suited for most operational workloads.” Smart engineers were choosing postgres not because of the logical fallacy of popularum, but for the following reasons: Data safety - not MyIsam, ACID, Similarity to Oracle, MVCC, SQL standards adherence, Postgres team, Helpful awesome community, Data types, High performance, BSD flexibility Above are the reasons I selected Postgres while at ATT early 2000s and our Oracle DBA found it a very easy transition. While Mysql went through rough transitions, PG has gone from strength to strength and ever improving path. I think Bruce Momjian is a big part of this success; they truly have an excellent community. <3
  • andruby 2y ago
    Similar. My preference switched from MySQL to PostgreSQL in 2005 when I wanted to use database views to create a "live" compatibility layer between an old (AS400) database schema and a modern Rails app. The preference kept growing thanks to data safety, DDL's in transactions, etc.
• halayli 2y ago
  This topic cannot be discussed alone without talking about disks. SSDs write 4k page at a time. Meaning if you're going to update 1 bit, the disk will read 4k, you update the bit, and it writes back a 4k page in a new slot. So the penalty for copying varies depending on the disk type.
  • srcreigh 2y ago
    Postgres pages are 8kb so the point is moot.
    • olavgg 2y ago
      The default is 8kb, but it can be recompiled for 4kb-32kb, I actually prefer 32kb because with ZSTD compression, it will most likey only use 8kb after being compressed. Average compress ratio with ZSTD, is usually between 4x-6x. But depending on how your compressable you data is, you may also get a lot less. Note that changing this block size, will require initialization of a new data file system for your Postgres database.
    • halayli 2y ago
      I am referring to physical pages in an SSD disk. The 8k pg page maps to 2 pages in a typical SSD disk. Your comment proves my initial point, which is write amplification cannot be discussed without talking about the disk types and their behavior.
      • emptiestplace 2y ago
        Huh? It seems you've forgotten that you were just saying that a single bit change would result in a 4096 byte write.
        • Tostino 2y ago
          > a single bit change would result in a 4096 byte write On (most) SSD hardware, regardless of what software you are using to do the writes. At least that's how I read their comment.
• mbreese 2y ago
  So, if this is such a problem, my question is — are the poor MVCC choices of Postgres enough to make the authors (or people here) recommend another RDBMS?
  • abenga 2y ago
    The last couple of paragraphs of the article answer this. (The answer is No).
    • mbreese 2y ago
      Thanks - I completely missed the “concluding remarks” paragraph the first time. After the “problems” sections, I apparently just stopped reading. For others who are curious: > But please don’t misunderstand our diatribe to mean that we don’t think you should ever use PostgreSQL. Although its MVCC implementation is the wrong way to do it, PostgreSQL is still our favorite DBMS. To love something is to be willing to work with its flaws.
• srcreigh 2y ago
  It’s really annoying to see people write that Postgres has a “primary index” and “secondary indexes”. No. That’s not what those words mean. Every index in Postgres is a secondary index.
  • sgarland 2y ago
    You’re not technically wrong, but even Postgres’ docs [0] use the term Primary Key. [0]: https://www.postgresql.org/docs/current/ddl-constraints.html https://www.postgresql.org/docs/current/ddl-constraints.html
    • srcreigh 2y ago
      Postgres primary key indexes are not primary indexes.
      • sgarland 2y ago
        I know that, I’m saying that it’s a fairly pedantic argument when even their own docs use the term loosely.
        • j16sdiz 2y ago
          "Primary Key" is the term in SQL standard. The url you linked is in "Part II: The SQL Language"
        • jeltz 2y ago
          Primary keys are primary indexes are two mostly unrelated terms.
        • deleted 2y ago
          [deleted]
• WuxiFingerHold 2y ago
  Putting aside the license / closed source issues with CockroachDB (CRDB) and just focus at it technically: CRDB uses MVVM too, but its storage is a key-value store. I know it uses some kind of garbage collection to remove the old versions. I wonder if CRDB (or other newer designed DBs) has circumvented those issues? Or don't we just hear from those issues as CRDB and the other newer DBs are not that widely used and mainly in the commercial space?
  • qaq 2y ago
    CRDB will be slower than PG on the same hardware.With CRDB you are trading off performance for ability to scale horizontally.
  • ddorian43 2y ago
    This is fixed in YugabyteDB that reuses the PostgreSQL query layer source code but uses it's own storage: https://www.yugabyte.com/blog/improve-postgresql/ https://www.yugabyte.com/blog/improve-postgresql/ (other issues too like XID wraparound etc). It's also apache2 license.
    • knowitnone 2y ago
      Thanks for pointing out Yugabyte. I did a search for performance comparisons and there seems (seemed?) to be some performance issues at least back in 2023 https://github.com/yugabyte/yugabyte-db/issues/10108 https://github.com/yugabyte/yugabyte-db/issues/10108 hopeful performance has improved since
      • ddorian43 2y ago
        Yes, performance is much better. But it's a bit apples to oranges comparisons because of distributed/sharding nature (example with bitmap scans https://www.yugabyte.com/blog/bitmap-scans-on-distributed-postgresql/ https://www.yugabyte.com/blog/bitmap-scans-on-distributed-po...), and always synchronous replication (https://www.yugabyte.com/blog/yugabytedb-resiliency-vs-postgresql-ha-solutions/ https://www.yugabyte.com/blog/yugabytedb-resiliency-vs-postg...).
• bluedonuts 2y ago
  Loved this post! Could anyone recommend a book (or other medium) with similar content about RMBDS internals?
  • cfors 2y ago
    While not strictly for RDBMS, I think this book is pretty close! https://www.databass.dev/ https://www.databass.dev/
  • xiasongh 2y ago
    CMU's Intro to Database Systems course is one of the best resources. Andy Pavlo has his lectures all up on youtube
• mxey 2y ago
  > The need for PostgreSQL to modify all of a table’s indexes for each update has several performance implications. Obviously, this makes update queries slower because the system has to do more work. You know, I was wondering something regarding this write amplification. It's true that MySQL doesn't need to update its indexes like that. However, MySQL replication relies on the binlog, where every change has to be written in addition to the database itself (InnoDB redo log and so on). So, it seems to me, MySQL, if used in a cluster, has a different kind of write amplification. One that PostgreSQL does not have, because it reuses its WAL for the replication. In addition, on the receiving side, MySQL first writes the incoming binlog to the relay log. The relay log is then consumed by the applier threads, creating more InnoDB writes and (by default) more binlog.
• uvas_pasas_per 2y ago
  My problem with PG is it just doesn't seem to help much with my situation. I want to write apps that work offline and sync data across devices using the 'cloud'. I think that means Sqlite on the client, but ?? for the server. I have yet to find a good book explaining techniques for this kind of replication/syncing.
  • tapoxi 2y ago
    CouchDB?
    • EGreg 2y ago
      PouchDB
    • uvas_pasas_per 2y ago
      Looks interesting, but I don't see anything for how to build it into an iOS or Android app. https://docs.couchdb.org/en/stable/install/index.html https://docs.couchdb.org/en/stable/install/index.html
      • tapoxi 2y ago
        There was a spinoff a while ago when they merged with Membase, I haven't used Couch in a few years but maybe this will work: https://docs.couchbase.com/couchbase-lite/current/swift/quickstart.html https://docs.couchbase.com/couchbase-lite/current/swift/quic...
  • beng-nl 2y ago
    At risk of saying something you know, CRDT’s may be a good fit for your use case. The problem is of course making changes offline that the user assumes are permanent but then later, when sync time comes, then turn out to conflict with changes made in the meantime. So changes can’t be made permanent. Either that requires difficult UX to reconcile or something that always will give you something consistent, like a crdt.
  • sgarland 2y ago
• didgetmaster 2y ago
  How big of an issue is this really for db users who work daily with large tables that are frequently updated but still have to be fast for queries? The article mentioned that there are nearly 900 different databases on the market. I am trying to build yet another one using a unique architecture I developed. It is very fast, but although it is designed for transactions; I haven't implemented them yet. I think if I spend the time and effort to do it right, this could be a real game changer (I think the architecture lends itself very well to a superior implementation); but I don't want to waste too much time on it if people don't really care one way or the other.
  • nasmorn 2y ago
    Unless you develop some holy grail solution I don’t think anyone will use an unproven DB for OLTP. At least not without HuMongos marketing spend
    • guenthert 2y ago
      To expand on this, DB administrators tend to be a conservative bunch. To some extend you can make a slow DB fast by spending big on hardware. No amount of money however will make an unsound DB reliable.
      • didgetmaster 2y ago
        I think it is obvious that no one will want to put their valuable data in an 'unsound' DB. To restate my original question: If you had two database systems that were equally reliable, but of course had different strengths and weaknesses, would the ability to update large tables without significantly impacting general query speeds, be a major factor in deciding between the two?
    • didgetmaster 2y ago
      Is that how PostgeSQL got so popular? After all, at one point it was unproven and I am not aware of a 'HuMongos marketing spend' changing that.
• Izkata 2y ago
  They mention autvacuum_vacuum_scale_factor, and its default value, but give no hint if they tried to change that. Obviously I have no access to their database, but one of piece of advice for ages has been, in situations similar to theirs where a lot of dead tuples accumulate and autovacuum is having trouble finishing, to lower this value so autovacuum runs much more often, so each run has less to do and less gets blocked.
• guenthert 2y ago
  "And second, traversing the entire version chain just to find the latest version (which is what most queries want) is wasteful." Is that what most queries want? I would have thought, that the latest version is part of a transaction which isn't committed yet and hence isn't even meant to be found by most queries (only those within the session which opened the modifying transaction). Where did I go wrong?